From 082dce5bf0d670723400fed1b8cb15055e00a663 Mon Sep 17 00:00:00 2001 From: Zeref996 <825276847@qq.com> Date: Thu, 4 Dec 2025 11:17:00 +0000 Subject: [PATCH] fix gpu acc monitor config --- .../accuracy/GPU/monitoring_configs_1.txt | 104 +++------- .../accuracy/GPU/monitoring_configs_2.txt | 54 ----- .../accuracy/GPU/monitoring_configs_3.txt | 96 ++------- .../accuracy/GPU/monitoring_configs_4.txt | 189 +++++++----------- 4 files changed, 114 insertions(+), 329 deletions(-) diff --git a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_1.txt b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_1.txt index 2fe40765..798ae661 100644 --- a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_1.txt +++ b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_1.txt @@ -4436,7 +4436,6 @@ paddle.Tensor.__add__(Tensor([104, 8, 29, 38],"float16"), Tensor([104, 1, 1, 38] paddle.Tensor.__add__(Tensor([104, 8, 29, 39],"float16"), Tensor([104, 1, 1, 39],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 30, 30],"float16"), Tensor([30, 30],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 31, 31],"float16"), Tensor([31, 31],"float16"), ) -paddle.Tensor.__add__(Tensor([104, 8, 32, 32],"float16"), Tensor([32, 32],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 32, 37],"float16"), Tensor([104, 1, 1, 37],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 33, 38],"float16"), Tensor([104, 1, 1, 38],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 35, 35],"float16"), Tensor([104, 1, 1, 35],"float16"), ) @@ -4445,9 +4444,7 @@ paddle.Tensor.__add__(Tensor([104, 8, 36, 27],"float16"), Tensor([104, 1, 1, 27] paddle.Tensor.__add__(Tensor([104, 8, 37, 30],"float16"), Tensor([104, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 37, 39],"float16"), Tensor([104, 1, 1, 39],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 37, 9],"float16"), Tensor([104, 1, 1, 9],"float16"), ) -paddle.Tensor.__add__(Tensor([104, 8, 38, 31],"float16"), Tensor([104, 1, 1, 31],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 38, 33],"float16"), Tensor([104, 1, 1, 33],"float16"), ) -paddle.Tensor.__add__(Tensor([104, 8, 38, 39],"float16"), Tensor([104, 1, 1, 39],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 39, 24],"float16"), Tensor([104, 1, 1, 24],"float16"), ) paddle.Tensor.__add__(Tensor([104, 8, 9, 9],"float16"), Tensor([104, 1, 1, 9],"float16"), ) paddle.Tensor.__add__(Tensor([104, 80],"float32"), Tensor([104, 80],"float32"), ) @@ -5724,7 +5721,6 @@ paddle.Tensor.__add__(Tensor([112, 12096],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([112, 128, 1, 1],"float32"), Tensor([112, 128, 1, 1],"float32"), ) paddle.Tensor.__add__(Tensor([112, 16, 12, 12],"float16"), Tensor([112, 1, 1, 12],"float16"), ) paddle.Tensor.__add__(Tensor([112, 16, 35, 35],"float16"), Tensor([35, 35],"float16"), ) -paddle.Tensor.__add__(Tensor([112, 16, 44, 42],"float16"), Tensor([112, 1, 1, 42],"float16"), ) paddle.Tensor.__add__(Tensor([112, 16, 45, 12],"float16"), Tensor([112, 1, 1, 12],"float16"), ) paddle.Tensor.__add__(Tensor([112, 17, 1024],"float32"), Tensor([112, 17, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([112, 1],"float32"), 1e-10, ) @@ -5783,7 +5779,6 @@ paddle.Tensor.__add__(Tensor([112, 8, 31, 31],"float16"), Tensor([112, 1, 1, 31] paddle.Tensor.__add__(Tensor([112, 8, 32, 35],"float16"), Tensor([112, 1, 1, 35],"float16"), ) paddle.Tensor.__add__(Tensor([112, 8, 33, 33],"float16"), Tensor([33, 33],"float16"), ) paddle.Tensor.__add__(Tensor([112, 8, 33, 36],"float16"), Tensor([112, 1, 1, 36],"float16"), ) -paddle.Tensor.__add__(Tensor([112, 8, 34, 21],"float16"), Tensor([112, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([112, 8, 35, 27],"float16"), Tensor([112, 1, 1, 27],"float16"), ) paddle.Tensor.__add__(Tensor([112, 8, 35, 29],"float16"), Tensor([112, 1, 1, 29],"float16"), ) paddle.Tensor.__add__(Tensor([112, 8, 35, 30],"float16"), Tensor([112, 1, 1, 30],"float16"), ) @@ -7065,8 +7060,6 @@ paddle.Tensor.__add__(Tensor([120, 120],"float32"), 40.0, ) paddle.Tensor.__add__(Tensor([120, 14, 1024],"float32"), Tensor([120, 14, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([120, 16, 1024],"float32"), Tensor([120, 16, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([120, 16, 14, 14],"float16"), Tensor([120, 1, 1, 14],"float16"), ) -paddle.Tensor.__add__(Tensor([120, 16, 37, 37],"float16"), Tensor([37, 37],"float16"), ) -paddle.Tensor.__add__(Tensor([120, 16, 37, 42],"float16"), Tensor([120, 1, 1, 42],"float16"), ) paddle.Tensor.__add__(Tensor([120, 16, 40, 42],"float16"), Tensor([120, 1, 1, 42],"float16"), ) paddle.Tensor.__add__(Tensor([120, 1],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([120, 1],"float32"), Tensor([120, 1],"float32"), ) @@ -7122,14 +7115,11 @@ paddle.Tensor.__add__(Tensor([120, 8, 24, 24],"float16"), Tensor([120, 1, 1, 24] paddle.Tensor.__add__(Tensor([120, 8, 24, 24],"float16"), Tensor([24, 24],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 25, 25],"float16"), Tensor([120, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 25, 25],"float16"), Tensor([25, 25],"float16"), ) -paddle.Tensor.__add__(Tensor([120, 8, 26, 33],"float16"), Tensor([120, 1, 1, 33],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 28, 34],"float16"), Tensor([120, 1, 1, 34],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 29, 29],"float16"), Tensor([120, 1, 1, 29],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 29, 29],"float16"), Tensor([29, 29],"float16"), ) -paddle.Tensor.__add__(Tensor([120, 8, 29, 34],"float16"), Tensor([120, 1, 1, 34],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 32, 33],"float16"), Tensor([120, 1, 1, 33],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 32, 34],"float16"), Tensor([120, 1, 1, 34],"float16"), ) -paddle.Tensor.__add__(Tensor([120, 8, 33, 30],"float16"), Tensor([120, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 34, 24],"float16"), Tensor([120, 1, 1, 24],"float16"), ) paddle.Tensor.__add__(Tensor([120, 8, 34, 28],"float16"), Tensor([120, 1, 1, 28],"float16"), ) paddle.Tensor.__add__(Tensor([120, 80, 3, 3],"float32"), Tensor([120, 80, 3, 3],"float32"), ) @@ -8398,7 +8388,6 @@ paddle.Tensor.__add__(Tensor([128, 128],"float32"), Tensor([128, 128],"float32") paddle.Tensor.__add__(Tensor([128, 13, 1024],"float32"), Tensor([128, 13, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([128, 1536, 7, 7],"float32"), Tensor([128, 1536, 7, 7],"float32"), ) paddle.Tensor.__add__(Tensor([128, 16, 1024],"float16"), Tensor([128, 16, 1024],"float16"), ) -paddle.Tensor.__add__(Tensor([128, 16, 39, 39],"float16"), Tensor([39, 39],"float16"), ) paddle.Tensor.__add__(Tensor([128, 16, 40, 11],"float16"), Tensor([128, 1, 1, 11],"float16"), ) paddle.Tensor.__add__(Tensor([128, 16, 49, 32],"float32"), Tensor([128, 16, 49, 32],"float32"), ) paddle.Tensor.__add__(Tensor([128, 160, 14, 14],"float32"), Tensor([128, 160, 14, 14],"float32"), ) @@ -8536,7 +8525,6 @@ paddle.Tensor.__add__(Tensor([128, 784, 192],"float32"), Tensor([128, 784, 192], paddle.Tensor.__add__(Tensor([128, 784, 256],"float16"), Tensor([128, 784, 256],"float16"), ) paddle.Tensor.__add__(Tensor([128, 8, 18, 18],"float16"), Tensor([128, 1, 1, 18],"float16"), ) paddle.Tensor.__add__(Tensor([128, 8, 23, 23],"float16"), Tensor([128, 1, 1, 23],"float16"), ) -paddle.Tensor.__add__(Tensor([128, 8, 23, 23],"float16"), Tensor([23, 23],"float16"), ) paddle.Tensor.__add__(Tensor([128, 8, 24, 24],"float16"), Tensor([128, 1, 1, 24],"float16"), ) paddle.Tensor.__add__(Tensor([128, 8, 25, 25],"float16"), Tensor([128, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([128, 8, 25, 32],"float16"), Tensor([128, 1, 1, 32],"float16"), ) @@ -8562,7 +8550,6 @@ paddle.Tensor.__add__(Tensor([128, 96, 1, 1],"float32"), Tensor([128, 96, 1, 1], paddle.Tensor.__add__(Tensor([128, 96, 14, 14],"float32"), Tensor([128, 96, 14, 14],"float32"), ) paddle.Tensor.__add__(Tensor([128, 96, 3, 3],"float32"), Tensor([128, 96, 3, 3],"float32"), ) paddle.Tensor.__add__(Tensor([128, 96, 56, 56],"float16"), Tensor([128, 96, 56, 56],"float16"), ) -paddle.Tensor.__add__(Tensor([128, 96, 56, 56],"float16"), Tensor([96, 1, 1],"float16"), ) paddle.Tensor.__add__(Tensor([128, 96, 56, 56],"float32"), Tensor([128, 96, 56, 56],"float32"), ) paddle.Tensor.__add__(Tensor([1280, 1, 5, 5],"float32"), Tensor([1280, 1, 5, 5],"float32"), ) paddle.Tensor.__add__(Tensor([1280, 10],"float32"), Tensor([1280, 10],"float32"), ) @@ -9924,20 +9911,16 @@ paddle.Tensor.__add__(Tensor([136, 8, 21, 29],"float16"), Tensor([136, 1, 1, 29] paddle.Tensor.__add__(Tensor([136, 8, 22, 22],"float16"), Tensor([136, 1, 1, 22],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 22, 22],"float16"), Tensor([22, 22],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 23, 23],"float16"), Tensor([136, 1, 1, 23],"float16"), ) -paddle.Tensor.__add__(Tensor([136, 8, 23, 23],"float16"), Tensor([23, 23],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 23, 30],"float16"), Tensor([136, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 24, 24],"float16"), Tensor([136, 1, 1, 24],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 24, 30],"float16"), Tensor([136, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 25, 29],"float16"), Tensor([136, 1, 1, 29],"float16"), ) -paddle.Tensor.__add__(Tensor([136, 8, 25, 30],"float16"), Tensor([136, 1, 1, 30],"float16"), ) -paddle.Tensor.__add__(Tensor([136, 8, 26, 26],"float16"), Tensor([136, 1, 1, 26],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 26, 26],"float16"), Tensor([26, 26],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 28, 21],"float16"), Tensor([136, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 29, 19],"float16"), Tensor([136, 1, 1, 19],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 29, 26],"float16"), Tensor([136, 1, 1, 26],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 29, 28],"float16"), Tensor([136, 1, 1, 28],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 29, 30],"float16"), Tensor([136, 1, 1, 30],"float16"), ) -paddle.Tensor.__add__(Tensor([136, 8, 30, 21],"float16"), Tensor([136, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 30, 22],"float16"), Tensor([136, 1, 1, 22],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 30, 23],"float16"), Tensor([136, 1, 1, 23],"float16"), ) paddle.Tensor.__add__(Tensor([136, 8, 30, 24],"float16"), Tensor([136, 1, 1, 24],"float16"), ) @@ -11137,7 +11120,6 @@ paddle.Tensor.__add__(Tensor([144, 144, 3, 3],"float32"), Tensor([144, 144, 3, 3 paddle.Tensor.__add__(Tensor([144, 144],"float32"), 20.0, ) paddle.Tensor.__add__(Tensor([144, 144],"int64"), 11, ) paddle.Tensor.__add__(Tensor([144, 15, 512],"float32"), Tensor([144, 15, 512],"float32"), ) -paddle.Tensor.__add__(Tensor([144, 16, 34, 23],"float16"), Tensor([144, 1, 1, 23],"float16"), ) paddle.Tensor.__add__(Tensor([144, 19, 512],"float32"), Tensor([144, 19, 512],"float32"), ) paddle.Tensor.__add__(Tensor([144, 192, 28, 28],"float32"), Tensor([144, 192, 28, 28],"float32"), ) paddle.Tensor.__add__(Tensor([144, 196, 384],"float32"), Tensor([144, 196, 384],"float32"), ) @@ -11198,9 +11180,7 @@ paddle.Tensor.__add__(Tensor([144, 8, 20, 28],"float16"), Tensor([144, 1, 1, 28] paddle.Tensor.__add__(Tensor([144, 8, 21, 27],"float16"), Tensor([144, 1, 1, 27],"float16"), ) paddle.Tensor.__add__(Tensor([144, 8, 22, 22],"float16"), Tensor([22, 22],"float16"), ) paddle.Tensor.__add__(Tensor([144, 8, 22, 27],"float16"), Tensor([144, 1, 1, 27],"float16"), ) -paddle.Tensor.__add__(Tensor([144, 8, 23, 23],"float16"), Tensor([144, 1, 1, 23],"float16"), ) paddle.Tensor.__add__(Tensor([144, 8, 24, 27],"float16"), Tensor([144, 1, 1, 27],"float16"), ) -paddle.Tensor.__add__(Tensor([144, 8, 25, 25],"float16"), Tensor([144, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([144, 8, 26, 27],"float16"), Tensor([144, 1, 1, 27],"float16"), ) paddle.Tensor.__add__(Tensor([144, 8, 27, 15],"float16"), Tensor([144, 1, 1, 15],"float16"), ) paddle.Tensor.__add__(Tensor([144, 8, 27, 22],"float16"), Tensor([144, 1, 1, 22],"float16"), ) @@ -12328,12 +12308,10 @@ paddle.Tensor.__add__(Tensor([152, 8, 22, 22],"float16"), Tensor([22, 22],"float paddle.Tensor.__add__(Tensor([152, 8, 24, 24],"float16"), Tensor([152, 1, 1, 24],"float16"), ) paddle.Tensor.__add__(Tensor([152, 8, 24, 26],"float16"), Tensor([152, 1, 1, 26],"float16"), ) paddle.Tensor.__add__(Tensor([152, 8, 26, 17],"float16"), Tensor([152, 1, 1, 17],"float16"), ) -paddle.Tensor.__add__(Tensor([152, 8, 26, 18],"float16"), Tensor([152, 1, 1, 18],"float16"), ) paddle.Tensor.__add__(Tensor([152, 8, 26, 20],"float16"), Tensor([152, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([152, 8, 26, 21],"float16"), Tensor([152, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([152, 8, 26, 23],"float16"), Tensor([152, 1, 1, 23],"float16"), ) paddle.Tensor.__add__(Tensor([152, 8, 26, 26],"float16"), Tensor([152, 1, 1, 26],"float16"), ) -paddle.Tensor.__add__(Tensor([152, 8, 26, 26],"float16"), Tensor([26, 26],"float16"), ) paddle.Tensor.__add__(Tensor([152, 80],"float32"), Tensor([152, 80],"float32"), ) paddle.Tensor.__add__(Tensor([152, 8400],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([152, 9261],"float32"), 1e-10, ) @@ -15040,8 +15018,6 @@ paddle.Tensor.__add__(Tensor([160, 120, 1, 1],"float32"), Tensor([160, 120, 1, 1 paddle.Tensor.__add__(Tensor([160, 12096],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([160, 16, 23, 23],"float16"), Tensor([160, 1, 1, 23],"float16"), ) paddle.Tensor.__add__(Tensor([160, 16, 25, 25],"float16"), Tensor([25, 25],"float16"), ) -paddle.Tensor.__add__(Tensor([160, 16, 31, 28],"float16"), Tensor([160, 1, 1, 28],"float16"), ) -paddle.Tensor.__add__(Tensor([160, 16, 32, 26],"float16"), Tensor([160, 1, 1, 26],"float16"), ) paddle.Tensor.__add__(Tensor([160, 16, 512],"float32"), Tensor([160, 16, 512],"float32"), ) paddle.Tensor.__add__(Tensor([160, 160, 1, 1],"float32"), Tensor([160, 160, 1, 1],"float32"), ) paddle.Tensor.__add__(Tensor([160, 160, 3, 3],"float32"), Tensor([160, 160, 3, 3],"float32"), ) @@ -15096,7 +15072,6 @@ paddle.Tensor.__add__(Tensor([160, 8, 17, 25],"float16"), Tensor([160, 1, 1, 25] paddle.Tensor.__add__(Tensor([160, 8, 18, 18],"float16"), Tensor([160, 1, 1, 18],"float16"), ) paddle.Tensor.__add__(Tensor([160, 8, 19, 19],"float16"), Tensor([160, 1, 1, 19],"float16"), ) paddle.Tensor.__add__(Tensor([160, 8, 19, 25],"float16"), Tensor([160, 1, 1, 25],"float16"), ) -paddle.Tensor.__add__(Tensor([160, 8, 20, 25],"float16"), Tensor([160, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([160, 8, 21, 21],"float16"), Tensor([160, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([160, 8, 21, 25],"float16"), Tensor([160, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([160, 8, 22, 11],"float16"), Tensor([160, 1, 1, 11],"float16"), ) @@ -17276,7 +17251,6 @@ paddle.Tensor.__add__(Tensor([176, 16, 1024],"float32"), Tensor([176, 16, 1024], paddle.Tensor.__add__(Tensor([176, 16, 16, 16],"float16"), Tensor([176, 1, 1, 16],"float16"), ) paddle.Tensor.__add__(Tensor([176, 16, 21, 21],"float16"), Tensor([21, 21],"float16"), ) paddle.Tensor.__add__(Tensor([176, 16, 24, 24],"float16"), Tensor([176, 1, 1, 24],"float16"), ) -paddle.Tensor.__add__(Tensor([176, 16, 28, 23],"float16"), Tensor([176, 1, 1, 23],"float16"), ) paddle.Tensor.__add__(Tensor([176, 16, 512],"float32"), Tensor([176, 16, 512],"float32"), ) paddle.Tensor.__add__(Tensor([176, 17, 512],"float32"), Tensor([176, 17, 512],"float32"), ) paddle.Tensor.__add__(Tensor([176, 176, 1, 1],"float32"), Tensor([176, 176, 1, 1],"float32"), ) @@ -19363,7 +19337,6 @@ paddle.Tensor.__add__(Tensor([192, 144, 1, 1],"float32"), Tensor([192, 144, 1, 1 paddle.Tensor.__add__(Tensor([192, 15, 512],"float32"), Tensor([192, 15, 512],"float32"), ) paddle.Tensor.__add__(Tensor([192, 16, 19, 19],"float16"), Tensor([19, 19],"float16"), ) paddle.Tensor.__add__(Tensor([192, 16, 19, 26],"float16"), Tensor([192, 1, 1, 26],"float16"), ) -paddle.Tensor.__add__(Tensor([192, 16, 20, 20],"float16"), Tensor([20, 20],"float16"), ) paddle.Tensor.__add__(Tensor([192, 16, 22, 22],"float16"), Tensor([22, 22],"float16"), ) paddle.Tensor.__add__(Tensor([192, 16, 24, 24],"float16"), Tensor([192, 1, 1, 24],"float16"), ) paddle.Tensor.__add__(Tensor([192, 16, 32, 160],"float16"), Tensor([192, 16, 32, 160],"float16"), ) @@ -19430,7 +19403,6 @@ paddle.Tensor.__add__(Tensor([192, 8, 16, 16],"float16"), Tensor([192, 1, 1, 16] paddle.Tensor.__add__(Tensor([192, 8, 17, 17],"float16"), Tensor([17, 17],"float16"), ) paddle.Tensor.__add__(Tensor([192, 8, 17, 17],"float16"), Tensor([192, 1, 1, 17],"float16"), ) paddle.Tensor.__add__(Tensor([192, 8, 17, 21],"float16"), Tensor([192, 1, 1, 21],"float16"), ) -paddle.Tensor.__add__(Tensor([192, 8, 18, 21],"float16"), Tensor([192, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([192, 8, 19, 19],"float16"), Tensor([192, 1, 1, 19],"float16"), ) paddle.Tensor.__add__(Tensor([192, 8, 20, 20],"float16"), Tensor([192, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([192, 8, 21, 17],"float16"), Tensor([192, 1, 1, 17],"float16"), ) @@ -25797,7 +25769,6 @@ paddle.Tensor.__add__(Tensor([200, 6069],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([200, 6804],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([200, 7581],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([200, 8, 14, 14],"float16"), Tensor([14, 14],"float16"), ) -paddle.Tensor.__add__(Tensor([200, 8, 14, 20],"float16"), Tensor([200, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([200, 8, 15, 20],"float16"), Tensor([200, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([200, 8, 17, 20],"float16"), Tensor([200, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([200, 8, 18, 18],"float16"), Tensor([18, 18],"float16"), ) @@ -28628,7 +28599,6 @@ paddle.Tensor.__add__(Tensor([224, 8, 18, 14],"float16"), Tensor([224, 1, 1, 14] paddle.Tensor.__add__(Tensor([224, 8, 18, 15],"float16"), Tensor([224, 1, 1, 15],"float16"), ) paddle.Tensor.__add__(Tensor([224, 8, 18, 16],"float16"), Tensor([224, 1, 1, 16],"float16"), ) paddle.Tensor.__add__(Tensor([224, 8, 18, 17],"float16"), Tensor([224, 1, 1, 17],"float16"), ) -paddle.Tensor.__add__(Tensor([224, 8, 18, 18],"float16"), Tensor([18, 18],"float16"), ) paddle.Tensor.__add__(Tensor([224, 80],"float32"), Tensor([224, 80],"float32"), ) paddle.Tensor.__add__(Tensor([224, 8400],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([224, 9261],"float32"), 1e-10, ) @@ -29451,7 +29421,6 @@ paddle.Tensor.__add__(Tensor([232, 16, 16, 16],"float16"), Tensor([16, 16],"floa paddle.Tensor.__add__(Tensor([232, 16, 17, 22],"float16"), Tensor([232, 1, 1, 22],"float16"), ) paddle.Tensor.__add__(Tensor([232, 16, 18, 18],"float16"), Tensor([18, 18],"float16"), ) paddle.Tensor.__add__(Tensor([232, 16, 20, 22],"float16"), Tensor([232, 1, 1, 22],"float16"), ) -paddle.Tensor.__add__(Tensor([232, 16, 21, 21],"float16"), Tensor([21, 21],"float16"), ) paddle.Tensor.__add__(Tensor([232, 16, 22, 20],"float16"), Tensor([232, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([232, 16, 22, 22],"float16"), Tensor([22, 22],"float16"), ) paddle.Tensor.__add__(Tensor([232, 17, 1024],"float32"), Tensor([232, 17, 1024],"float32"), ) @@ -30405,12 +30374,10 @@ paddle.Tensor.__add__(Tensor([24, 7581],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([24, 7681],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([24, 8, 124, 124],"float16"), Tensor([24, 1, 1, 124],"float16"), ) paddle.Tensor.__add__(Tensor([24, 8, 137, 87],"float16"), Tensor([24, 1, 1, 87],"float16"), ) -paddle.Tensor.__add__(Tensor([24, 8, 151, 72],"float16"), Tensor([24, 1, 1, 72],"float16"), ) paddle.Tensor.__add__(Tensor([24, 8, 68, 68],"float16"), Tensor([24, 1, 1, 68],"float16"), ) paddle.Tensor.__add__(Tensor([24, 8, 80, 80],"float16"), Tensor([24, 1, 1, 80],"float16"), ) paddle.Tensor.__add__(Tensor([24, 8, 82, 82],"float16"), Tensor([24, 1, 1, 82],"float16"), ) paddle.Tensor.__add__(Tensor([24, 8, 83, 83],"float16"), Tensor([24, 1, 1, 83],"float16"), ) -paddle.Tensor.__add__(Tensor([24, 8, 97, 97],"float16"), Tensor([24, 1, 1, 97],"float16"), ) paddle.Tensor.__add__(Tensor([24, 80, 512],"float32"), Tensor([24, 80, 512],"float32"), ) paddle.Tensor.__add__(Tensor([24, 81, 1024],"float32"), Tensor([24, 81, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([24, 81, 512],"float32"), Tensor([24, 81, 512],"float32"), ) @@ -30445,10 +30412,8 @@ paddle.Tensor.__add__(Tensor([240, 15, 1024],"float32"), Tensor([240, 15, 1024], paddle.Tensor.__add__(Tensor([240, 15, 512],"float32"), Tensor([240, 15, 512],"float32"), ) paddle.Tensor.__add__(Tensor([240, 16, 1024],"float32"), Tensor([240, 16, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([240, 16, 14, 14],"float16"), Tensor([240, 1, 1, 14],"float16"), ) -paddle.Tensor.__add__(Tensor([240, 16, 16, 16],"float16"), Tensor([16, 16],"float16"), ) paddle.Tensor.__add__(Tensor([240, 16, 19, 19],"float16"), Tensor([19, 19],"float16"), ) paddle.Tensor.__add__(Tensor([240, 16, 21, 19],"float16"), Tensor([240, 1, 1, 19],"float16"), ) -paddle.Tensor.__add__(Tensor([240, 16, 21, 21],"float16"), Tensor([21, 21],"float16"), ) paddle.Tensor.__add__(Tensor([240, 16, 21, 7],"float16"), Tensor([240, 1, 1, 7],"float16"), ) paddle.Tensor.__add__(Tensor([240, 16, 512],"float32"), Tensor([240, 16, 512],"float32"), ) paddle.Tensor.__add__(Tensor([240, 16, 7, 7],"float16"), Tensor([240, 1, 1, 7],"float16"), ) @@ -32204,7 +32169,6 @@ paddle.Tensor.__add__(Tensor([256, 8, 14, 14],"float16"), Tensor([14, 14],"float paddle.Tensor.__add__(Tensor([256, 8, 14, 14],"float16"), Tensor([256, 1, 1, 14],"float16"), ) paddle.Tensor.__add__(Tensor([256, 8, 14, 16],"float16"), Tensor([256, 1, 1, 16],"float16"), ) paddle.Tensor.__add__(Tensor([256, 8, 15, 15],"float16"), Tensor([15, 15],"float16"), ) -paddle.Tensor.__add__(Tensor([256, 8, 15, 16],"float16"), Tensor([256, 1, 1, 16],"float16"), ) paddle.Tensor.__add__(Tensor([256, 8, 16, 11],"float16"), Tensor([256, 1, 1, 11],"float16"), ) paddle.Tensor.__add__(Tensor([256, 8, 16, 12],"float16"), Tensor([256, 1, 1, 12],"float16"), ) paddle.Tensor.__add__(Tensor([256, 8, 16, 13],"float16"), Tensor([256, 1, 1, 13],"float16"), ) @@ -34402,7 +34366,6 @@ paddle.Tensor.__add__(Tensor([280, 14, 1024],"float32"), Tensor([280, 14, 1024], paddle.Tensor.__add__(Tensor([280, 15, 1024],"float32"), Tensor([280, 15, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([280, 16, 1024],"float32"), Tensor([280, 16, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([280, 16, 16, 16],"float16"), Tensor([16, 16],"float16"), ) -paddle.Tensor.__add__(Tensor([280, 16, 17, 17],"float16"), Tensor([280, 1, 1, 17],"float16"), ) paddle.Tensor.__add__(Tensor([280, 16, 18, 18],"float16"), Tensor([18, 18],"float16"), ) paddle.Tensor.__add__(Tensor([280, 17, 1024],"float32"), Tensor([280, 17, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([280, 18, 1024],"float32"), Tensor([280, 18, 1024],"float32"), ) @@ -35752,7 +35715,6 @@ paddle.Tensor.__add__(Tensor([296, 15, 1024],"float32"), Tensor([296, 15, 1024], paddle.Tensor.__add__(Tensor([296, 16, 1024],"float32"), Tensor([296, 16, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([296, 16, 11, 11],"float16"), Tensor([296, 1, 1, 11],"float16"), ) paddle.Tensor.__add__(Tensor([296, 16, 13, 13],"float16"), Tensor([13, 13],"float16"), ) -paddle.Tensor.__add__(Tensor([296, 16, 13, 13],"float16"), Tensor([296, 1, 1, 13],"float16"), ) paddle.Tensor.__add__(Tensor([296, 16, 14, 14],"float16"), Tensor([14, 14],"float16"), ) paddle.Tensor.__add__(Tensor([296, 16, 16, 16],"float16"), Tensor([16, 16],"float16"), ) paddle.Tensor.__add__(Tensor([296, 16, 16, 17],"float16"), Tensor([296, 1, 1, 17],"float16"), ) @@ -36265,7 +36227,6 @@ paddle.Tensor.__add__(Tensor([3, 159, 256],"float32"), Tensor([3, 159, 256],"flo paddle.Tensor.__add__(Tensor([3, 16, 256],"float32"), Tensor([1, 16, 256],"float32"), ) paddle.Tensor.__add__(Tensor([3, 16, 256],"float32"), Tensor([3, 16, 256],"float32"), ) paddle.Tensor.__add__(Tensor([3, 16, 4, 4],"float32"), Tensor([3, 16, 4, 4],"float32"), ) -paddle.Tensor.__add__(Tensor([3, 16, 64, 64],"float16"), Tensor([3, 1, 64, 64],"float16"), ) paddle.Tensor.__add__(Tensor([3, 160, 256],"float32"), Tensor([1, 160, 256],"float32"), ) paddle.Tensor.__add__(Tensor([3, 160, 256],"float32"), Tensor([3, 160, 256],"float32"), ) paddle.Tensor.__add__(Tensor([3, 161, 256],"float32"), Tensor([1, 161, 256],"float32"), ) @@ -38568,9 +38529,7 @@ paddle.Tensor.__add__(Tensor([32, 78, 512],"float32"), Tensor([32, 78, 512],"flo paddle.Tensor.__add__(Tensor([32, 79, 512],"float32"), Tensor([32, 79, 512],"float32"), ) paddle.Tensor.__add__(Tensor([32, 8, 4, 4],"float32"), Tensor([32, 8, 4, 4],"float32"), ) paddle.Tensor.__add__(Tensor([32, 8, 46, 46],"float16"), Tensor([32, 1, 1, 46],"float16"), ) -paddle.Tensor.__add__(Tensor([32, 8, 67, 67],"float16"), Tensor([32, 1, 1, 67],"float16"), ) paddle.Tensor.__add__(Tensor([32, 8, 69, 69],"float16"), Tensor([32, 1, 1, 69],"float16"), ) -paddle.Tensor.__add__(Tensor([32, 8, 70, 70],"float16"), Tensor([32, 1, 1, 70],"float16"), ) paddle.Tensor.__add__(Tensor([32, 8, 79, 79],"float16"), Tensor([32, 1, 1, 79],"float16"), ) paddle.Tensor.__add__(Tensor([32, 80, 1024],"float32"), Tensor([32, 80, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([32, 80, 512],"float32"), Tensor([32, 80, 512],"float32"), ) @@ -39698,8 +39657,6 @@ paddle.Tensor.__add__(Tensor([336, 14, 1024],"float32"), Tensor([336, 14, 1024], paddle.Tensor.__add__(Tensor([336, 15, 1024],"float32"), Tensor([336, 15, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([336, 15],"float32"), Tensor([336, 15],"float32"), ) paddle.Tensor.__add__(Tensor([336, 16, 11, 11],"float16"), Tensor([11, 11],"float16"), ) -paddle.Tensor.__add__(Tensor([336, 16, 12, 12],"float16"), Tensor([12, 12],"float16"), ) -paddle.Tensor.__add__(Tensor([336, 16, 13, 13],"float16"), Tensor([13, 13],"float16"), ) paddle.Tensor.__add__(Tensor([336, 16, 13, 13],"float16"), Tensor([336, 1, 1, 13],"float16"), ) paddle.Tensor.__add__(Tensor([336, 16, 13, 15],"float16"), Tensor([336, 1, 1, 15],"float16"), ) paddle.Tensor.__add__(Tensor([336, 16, 15, 13],"float16"), Tensor([336, 1, 1, 13],"float16"), ) @@ -41346,12 +41303,9 @@ paddle.Tensor.__add__(Tensor([360, 11, 512],"float32"), Tensor([360, 11, 512],"f paddle.Tensor.__add__(Tensor([360, 12, 1024],"float32"), Tensor([360, 12, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([360, 13, 1024],"float32"), Tensor([360, 13, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([360, 14, 1024],"float32"), Tensor([360, 14, 1024],"float32"), ) -paddle.Tensor.__add__(Tensor([360, 16, 13, 13],"float16"), Tensor([360, 1, 1, 13],"float16"), ) paddle.Tensor.__add__(Tensor([360, 16, 14, 10],"float16"), Tensor([360, 1, 1, 10],"float16"), ) paddle.Tensor.__add__(Tensor([360, 16, 14, 12],"float16"), Tensor([360, 1, 1, 12],"float16"), ) paddle.Tensor.__add__(Tensor([360, 16, 14, 13],"float16"), Tensor([360, 1, 1, 13],"float16"), ) -paddle.Tensor.__add__(Tensor([360, 16, 14, 14],"float16"), Tensor([360, 1, 1, 14],"float16"), ) -paddle.Tensor.__add__(Tensor([360, 16, 9, 9],"float16"), Tensor([360, 1, 1, 9],"float16"), ) paddle.Tensor.__add__(Tensor([360, 1],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([360, 1],"float32"), Tensor([360, 1],"float32"), ) paddle.Tensor.__add__(Tensor([360, 1],"int64"), Tensor([4],"int64"), ) @@ -43052,7 +43006,6 @@ paddle.Tensor.__add__(Tensor([392, 13, 1024],"float32"), Tensor([392, 13, 1024], paddle.Tensor.__add__(Tensor([392, 16, 10, 10],"float16"), Tensor([10, 10],"float16"), ) paddle.Tensor.__add__(Tensor([392, 16, 11, 11],"float16"), Tensor([392, 1, 1, 11],"float16"), ) paddle.Tensor.__add__(Tensor([392, 16, 12, 12],"float16"), Tensor([12, 12],"float16"), ) -paddle.Tensor.__add__(Tensor([392, 16, 12, 12],"float16"), Tensor([392, 1, 1, 12],"float16"), ) paddle.Tensor.__add__(Tensor([392, 16, 12, 13],"float16"), Tensor([392, 1, 1, 13],"float16"), ) paddle.Tensor.__add__(Tensor([392, 16, 13, 13],"float16"), Tensor([392, 1, 1, 13],"float16"), ) paddle.Tensor.__add__(Tensor([392, 1],"float32"), 1e-10, ) @@ -46831,10 +46784,8 @@ paddle.Tensor.__add__(Tensor([40, 8, 48, 48],"float16"), Tensor([40, 1, 1, 48]," paddle.Tensor.__add__(Tensor([40, 8, 51, 51],"float16"), Tensor([40, 1, 1, 51],"float16"), ) paddle.Tensor.__add__(Tensor([40, 8, 74, 74],"float16"), Tensor([40, 1, 1, 74],"float16"), ) paddle.Tensor.__add__(Tensor([40, 8, 77, 77],"float16"), Tensor([77, 77],"float16"), ) -paddle.Tensor.__add__(Tensor([40, 8, 77, 86],"float16"), Tensor([40, 1, 1, 86],"float16"), ) paddle.Tensor.__add__(Tensor([40, 8, 80, 80],"float16"), Tensor([80, 80],"float16"), ) paddle.Tensor.__add__(Tensor([40, 8, 82, 56],"float16"), Tensor([40, 1, 1, 56],"float16"), ) -paddle.Tensor.__add__(Tensor([40, 8, 83, 83],"float16"), Tensor([83, 83],"float16"), ) paddle.Tensor.__add__(Tensor([40, 8, 86, 71],"float16"), Tensor([40, 1, 1, 71],"float16"), ) paddle.Tensor.__add__(Tensor([40, 80, 512],"float32"), Tensor([40, 80, 512],"float32"), ) paddle.Tensor.__add__(Tensor([40, 81, 512],"float32"), Tensor([40, 81, 512],"float32"), ) @@ -47250,7 +47201,6 @@ paddle.Tensor.__add__(Tensor([408, 10, 1024],"float32"), Tensor([408, 10, 1024], paddle.Tensor.__add__(Tensor([408, 10, 512],"float32"), Tensor([408, 10, 512],"float32"), ) paddle.Tensor.__add__(Tensor([408, 11],"float32"), Tensor([408, 11],"float32"), ) paddle.Tensor.__add__(Tensor([408, 12, 1024],"float32"), Tensor([408, 12, 1024],"float32"), ) -paddle.Tensor.__add__(Tensor([408, 16, 12, 10],"float16"), Tensor([408, 1, 1, 10],"float16"), ) paddle.Tensor.__add__(Tensor([408, 17],"float32"), Tensor([408, 17],"float32"), ) paddle.Tensor.__add__(Tensor([408, 1],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([408, 1],"float32"), Tensor([408, 1],"float32"), ) @@ -50372,16 +50322,11 @@ paddle.Tensor.__add__(Tensor([48, 79, 1024],"float32"), Tensor([48, 79, 1024],"f paddle.Tensor.__add__(Tensor([48, 79, 512],"float32"), Tensor([48, 79, 512],"float32"), ) paddle.Tensor.__add__(Tensor([48, 8, 32, 32],"float16"), Tensor([48, 1, 1, 32],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 34, 34],"float16"), Tensor([48, 1, 1, 34],"float16"), ) -paddle.Tensor.__add__(Tensor([48, 8, 36, 36],"float16"), Tensor([48, 1, 1, 36],"float16"), ) -paddle.Tensor.__add__(Tensor([48, 8, 64, 36],"float16"), Tensor([48, 1, 1, 36],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 68, 68],"float16"), Tensor([48, 1, 1, 68],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 68, 68],"float16"), Tensor([68, 68],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 69, 75],"float16"), Tensor([48, 1, 1, 75],"float16"), ) -paddle.Tensor.__add__(Tensor([48, 8, 73, 73],"float16"), Tensor([48, 1, 1, 73],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 78, 30],"float16"), Tensor([48, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 78, 36],"float16"), Tensor([48, 1, 1, 36],"float16"), ) -paddle.Tensor.__add__(Tensor([48, 8, 78, 67],"float16"), Tensor([48, 1, 1, 67],"float16"), ) -paddle.Tensor.__add__(Tensor([48, 8, 79, 79],"float16"), Tensor([48, 1, 1, 79],"float16"), ) paddle.Tensor.__add__(Tensor([48, 8, 83, 25],"float16"), Tensor([48, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([48, 80, 512],"float32"), Tensor([48, 80, 512],"float32"), ) paddle.Tensor.__add__(Tensor([48, 81, 1024],"float32"), Tensor([48, 81, 1024],"float32"), ) @@ -53044,8 +52989,6 @@ paddle.Tensor.__add__(Tensor([56, 8, 65, 45],"float16"), Tensor([56, 1, 1, 45]," paddle.Tensor.__add__(Tensor([56, 8, 65, 60],"float16"), Tensor([56, 1, 1, 60],"float16"), ) paddle.Tensor.__add__(Tensor([56, 8, 68, 59],"float16"), Tensor([56, 1, 1, 59],"float16"), ) paddle.Tensor.__add__(Tensor([56, 8, 69, 26],"float16"), Tensor([56, 1, 1, 26],"float16"), ) -paddle.Tensor.__add__(Tensor([56, 8, 70, 73],"float16"), Tensor([56, 1, 1, 73],"float16"), ) -paddle.Tensor.__add__(Tensor([56, 8, 72, 35],"float16"), Tensor([56, 1, 1, 35],"float16"), ) paddle.Tensor.__add__(Tensor([56, 80, 1024],"float32"), Tensor([56, 80, 1024],"float32"), ) paddle.Tensor.__add__(Tensor([56, 80],"float32"), Tensor([56, 80],"float32"), ) paddle.Tensor.__add__(Tensor([56, 81, 1024],"float32"), Tensor([56, 81, 1024],"float32"), ) @@ -55113,7 +55056,6 @@ paddle.Tensor.__add__(Tensor([623],"float32"), Tensor([623],"float32"), ) paddle.Tensor.__add__(Tensor([624, 10],"float32"), Tensor([624, 10],"float32"), ) paddle.Tensor.__add__(Tensor([624, 11],"float32"), Tensor([624, 11],"float32"), ) paddle.Tensor.__add__(Tensor([624, 12],"float32"), Tensor([624, 12],"float32"), ) -paddle.Tensor.__add__(Tensor([624, 16, 7, 7],"float16"), Tensor([624, 1, 1, 7],"float16"), ) paddle.Tensor.__add__(Tensor([624, 16, 8, 7],"float16"), Tensor([624, 1, 1, 7],"float16"), ) paddle.Tensor.__add__(Tensor([624, 17],"float32"), Tensor([624, 17],"float32"), ) paddle.Tensor.__add__(Tensor([624, 1],"float32"), 1e-10, ) @@ -56411,7 +56353,6 @@ paddle.Tensor.__add__(Tensor([64, 8, 54, 54],"float16"), Tensor([54, 54],"float1 paddle.Tensor.__add__(Tensor([64, 8, 55, 63],"float16"), Tensor([64, 1, 1, 63],"float16"), ) paddle.Tensor.__add__(Tensor([64, 8, 56, 40],"float16"), Tensor([64, 1, 1, 40],"float16"), ) paddle.Tensor.__add__(Tensor([64, 8, 57, 33],"float16"), Tensor([64, 1, 1, 33],"float16"), ) -paddle.Tensor.__add__(Tensor([64, 8, 57, 8],"float16"), Tensor([64, 1, 1, 8],"float16"), ) paddle.Tensor.__add__(Tensor([64, 8, 58, 45],"float16"), Tensor([64, 1, 1, 45],"float16"), ) paddle.Tensor.__add__(Tensor([64, 8, 58, 46],"float16"), Tensor([64, 1, 1, 46],"float16"), ) paddle.Tensor.__add__(Tensor([64, 8, 59, 42],"float16"), Tensor([64, 1, 1, 42],"float16"), ) @@ -58814,9 +58755,7 @@ paddle.Tensor.__add__(Tensor([72, 8, 40, 40],"float16"), Tensor([72, 1, 1, 40]," paddle.Tensor.__add__(Tensor([72, 8, 45, 54],"float16"), Tensor([72, 1, 1, 54],"float16"), ) paddle.Tensor.__add__(Tensor([72, 8, 51, 51],"float16"), Tensor([72, 1, 1, 51],"float16"), ) paddle.Tensor.__add__(Tensor([72, 8, 51, 52],"float16"), Tensor([72, 1, 1, 52],"float16"), ) -paddle.Tensor.__add__(Tensor([72, 8, 53, 43],"float16"), Tensor([72, 1, 1, 43],"float16"), ) paddle.Tensor.__add__(Tensor([72, 8, 53, 48],"float16"), Tensor([72, 1, 1, 48],"float16"), ) -paddle.Tensor.__add__(Tensor([72, 8, 54, 55],"float16"), Tensor([72, 1, 1, 55],"float16"), ) paddle.Tensor.__add__(Tensor([72, 8, 55, 15],"float16"), Tensor([72, 1, 1, 15],"float16"), ) paddle.Tensor.__add__(Tensor([72, 8, 55, 50],"float16"), Tensor([72, 1, 1, 50],"float16"), ) paddle.Tensor.__add__(Tensor([72, 8, 56, 48],"float16"), Tensor([72, 1, 1, 48],"float16"), ) @@ -60672,7 +60611,6 @@ paddle.Tensor.__add__(Tensor([7997, 80],"float32"), Tensor([7997, 80],"float32") paddle.Tensor.__add__(Tensor([7998, 80],"float32"), Tensor([7998, 80],"float32"), ) paddle.Tensor.__add__(Tensor([799],"float32"), Tensor([799],"float32"), ) paddle.Tensor.__add__(Tensor([79],"float32"), Tensor([79],"float32"), ) -paddle.Tensor.__add__(Tensor([7],"complex64"), Tensor([],"float32"), ) paddle.Tensor.__add__(Tensor([7],"float32"), 0.5, ) paddle.Tensor.__add__(Tensor([7],"float32"), 1.7170948287741004, ) paddle.Tensor.__add__(Tensor([7],"float32"), Tensor([7],"float32"), ) @@ -64064,7 +64002,6 @@ paddle.Tensor.__add__(Tensor([80, 8, 22, 22],"float16"), Tensor([80, 1, 1, 22]," paddle.Tensor.__add__(Tensor([80, 8, 25, 25],"float16"), Tensor([80, 1, 1, 25],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 28, 28],"float16"), Tensor([80, 1, 1, 28],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 30, 30],"float16"), Tensor([80, 1, 1, 30],"float16"), ) -paddle.Tensor.__add__(Tensor([80, 8, 31, 31],"float16"), Tensor([80, 1, 1, 31],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 32, 32],"float16"), Tensor([80, 1, 1, 32],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 34, 34],"float16"), Tensor([80, 1, 1, 34],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 35, 35],"float16"), Tensor([80, 1, 1, 35],"float16"), ) @@ -64072,12 +64009,9 @@ paddle.Tensor.__add__(Tensor([80, 8, 37, 37],"float16"), Tensor([37, 37],"float1 paddle.Tensor.__add__(Tensor([80, 8, 37, 37],"float16"), Tensor([80, 1, 1, 37],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 39, 50],"float16"), Tensor([80, 1, 1, 50],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 40, 20],"float16"), Tensor([80, 1, 1, 20],"float16"), ) -paddle.Tensor.__add__(Tensor([80, 8, 42, 49],"float16"), Tensor([80, 1, 1, 49],"float16"), ) -paddle.Tensor.__add__(Tensor([80, 8, 44, 28],"float16"), Tensor([80, 1, 1, 28],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 44, 44],"float16"), Tensor([80, 1, 1, 44],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 46, 51],"float16"), Tensor([80, 1, 1, 51],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 47, 22],"float16"), Tensor([80, 1, 1, 22],"float16"), ) -paddle.Tensor.__add__(Tensor([80, 8, 47, 30],"float16"), Tensor([80, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 47, 42],"float16"), Tensor([80, 1, 1, 42],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 48, 21],"float16"), Tensor([80, 1, 1, 21],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 48, 36],"float16"), Tensor([80, 1, 1, 36],"float16"), ) @@ -64087,8 +64021,6 @@ paddle.Tensor.__add__(Tensor([80, 8, 49, 44],"float16"), Tensor([80, 1, 1, 44]," paddle.Tensor.__add__(Tensor([80, 8, 50, 46],"float16"), Tensor([80, 1, 1, 46],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 50, 47],"float16"), Tensor([80, 1, 1, 47],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 50, 48],"float16"), Tensor([80, 1, 1, 48],"float16"), ) -paddle.Tensor.__add__(Tensor([80, 8, 50, 49],"float16"), Tensor([80, 1, 1, 49],"float16"), ) -paddle.Tensor.__add__(Tensor([80, 8, 51, 38],"float16"), Tensor([80, 1, 1, 38],"float16"), ) paddle.Tensor.__add__(Tensor([80, 8, 51, 50],"float16"), Tensor([80, 1, 1, 50],"float16"), ) paddle.Tensor.__add__(Tensor([80, 80, 1, 1],"float32"), Tensor([80, 80, 1, 1],"float32"), ) paddle.Tensor.__add__(Tensor([80, 80, 3, 3],"float32"), Tensor([80, 80, 3, 3],"float32"), ) @@ -65088,7 +65020,6 @@ paddle.Tensor.__add__(Tensor([8478, 80],"float32"), Tensor([8478, 80],"float32") paddle.Tensor.__add__(Tensor([848, 11],"float32"), Tensor([848, 11],"float32"), ) paddle.Tensor.__add__(Tensor([848, 12],"float32"), Tensor([848, 12],"float32"), ) paddle.Tensor.__add__(Tensor([848, 16, 6, 6],"float16"), Tensor([6, 6],"float16"), ) -paddle.Tensor.__add__(Tensor([848, 16, 6, 6],"float16"), Tensor([848, 1, 1, 6],"float16"), ) paddle.Tensor.__add__(Tensor([848, 19],"float32"), Tensor([848, 19],"float32"), ) paddle.Tensor.__add__(Tensor([848, 1],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([848, 1],"float32"), Tensor([848, 1],"float32"), ) @@ -65726,7 +65657,6 @@ paddle.Tensor.__add__(Tensor([88, 16, 15, 15],"float16"), Tensor([88, 1, 1, 15], paddle.Tensor.__add__(Tensor([88, 16, 20, 20],"float16"), Tensor([88, 1, 1, 20],"float16"), ) paddle.Tensor.__add__(Tensor([88, 16, 36, 36],"float16"), Tensor([88, 1, 1, 36],"float16"), ) paddle.Tensor.__add__(Tensor([88, 16, 512],"float32"), Tensor([88, 16, 512],"float32"), ) -paddle.Tensor.__add__(Tensor([88, 16, 57, 8],"float16"), Tensor([88, 1, 1, 8],"float16"), ) paddle.Tensor.__add__(Tensor([88, 16, 8, 8],"float16"), Tensor([88, 1, 1, 8],"float16"), ) paddle.Tensor.__add__(Tensor([88, 17, 512],"float32"), Tensor([88, 17, 512],"float32"), ) paddle.Tensor.__add__(Tensor([88, 192, 3, 3],"float32"), Tensor([88, 192, 3, 3],"float32"), ) @@ -65799,7 +65729,6 @@ paddle.Tensor.__add__(Tensor([88, 8, 17, 17],"float16"), Tensor([88, 1, 1, 17]," paddle.Tensor.__add__(Tensor([88, 8, 27, 27],"float16"), Tensor([88, 1, 1, 27],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 33, 44],"float16"), Tensor([88, 1, 1, 44],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 35, 35],"float16"), Tensor([88, 1, 1, 35],"float16"), ) -paddle.Tensor.__add__(Tensor([88, 8, 36, 36],"float16"), Tensor([88, 1, 1, 36],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 37, 43],"float16"), Tensor([88, 1, 1, 43],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 37, 44],"float16"), Tensor([88, 1, 1, 44],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 38, 43],"float16"), Tensor([88, 1, 1, 43],"float16"), ) @@ -65807,12 +65736,10 @@ paddle.Tensor.__add__(Tensor([88, 8, 38, 44],"float16"), Tensor([88, 1, 1, 44]," paddle.Tensor.__add__(Tensor([88, 8, 39, 39],"float16"), Tensor([39, 39],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 42, 42],"float16"), Tensor([88, 1, 1, 42],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 42, 44],"float16"), Tensor([88, 1, 1, 44],"float16"), ) -paddle.Tensor.__add__(Tensor([88, 8, 43, 37],"float16"), Tensor([88, 1, 1, 37],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 43, 43],"float16"), Tensor([43, 43],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 44, 17],"float16"), Tensor([88, 1, 1, 17],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 44, 37],"float16"), Tensor([88, 1, 1, 37],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 44, 41],"float16"), Tensor([88, 1, 1, 41],"float16"), ) -paddle.Tensor.__add__(Tensor([88, 8, 44, 44],"float16"), Tensor([44, 44],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 44, 44],"float16"), Tensor([88, 1, 1, 44],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 45, 35],"float16"), Tensor([88, 1, 1, 35],"float16"), ) paddle.Tensor.__add__(Tensor([88, 8, 45, 46],"float16"), Tensor([88, 1, 1, 46],"float16"), ) @@ -67451,7 +67378,6 @@ paddle.Tensor.__add__(Tensor([96, 6804],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([96, 72, 1, 1],"float32"), Tensor([96, 72, 1, 1],"float32"), ) paddle.Tensor.__add__(Tensor([96, 7581],"float32"), 1e-10, ) paddle.Tensor.__add__(Tensor([96, 8, 11, 11],"float16"), Tensor([96, 1, 1, 11],"float16"), ) -paddle.Tensor.__add__(Tensor([96, 8, 28, 28],"float16"), Tensor([96, 1, 1, 28],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 29, 29],"float16"), Tensor([96, 1, 1, 29],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 30, 41],"float16"), Tensor([96, 1, 1, 41],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 31, 31],"float16"), Tensor([96, 1, 1, 31],"float16"), ) @@ -67460,7 +67386,6 @@ paddle.Tensor.__add__(Tensor([96, 8, 34, 41],"float16"), Tensor([96, 1, 1, 41]," paddle.Tensor.__add__(Tensor([96, 8, 38, 40],"float16"), Tensor([96, 1, 1, 40],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 39, 30],"float16"), Tensor([96, 1, 1, 30],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 39, 40],"float16"), Tensor([96, 1, 1, 40],"float16"), ) -paddle.Tensor.__add__(Tensor([96, 8, 40, 29],"float16"), Tensor([96, 1, 1, 29],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 40, 32],"float16"), Tensor([96, 1, 1, 32],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 41, 32],"float16"), Tensor([96, 1, 1, 32],"float16"), ) paddle.Tensor.__add__(Tensor([96, 8, 41, 38],"float16"), Tensor([96, 1, 1, 38],"float16"), ) @@ -313200,7 +313125,6 @@ paddle.Tensor.__mul__(Tensor([2, 79, 3549],"float32"), Tensor([2, 79, 3549],"flo paddle.Tensor.__mul__(Tensor([2, 79, 4116],"float32"), Tensor([2, 79, 4116],"float32"), ) paddle.Tensor.__mul__(Tensor([2, 79, 4725],"float32"), Tensor([2, 79, 4725],"float32"), ) paddle.Tensor.__mul__(Tensor([2, 79, 5376],"float32"), Tensor([2, 79, 5376],"float32"), ) -paddle.Tensor.__mul__(Tensor([2, 79, 768],"float16"), Tensor([768],"float16"), ) paddle.Tensor.__mul__(Tensor([2, 79, 8, 96],"float16"), Tensor([2, 79, 1, 96],"float16"), ) paddle.Tensor.__mul__(Tensor([2, 79, 9261],"float32"), Tensor([2, 79, 9261],"float32"), ) paddle.Tensor.__mul__(Tensor([2, 79],"float32"), Tensor([2, 79],"float32"), ) @@ -344066,7 +343990,6 @@ paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 13],"float64"), ) paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 14],"float64"), ) paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 15],"float64"), ) paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 16],"float64"), ) -paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 1],"float64"), ) paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 2],"float64"), ) paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 3],"float64"), ) paddle.Tensor.__mul__(Tensor([3, 1],"float64"), Tensor([1, 4],"float64"), ) @@ -364644,7 +364567,6 @@ paddle.Tensor.__mul__(Tensor([4, 182, 32],"float16"), 1.0, ) paddle.Tensor.__mul__(Tensor([4, 182, 32],"float16"), 1.414213562373095, ) paddle.Tensor.__mul__(Tensor([4, 182, 64],"float16"), 1.0, ) paddle.Tensor.__mul__(Tensor([4, 182, 64],"float16"), 1.414213562373095, ) -paddle.Tensor.__mul__(Tensor([4, 182, 64],"float16"), Tensor([64],"float16"), ) paddle.Tensor.__mul__(Tensor([4, 18496, 4],"float32"), 8, ) paddle.Tensor.__mul__(Tensor([4, 19, 1024],"float32"), Tensor([4, 19, 1024],"float32"), ) paddle.Tensor.__mul__(Tensor([4, 19, 11109],"float32"), Tensor([4, 19, 11109],"float32"), ) @@ -400491,7 +400413,6 @@ paddle.Tensor.__mul__(Tensor([8, 38, 38],"float16"), 0.08838834764831843, ) paddle.Tensor.__mul__(Tensor([8, 38, 4725],"float32"), Tensor([8, 38, 4725],"float32"), ) paddle.Tensor.__mul__(Tensor([8, 384, 10, 10],"float32"), Tensor([8, 384, 10, 10],"float32"), ) paddle.Tensor.__mul__(Tensor([8, 384, 12, 12],"float16"), Tensor([8, 384, 1, 1],"float16"), ) -paddle.Tensor.__mul__(Tensor([8, 384, 14, 14],"float16"), Tensor([8, 384, 1, 1],"float16"), ) paddle.Tensor.__mul__(Tensor([8, 384, 15, 15],"float32"), Tensor([8, 384, 15, 15],"float32"), ) paddle.Tensor.__mul__(Tensor([8, 384, 16, 16],"float16"), Tensor([8, 384, 1, 1],"float16"), ) paddle.Tensor.__mul__(Tensor([8, 384, 18, 18],"float16"), Tensor([8, 384, 1, 1],"float16"), ) @@ -544192,3 +544113,28 @@ paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.038461538461538436 paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03862660944206009, ) paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03879310344827591, ) paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.038961038961038974, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03913043478260869, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.0393013100436681, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03947368421052633, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03964757709251099, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03982300884955747, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.040000000000000036, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.0401785714285714, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04035874439461884, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04054054054054057, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.040723981900452455, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.040909090909090895, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04109589041095896, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.041284403669724745, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04147465437788023, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04166666666666663, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.041860465116279055, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04205607476635509, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04225352112676062, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04245283018867929, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.042654028436018954, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.042857142857142816, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.0430622009569378, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.043269230769230727, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04347826086956519, ) +paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.043689320388349495, ) diff --git a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_2.txt b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_2.txt index 2a9c7a1d..7100edb8 100644 --- a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_2.txt +++ b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_2.txt @@ -1,28 +1,3 @@ -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03913043478260869, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.0393013100436681, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03947368421052633, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03964757709251099, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.03982300884955747, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.040000000000000036, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.0401785714285714, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04035874439461884, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04054054054054057, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.040723981900452455, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.040909090909090895, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04109589041095896, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.041284403669724745, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04147465437788023, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04166666666666663, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.041860465116279055, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04205607476635509, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04225352112676062, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04245283018867929, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.042654028436018954, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.042857142857142816, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.0430622009569378, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.043269230769230727, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04347826086956519, ) -paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.043689320388349495, ) paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.04390243902439028, ) paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.044117647058823484, ) paddle.Tensor.__rmul__(Tensor([1024, 768, 1, 1],"float32"), 0.044334975369458074, ) @@ -324131,7 +324106,6 @@ paddle.Tensor.__sub__(Tensor([1, 397467],"float32"), Tensor([1, 397467],"float32 paddle.Tensor.__sub__(Tensor([1, 398487, 2],"float32"), Tensor([1, 398487, 2],"float32"), ) paddle.Tensor.__sub__(Tensor([1, 398487],"float32"), Tensor([1, 398487],"float32"), ) paddle.Tensor.__sub__(Tensor([1, 3],"float32"), 1, ) -paddle.Tensor.__sub__(Tensor([1, 3],"float32"), Tensor([1, 1],"float32"), ) paddle.Tensor.__sub__(Tensor([1, 3],"float32"), Tensor([1, 3],"float32"), ) paddle.Tensor.__sub__(Tensor([1, 3],"float64"), Tensor([1, 3],"float64"), ) paddle.Tensor.__sub__(Tensor([1, 3],"int64"), 1, ) @@ -421212,7 +421186,6 @@ paddle.Tensor.__truediv__(Tensor([1088, 3060],"float32"), Tensor([1088, 3060],"f paddle.Tensor.__truediv__(Tensor([1088, 34],"float32"), Tensor([1088, 34],"float32"), ) paddle.Tensor.__truediv__(Tensor([1088, 3],"float32"), Tensor([1088, 3],"float32"), ) paddle.Tensor.__truediv__(Tensor([1088, 4],"float32"), Tensor([1088, 4],"float32"), ) -paddle.Tensor.__truediv__(Tensor([1088, 512],"float16"), Tensor([1088, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([1088, 6],"float32"), Tensor([1088, 6],"float32"), ) paddle.Tensor.__truediv__(Tensor([1088, 9261],"float32"), Tensor([1088, 9261],"float32"), ) paddle.Tensor.__truediv__(Tensor([1088, 9],"float32"), Tensor([1088, 9],"float32"), ) @@ -421743,7 +421716,6 @@ paddle.Tensor.__truediv__(Tensor([1123, 11],"float32"), Tensor([1123, 11],"float paddle.Tensor.__truediv__(Tensor([1123, 1],"float32"), Tensor([1123, 1],"float32"), ) paddle.Tensor.__truediv__(Tensor([1123, 2],"float32"), Tensor([1123, 2],"float32"), ) paddle.Tensor.__truediv__(Tensor([1123, 4],"float32"), Tensor([1123, 4],"float32"), ) -paddle.Tensor.__truediv__(Tensor([1123, 512],"float16"), Tensor([1123, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([1123, 8],"float32"), Tensor([1123, 8],"float32"), ) paddle.Tensor.__truediv__(Tensor([1124, 15],"float32"), Tensor([1124, 15],"float32"), ) paddle.Tensor.__truediv__(Tensor([1124, 19],"float32"), Tensor([1124, 19],"float32"), ) @@ -426461,7 +426433,6 @@ paddle.Tensor.__truediv__(Tensor([1536, 2],"float32"), Tensor([1536, 2],"float32 paddle.Tensor.__truediv__(Tensor([1536, 3060],"float32"), Tensor([1536, 3060],"float32"), ) paddle.Tensor.__truediv__(Tensor([1536, 3],"float32"), Tensor([1536, 3],"float32"), ) paddle.Tensor.__truediv__(Tensor([1536, 4],"float32"), Tensor([1536, 4],"float32"), ) -paddle.Tensor.__truediv__(Tensor([1536, 512],"float16"), Tensor([1536, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([1536, 6],"float32"), Tensor([1536, 6],"float32"), ) paddle.Tensor.__truediv__(Tensor([1536, 7],"float32"), Tensor([1536, 7],"float32"), ) paddle.Tensor.__truediv__(Tensor([1536, 9],"float32"), Tensor([1536, 9],"float32"), ) @@ -426525,7 +426496,6 @@ paddle.Tensor.__truediv__(Tensor([1541, 13],"float32"), Tensor([1541, 13],"float paddle.Tensor.__truediv__(Tensor([1541, 1],"float32"), Tensor([1541, 1],"float32"), ) paddle.Tensor.__truediv__(Tensor([1541, 2],"float32"), Tensor([1541, 2],"float32"), ) paddle.Tensor.__truediv__(Tensor([1541, 45],"float32"), Tensor([1541, 45],"float32"), ) -paddle.Tensor.__truediv__(Tensor([1541, 512],"float16"), Tensor([1541, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([1541, 56],"float32"), Tensor([1541, 56],"float32"), ) paddle.Tensor.__truediv__(Tensor([1541, 5],"float32"), Tensor([1541, 5],"float32"), ) paddle.Tensor.__truediv__(Tensor([1541, 6],"float32"), Tensor([1541, 6],"float32"), ) @@ -434933,7 +434903,6 @@ paddle.Tensor.__truediv__(Tensor([2081, 1],"float32"), Tensor([2081, 1],"float32 paddle.Tensor.__truediv__(Tensor([2081, 2],"float32"), Tensor([2081, 2],"float32"), ) paddle.Tensor.__truediv__(Tensor([2081, 3],"float32"), Tensor([2081, 3],"float32"), ) paddle.Tensor.__truediv__(Tensor([2081, 4],"float32"), Tensor([2081, 4],"float32"), ) -paddle.Tensor.__truediv__(Tensor([2081, 512],"float16"), Tensor([2081, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([2081, 5],"float32"), Tensor([2081, 5],"float32"), ) paddle.Tensor.__truediv__(Tensor([2081, 8],"float32"), Tensor([2081, 8],"float32"), ) paddle.Tensor.__truediv__(Tensor([208197],"float32"), Tensor([208197],"float32"), ) @@ -458384,7 +458353,6 @@ paddle.Tensor.__truediv__(Tensor([87600],"float32"), Tensor([87600],"float32"), paddle.Tensor.__truediv__(Tensor([876184],"float32"), Tensor([876184],"float32"), ) paddle.Tensor.__truediv__(Tensor([876793],"float32"), Tensor([876793],"float32"), ) paddle.Tensor.__truediv__(Tensor([877, 10],"float32"), Tensor([877, 10],"float32"), ) -paddle.Tensor.__truediv__(Tensor([877, 128],"float16"), Tensor([877, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([877, 12],"float32"), Tensor([877, 12],"float32"), ) paddle.Tensor.__truediv__(Tensor([877, 13],"float32"), Tensor([877, 13],"float32"), ) paddle.Tensor.__truediv__(Tensor([877, 16],"float32"), Tensor([877, 16],"float32"), ) @@ -459962,7 +459930,6 @@ paddle.Tensor.__truediv__(Tensor([966, 2],"float32"), 8, ) paddle.Tensor.__truediv__(Tensor([966, 2],"float32"), Tensor([966, 2],"float32"), ) paddle.Tensor.__truediv__(Tensor([966, 3],"float32"), Tensor([966, 3],"float32"), ) paddle.Tensor.__truediv__(Tensor([966, 4],"float32"), 8, ) -paddle.Tensor.__truediv__(Tensor([966, 512],"float16"), Tensor([966, 1],"float16"), ) paddle.Tensor.__truediv__(Tensor([966, 5],"float32"), Tensor([966, 5],"float32"), ) paddle.Tensor.__truediv__(Tensor([966, 7],"float32"), Tensor([966, 7],"float32"), ) paddle.Tensor.__truediv__(Tensor([966455],"float32"), Tensor([966455],"float32"), ) @@ -544171,24 +544138,3 @@ paddle.Tensor.cast(Tensor([2204, 5],"int64"), "bool", ) paddle.Tensor.cast(Tensor([2204, 80],"bool"), "float32", ) paddle.Tensor.cast(Tensor([2204, 80],"float64"), Dtype(float32), ) paddle.Tensor.cast(Tensor([220406, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([220408, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([220416, 80],"float64"), "float32", ) -paddle.Tensor.cast(Tensor([220431, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([22044, 80],"bool"), "float32", ) -paddle.Tensor.cast(Tensor([22044, 80],"float64"), Dtype(float32), ) -paddle.Tensor.cast(Tensor([220442, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([220470, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([220474, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([220477, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([22049, 80],"bool"), "float32", ) -paddle.Tensor.cast(Tensor([22049, 80],"float64"), Dtype(float32), ) -paddle.Tensor.cast(Tensor([220496, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([220497, 1],"int64"), "int32", ) -paddle.Tensor.cast(Tensor([2204],"float32"), "int64", ) -paddle.Tensor.cast(Tensor([2204],"int64"), "float32", ) -paddle.Tensor.cast(Tensor([2205, 11],"bool"), "float32", ) -paddle.Tensor.cast(Tensor([2205, 11],"int64"), "bool", ) -paddle.Tensor.cast(Tensor([2205, 12],"bool"), "float32", ) -paddle.Tensor.cast(Tensor([2205, 12],"int64"), "bool", ) -paddle.Tensor.cast(Tensor([2205, 15],"bool"), "float32", ) -paddle.Tensor.cast(Tensor([2205, 15],"int64"), "bool", ) diff --git a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_3.txt b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_3.txt index e4dfcb55..f9088f4f 100644 --- a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_3.txt +++ b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_3.txt @@ -1,3 +1,24 @@ +paddle.Tensor.cast(Tensor([220408, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([220416, 80],"float64"), "float32", ) +paddle.Tensor.cast(Tensor([220431, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([22044, 80],"bool"), "float32", ) +paddle.Tensor.cast(Tensor([22044, 80],"float64"), Dtype(float32), ) +paddle.Tensor.cast(Tensor([220442, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([220470, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([220474, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([220477, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([22049, 80],"bool"), "float32", ) +paddle.Tensor.cast(Tensor([22049, 80],"float64"), Dtype(float32), ) +paddle.Tensor.cast(Tensor([220496, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([220497, 1],"int64"), "int32", ) +paddle.Tensor.cast(Tensor([2204],"float32"), "int64", ) +paddle.Tensor.cast(Tensor([2204],"int64"), "float32", ) +paddle.Tensor.cast(Tensor([2205, 11],"bool"), "float32", ) +paddle.Tensor.cast(Tensor([2205, 11],"int64"), "bool", ) +paddle.Tensor.cast(Tensor([2205, 12],"bool"), "float32", ) +paddle.Tensor.cast(Tensor([2205, 12],"int64"), "bool", ) +paddle.Tensor.cast(Tensor([2205, 15],"bool"), "float32", ) +paddle.Tensor.cast(Tensor([2205, 15],"int64"), "bool", ) paddle.Tensor.cast(Tensor([2205, 18],"bool"), "float32", ) paddle.Tensor.cast(Tensor([2205, 18],"int64"), "bool", ) paddle.Tensor.cast(Tensor([2205, 24],"bool"), "float32", ) @@ -117053,7 +117074,6 @@ paddle.Tensor.divide(Tensor([4, 128, 32, 32],"float16"), Tensor([],"float16"), ) paddle.Tensor.divide(Tensor([4, 16384, 64],"float16"), Tensor([],"float16"), ) paddle.Tensor.divide(Tensor([4, 192, 16, 16],"float16"), Tensor([],"float16"), ) paddle.Tensor.divide(Tensor([4, 4096, 160],"float16"), Tensor([],"float16"), ) -paddle.Tensor.divide(Tensor([4, 65536, 32],"float16"), Tensor([],"float16"), ) paddle.Tensor.divide(Tensor([42],"float32"), Tensor([42],"float32"), ) paddle.Tensor.divide(Tensor([512, 100, 128],"float16"), Tensor([],"float16"), ) paddle.Tensor.divide(Tensor([512, 200, 64],"float16"), Tensor([],"float16"), ) @@ -140986,7 +141006,6 @@ paddle.Tensor.log(Tensor([4],"float32"), ) paddle.Tensor.log(Tensor([4],"float64"), ) paddle.Tensor.log(Tensor([600, 4],"float16"), ) paddle.Tensor.log(Tensor([8, 10],"float64"), ) -paddle.Tensor.log(Tensor([],"float32"), ) paddle.Tensor.log(Tensor([],"float64"), ) paddle.Tensor.logical_and(Tensor([1038],"bool"), Tensor([1038],"bool"), ) paddle.Tensor.logical_and(Tensor([1697],"bool"), Tensor([1697],"bool"), ) @@ -141054,7 +141073,6 @@ paddle.Tensor.logsumexp(Tensor([2, 3, 4, 5],"float32"), None, False, ) paddle.Tensor.logsumexp(Tensor([2, 3, 4, 5],"float32"), None, True, ) paddle.Tensor.logsumexp(Tensor([3, 5],"float32"), axis=None, ) paddle.Tensor.logsumexp(Tensor([3, 5],"float32"), keepdim=True, ) -paddle.Tensor.logsumexp(Tensor([5],"float32"), axis=0, ) paddle.Tensor.logsumexp(Tensor([],"float32"), axis=-1, ) paddle.Tensor.logsumexp(Tensor([],"float32"), axis=0, ) paddle.Tensor.logsumexp(Tensor([],"float32"), axis=None, ) @@ -151029,12 +151047,10 @@ paddle.Tensor.mean(Tensor([8, 192, 28, 28],"float16"), tuple(2,3,), keepdim=True paddle.Tensor.mean(Tensor([8, 192, 30, 30],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 192, 32, 32],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 192, 34, 34],"float16"), tuple(2,3,), keepdim=True, ) -paddle.Tensor.mean(Tensor([8, 192, 40, 40],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 192, 42, 42],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 1],"float32"), ) paddle.Tensor.mean(Tensor([8, 2],"float16"), ) paddle.Tensor.mean(Tensor([8, 2],"float32"), ) -paddle.Tensor.mean(Tensor([8, 384, 10, 10],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 384, 12, 12],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 384, 13, 13],"float16"), tuple(2,3,), keepdim=True, ) paddle.Tensor.mean(Tensor([8, 384, 14, 14],"float16"), tuple(2,3,), keepdim=True, ) @@ -429358,7 +429374,6 @@ paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,10,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,16,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,32,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,33,], ) -paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,34,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,5,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,6,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,1,1,8,], ) @@ -429368,7 +429383,6 @@ paddle.broadcast_to(Tensor([1],"float64"), list[1,4,4,2,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,4,4,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,4,], ) paddle.broadcast_to(Tensor([1],"float64"), list[1,], ) -paddle.broadcast_to(Tensor([1],"float64"), list[2,1,1,6,], ) paddle.broadcast_to(Tensor([1],"float64"), list[2,1,], ) paddle.broadcast_to(Tensor([1],"float64"), list[4,], ) paddle.broadcast_to(Tensor([1],"float64"), shape=tuple(1,), ) @@ -544124,71 +544138,3 @@ paddle.concat(tuple(Tensor([22067, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, paddle.concat(tuple(Tensor([22067, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) paddle.concat(tuple(Tensor([22067],"int32"),Tensor([1],"int32"),), axis=0, ) paddle.concat(tuple(Tensor([22068, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22068, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22068],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22069, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22069, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22069],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([2206],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([2207, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([2207, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22070, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22070, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22070],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22071, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22071, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22071],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22072, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22072, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22072],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22073, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22073, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22073],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22074, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22074, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22074],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22075, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22075, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22075],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22076, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22076, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22076],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22077, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22077, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22077],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22078, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22078, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22078],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22079, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22079, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22079],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([2207],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([2208, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([2208, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22080, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22080, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22080],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22081, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22081, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22081],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22082, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22082, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22082],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22083, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22083, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22083],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22084, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22084, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22084],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22085, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22085, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22085],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22086, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22086, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22086],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22087, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22087, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22087],"int32"),Tensor([1],"int32"),), axis=0, ) -paddle.concat(tuple(Tensor([22088, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) -paddle.concat(tuple(Tensor([22088, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) -paddle.concat(tuple(Tensor([22088],"int32"),Tensor([1],"int32"),), axis=0, ) diff --git a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_4.txt b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_4.txt index 7aa5e5d0..0b065e23 100644 --- a/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_4.txt +++ b/tester/api_config/monitor_config/accuracy/GPU/monitoring_configs_4.txt @@ -1,3 +1,71 @@ +paddle.concat(tuple(Tensor([22068, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22068],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22069, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22069, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22069],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([2206],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([2207, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([2207, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22070, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22070, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22070],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22071, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22071, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22071],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22072, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22072, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22072],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22073, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22073, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22073],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22074, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22074, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22074],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22075, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22075, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22075],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22076, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22076, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22076],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22077, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22077, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22077],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22078, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22078, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22078],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22079, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22079, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22079],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([2207],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([2208, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([2208, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22080, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22080, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22080],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22081, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22081, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22081],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22082, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22082, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22082],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22083, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22083, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22083],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22084, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22084, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22084],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22085, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22085, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22085],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22086, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22086, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22086],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22087, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22087, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22087],"int32"),Tensor([1],"int32"),), axis=0, ) +paddle.concat(tuple(Tensor([22088, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) +paddle.concat(tuple(Tensor([22088, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) +paddle.concat(tuple(Tensor([22088],"int32"),Tensor([1],"int32"),), axis=0, ) paddle.concat(tuple(Tensor([22089, 1],"int64"),Tensor([1, 1],"int64"),), axis=0, ) paddle.concat(tuple(Tensor([22089, 768],"float32"),Tensor([1, 768],"float32"),), axis=0, ) paddle.concat(tuple(Tensor([22089],"int32"),Tensor([1],"int32"),), axis=0, ) @@ -254260,7 +254328,6 @@ paddle.linalg.cond(Tensor([0, 9, 9],"float32"), 1, ) paddle.linalg.cond(Tensor([0, 9, 9],"float32"), 2, ) paddle.linalg.cond(Tensor([0, 9, 9],"float32"), None, ) paddle.linalg.cond(Tensor([0, 9, 9],"float32"), math.inf, ) -paddle.linalg.cond(Tensor([5, 5],"float32"), -math.inf, ) paddle.linalg.eigh(Tensor([2, 2],"complex64"), "L", ) paddle.linalg.eigh(Tensor([32, 32],"float32"), "L", ) paddle.linalg.eigh(Tensor([4, 4],"float32"), "L", ) @@ -254804,7 +254871,6 @@ paddle.log(Tensor([1],"float64"), ) paddle.log(Tensor([2, 1, 1],"float32"), ) paddle.log(Tensor([2, 1],"float64"), ) paddle.log(Tensor([2, 2],"float64"), ) -paddle.log(Tensor([2, 3],"float32"), ) paddle.log(Tensor([2, 3],"float64"), ) paddle.log(Tensor([2, 5, 2],"float64"), ) paddle.log(Tensor([2, 99],"float16"), ) @@ -329504,8 +329570,6 @@ paddle.multiply(Tensor([124],"float32"), Tensor([124],"float32"), ) paddle.multiply(Tensor([128, 112, 14, 14],"float16"), Tensor([128, 1, 1, 1],"float16"), ) paddle.multiply(Tensor([128, 1152, 7, 7],"float16"), Tensor([128, 1152, 1, 1],"float16"), ) paddle.multiply(Tensor([128, 1152, 7, 7],"float32"), Tensor([128, 1152, 1, 1],"float32"), ) -paddle.multiply(Tensor([128, 24, 56, 56],"float16"), Tensor([128, 1, 1, 1],"float16"), ) -paddle.multiply(Tensor([128, 40, 28, 28],"float16"), Tensor([128, 1, 1, 1],"float16"), ) paddle.multiply(Tensor([128, 64],"float32"), Tensor([128, 64],"float32"), ) paddle.multiply(Tensor([128, 672, 7, 7],"float16"), Tensor([128, 672, 1, 1],"float16"), ) paddle.multiply(Tensor([128, 672, 7, 7],"float32"), Tensor([128, 672, 1, 1],"float32"), ) @@ -331603,7 +331667,6 @@ paddle.nansum(Tensor([2, 3],"float32"), axis=list[-1,], keepdim=False, name=None paddle.nansum(Tensor([2, 3],"float32"), axis=list[0,], keepdim=True, name=None, ) paddle.nansum(Tensor([2, 3],"float32"), axis=list[1,], keepdim=False, name=None, ) paddle.nansum(Tensor([2, 4],"float32"), ) -paddle.nansum(Tensor([5],"float32"), axis=list[0,], keepdim=False, name=None, ) paddle.nansum(Tensor([],"float32"), axis=-1, ) paddle.nansum(Tensor([],"float32"), axis=0, ) paddle.nansum(Tensor([],"float32"), axis=None, ) @@ -331774,11 +331837,9 @@ paddle.nn.functional.bilinear(Tensor([3, 1],"float64"), Tensor([3, 2],"float64") paddle.nn.functional.bilinear(Tensor([5, 5],"float32"), Tensor([5, 4],"float32"), Tensor([1000, 5, 4],"float32"), Tensor([1, 1000],"float32"), None, ) paddle.nn.functional.binary_cross_entropy(Tensor([1, 1, 2],"float64"), label=Tensor([1, 1, 2],"float64"), weight=None, reduction="mean", name=None, ) paddle.nn.functional.binary_cross_entropy(Tensor([2, 2100, 1],"float32"), Tensor([2, 2100, 1],"float32"), weight=Tensor([2, 2100, 1],"float32"), reduction="sum", ) -paddle.nn.functional.binary_cross_entropy(Tensor([2, 4725, 10],"float32"), Tensor([2, 4725, 10],"float32"), weight=Tensor([2, 4725, 10],"float32"), reduction="sum", ) paddle.nn.functional.binary_cross_entropy(Tensor([8, 2100, 4],"float32"), Tensor([8, 2100, 4],"float32"), weight=Tensor([8, 2100, 4],"float32"), reduction="sum", ) paddle.nn.functional.binary_cross_entropy(Tensor([8, 4725, 1],"float32"), Tensor([8, 4725, 1],"float32"), reduction="sum", ) paddle.nn.functional.binary_cross_entropy(Tensor([8, 4725, 80],"float32"), Tensor([8, 4725, 80],"float32"), weight=Tensor([8, 4725, 80],"float32"), reduction="sum", ) -paddle.nn.functional.binary_cross_entropy_with_logits(Tensor([1, 1, 2],"float64"), label=Tensor([1, 1, 2],"float64"), weight=None, reduction="mean", name=None, ) paddle.nn.functional.channel_shuffle(Tensor([2, 4, 4, 9],"float64"), 3, "NHWC", ) paddle.nn.functional.channel_shuffle(Tensor([2, 4, 4, 9],"float64"), 3, "NHWC", None, ) paddle.nn.functional.channel_shuffle(Tensor([2, 9, 4, 4],"float64"), 3, "NCHW", ) @@ -332410,7 +332471,6 @@ paddle.nn.functional.cross_entropy(Tensor([1632, 8],"float32"), Tensor([1632],"i paddle.nn.functional.cross_entropy(Tensor([1636, 8],"float32"), Tensor([1636],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([164, 17],"float16"), Tensor([164],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([164, 17],"float32"), Tensor([164],"int64"), reduction="none", ) -paddle.nn.functional.cross_entropy(Tensor([164, 4, 17],"float16"), Tensor([164, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([164, 8],"float32"), Tensor([164],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([1640, 8],"float32"), Tensor([1640],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([1644, 8],"float32"), Tensor([1644],"int64"), reduction="none", ) @@ -332607,7 +332667,6 @@ paddle.nn.functional.cross_entropy(Tensor([199, 4, 17],"float16"), Tensor([199, paddle.nn.functional.cross_entropy(Tensor([1992, 8],"float32"), Tensor([1992],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([1996, 8],"float32"), Tensor([1996],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([2, 1024, 1024, 2],"float32"), Tensor([2, 1024, 1024],"int64"), ignore_index=255, reduction="none", weight=None, ) -paddle.nn.functional.cross_entropy(Tensor([2, 10],"float32"), Tensor([2, 1],"int64"), reduction="none", use_softmax=False, ) paddle.nn.functional.cross_entropy(Tensor([2, 10],"float32"), Tensor([2, 1],"int64"), weight=None, ignore_index=-100, reduction="mean", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, ) paddle.nn.functional.cross_entropy(Tensor([2, 20, 100],"float32"), Tensor([2, 20, 1],"int64"), weight=None, ignore_index=-100, reduction="none", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, ) paddle.nn.functional.cross_entropy(Tensor([2, 2],"float32"), Tensor([2, 1],"int64"), reduction="none", ) @@ -333036,7 +333095,6 @@ paddle.nn.functional.cross_entropy(Tensor([2964, 8],"float32"), Tensor([2964],"i paddle.nn.functional.cross_entropy(Tensor([2968, 8],"float32"), Tensor([2968],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([297, 4, 17],"float16"), Tensor([297, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([2972, 8],"float32"), Tensor([2972],"int64"), reduction="none", ) -paddle.nn.functional.cross_entropy(Tensor([298, 4, 17],"float16"), Tensor([298, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([2988, 8],"float32"), Tensor([2988],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([299, 4, 17],"float16"), Tensor([299, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([2992, 8],"float32"), Tensor([2992],"int64"), reduction="none", ) @@ -333156,7 +333214,6 @@ paddle.nn.functional.cross_entropy(Tensor([332, 8],"float32"), Tensor([332],"int paddle.nn.functional.cross_entropy(Tensor([3332, 8],"float32"), Tensor([3332],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([334, 4, 17],"float16"), Tensor([334, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([3344, 8],"float32"), Tensor([3344],"int64"), reduction="none", ) -paddle.nn.functional.cross_entropy(Tensor([335, 4, 17],"float16"), Tensor([335, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([336, 17],"float16"), Tensor([336],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([336, 17],"float32"), Tensor([336],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([336, 8],"float32"), Tensor([336],"int64"), reduction="none", ) @@ -333237,9 +333294,7 @@ paddle.nn.functional.cross_entropy(Tensor([368, 17],"float32"), Tensor([368],"in paddle.nn.functional.cross_entropy(Tensor([368, 8],"float32"), Tensor([368],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([3680, 8],"float32"), Tensor([3680],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([3684, 8],"float32"), Tensor([3684],"int64"), reduction="none", ) -paddle.nn.functional.cross_entropy(Tensor([369, 4, 17],"float16"), Tensor([369, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([37, 212],"float16"), Tensor([37],"int64"), ignore_index=-1, reduction="mean", ) -paddle.nn.functional.cross_entropy(Tensor([371, 4, 17],"float16"), Tensor([371, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([372, 17],"float16"), Tensor([372],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([372, 17],"float32"), Tensor([372],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([372, 8],"float32"), Tensor([372],"int64"), reduction="none", ) @@ -333258,7 +333313,6 @@ paddle.nn.functional.cross_entropy(Tensor([376, 17],"float32"), Tensor([376],"in paddle.nn.functional.cross_entropy(Tensor([376, 8],"float32"), Tensor([376],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([380, 17],"float16"), Tensor([380],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([380, 17],"float32"), Tensor([380],"int64"), reduction="none", ) -paddle.nn.functional.cross_entropy(Tensor([380, 4, 17],"float16"), Tensor([380, 4],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([380, 8],"float32"), Tensor([380],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([3800, 8],"float32"), Tensor([3800],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([384, 17],"float16"), Tensor([384],"int64"), reduction="none", ) @@ -333583,7 +333637,6 @@ paddle.nn.functional.cross_entropy(Tensor([5924, 8],"float16"), Tensor([5924],"i paddle.nn.functional.cross_entropy(Tensor([5924, 8],"float32"), Tensor([5924],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([5928, 8],"float16"), Tensor([5928],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([5928, 8],"float32"), Tensor([5928],"int64"), reduction="none", ) -paddle.nn.functional.cross_entropy(Tensor([5940, 8000],"float32"), Tensor([5940],"int64"), weight=None, ignore_index=-100, reduction="mean", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, ) paddle.nn.functional.cross_entropy(Tensor([5944, 8],"float16"), Tensor([5944],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([5944, 8],"float32"), Tensor([5944],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([5948, 8],"float16"), Tensor([5948],"int64"), reduction="none", ) @@ -333723,7 +333776,6 @@ paddle.nn.functional.cross_entropy(Tensor([6400, 8],"float32"), Tensor([6400],"i paddle.nn.functional.cross_entropy(Tensor([6408, 8],"float16"), Tensor([6408],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([6408, 8],"float32"), Tensor([6408],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([641, 212],"float16"), Tensor([641, 1],"int64"), weight=None, ignore_index=-1, reduction="sum", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, ) -paddle.nn.functional.cross_entropy(Tensor([641, 212],"float32"), Tensor([641, 1],"int64"), weight=None, ignore_index=-1, reduction="sum", soft_label=False, axis=-1, use_softmax=True, label_smoothing=0.0, name=None, ) paddle.nn.functional.cross_entropy(Tensor([6412, 8],"float16"), Tensor([6412],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([6412, 8],"float32"), Tensor([6412],"int64"), reduction="none", ) paddle.nn.functional.cross_entropy(Tensor([6420, 8],"float16"), Tensor([6420],"int64"), reduction="none", ) @@ -335193,7 +335245,6 @@ paddle.nn.functional.embedding(Tensor([104, 18],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([104, 21],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 21],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 22],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([104, 22],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 24],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 25],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 26],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335212,7 +335263,6 @@ paddle.nn.functional.embedding(Tensor([104, 32],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([104, 32],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 33],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 33],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([104, 33],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 34],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 34],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([104, 35],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335258,7 +335308,6 @@ paddle.nn.functional.embedding(Tensor([111],"int64"), weight=Tensor([512, 256]," paddle.nn.functional.embedding(Tensor([112, 12],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 12],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 17],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([112, 17],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 21],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 21],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 23],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335289,7 +335338,6 @@ paddle.nn.functional.embedding(Tensor([112, 36],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([112, 37],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 38],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 39],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([112, 39],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 40],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 40],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([112, 41],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335339,14 +335387,12 @@ paddle.nn.functional.embedding(Tensor([120, 26],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([120, 26],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 27],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([120, 27],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 28],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 29],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 29],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 30],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 31],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 31],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([120, 31],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 32],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 32],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 33],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335355,7 +335401,6 @@ paddle.nn.functional.embedding(Tensor([120, 33],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([120, 33],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 34],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 34],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([120, 34],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 35],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 36],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 36],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335367,7 +335412,6 @@ paddle.nn.functional.embedding(Tensor([120, 40],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([120, 40],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 41],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120, 42],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([120, 42],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([120],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([121],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([122],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335402,7 +335446,6 @@ paddle.nn.functional.embedding(Tensor([128, 28],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([128, 29],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([128, 29],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([128, 29],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([128, 29],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([128, 30],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([128, 30],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([128, 30],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335474,7 +335517,6 @@ paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([2, 64],"f paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([50249, 32],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([50264, 32],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([50274, 32],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([512, 64],"float32"), padding_idx=1, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([66, 24],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([81, 24],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([13, 7],"int32"), weight=Tensor([84, 32],"float16"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335537,7 +335579,6 @@ paddle.nn.functional.embedding(Tensor([136, 26],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([136, 26],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([136, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([136, 27],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([136, 27],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([136, 27],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([136, 28],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([136, 28],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335652,7 +335693,6 @@ paddle.nn.functional.embedding(Tensor([144, 32],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([144, 32],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([144, 33],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([144, 34],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([144, 34],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([144, 35],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([144],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([145],"int64"), weight=Tensor([32000, 768],"float16"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335681,7 +335721,6 @@ paddle.nn.functional.embedding(Tensor([152, 23],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([152, 24],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 24],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 24],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([152, 24],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 25],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 25],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 25],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335691,7 +335730,6 @@ paddle.nn.functional.embedding(Tensor([152, 26],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([152, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 27],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 28],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([152, 28],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 29],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 30],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([152, 30],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335724,7 +335762,6 @@ paddle.nn.functional.embedding(Tensor([16, 141],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([16, 146],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([16, 146],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([16, 149],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([16, 149],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([16, 156],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([16, 166],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([16, 170],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335787,11 +335824,9 @@ paddle.nn.functional.embedding(Tensor([160, 24],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([160, 25],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 25],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 26],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([160, 26],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 27],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 28],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([160, 28],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 29],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 29],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([160, 30],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335816,7 +335851,6 @@ paddle.nn.functional.embedding(Tensor([168, 19],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([168, 19],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 20],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 20],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([168, 20],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 20],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 21],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 22],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335828,7 +335862,6 @@ paddle.nn.functional.embedding(Tensor([168, 24],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([168, 24],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 25],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 26],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([168, 26],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 27],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([168, 28],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335869,12 +335902,10 @@ paddle.nn.functional.embedding(Tensor([176, 23],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([176, 24],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176, 25],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176, 26],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([176, 26],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176, 27],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176, 28],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176, 29],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([176, 29],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([176],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([177],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([178],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335894,11 +335925,9 @@ paddle.nn.functional.embedding(Tensor([184, 17],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([184, 18],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 18],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 18],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([184, 18],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 19],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 20],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 20],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([184, 20],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 21],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 21],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([184, 22],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -335926,7 +335955,6 @@ paddle.nn.functional.embedding(Tensor([191],"int64"), weight=Tensor([512, 256]," paddle.nn.functional.embedding(Tensor([192, 10],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([192, 10],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([192, 15],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([192, 15],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([192, 16],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([192, 16],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([192, 17],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336331,7 +336359,6 @@ paddle.nn.functional.embedding(Tensor([200, 22],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([200, 22],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([200, 23],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([200, 24],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([200, 24],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([200, 25],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([200, 25],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([200],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336350,11 +336377,9 @@ paddle.nn.functional.embedding(Tensor([208, 15],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([208, 16],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 17],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 17],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([208, 17],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 17],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 18],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 18],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([208, 18],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 19],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 19],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([208, 20],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336377,7 +336402,6 @@ paddle.nn.functional.embedding(Tensor([216, 10],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([216, 10],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([216, 16],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([216, 17],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([216, 17],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([216, 18],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([216, 18],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([216, 19],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336486,7 +336510,6 @@ paddle.nn.functional.embedding(Tensor([24, 135],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([24, 136],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 137],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 139],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([24, 139],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 140],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 140],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 141],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336523,7 +336546,6 @@ paddle.nn.functional.embedding(Tensor([24, 173],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([24, 174],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 176],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 178],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([24, 178],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 182],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 182],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 205],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336532,7 +336554,6 @@ paddle.nn.functional.embedding(Tensor([24, 68],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([24, 72],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 72],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 80],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([24, 80],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 81],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 81],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 82],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336553,7 +336574,6 @@ paddle.nn.functional.embedding(Tensor([24, 97],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([24, 97],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 97],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 98],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([24, 98],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 99],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 99],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([24, 99],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336566,7 +336586,6 @@ paddle.nn.functional.embedding(Tensor([240, 14],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([240, 15],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([240, 15],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([240, 15],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([240, 15],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([240, 16],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([240, 16],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([240, 16],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336653,7 +336672,6 @@ paddle.nn.functional.embedding(Tensor([272, 13],"int64"), weight=Tensor([257, 51 paddle.nn.functional.embedding(Tensor([272, 14],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([272, 14],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([272, 15],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([272, 15],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([272, 5],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([272, 5],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([272, 6],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -336672,7 +336690,6 @@ paddle.nn.functional.embedding(Tensor([280, 15],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([280, 16],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([280, 16],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([280, 17],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([280, 17],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([280, 18],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([280, 18],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([280],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337059,7 +337076,6 @@ paddle.nn.functional.embedding(Tensor([30],"int64"), weight=Tensor([512, 256],"f paddle.nn.functional.embedding(Tensor([312, 10],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([312, 10],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([312, 11],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([312, 11],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([312, 12],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([312, 13],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([312, 14],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337110,13 +337126,11 @@ paddle.nn.functional.embedding(Tensor([32, 114],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([32, 114],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 115],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 115],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 115],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 117],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 117],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 117],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 118],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 119],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 119],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 121],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 121],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 122],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337142,7 +337156,6 @@ paddle.nn.functional.embedding(Tensor([32, 129],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([32, 129],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 130],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 131],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 131],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 132],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 133],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 135],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337215,7 +337228,6 @@ paddle.nn.functional.embedding(Tensor([32, 64],"int64"), weight=Tensor([33712, 5 paddle.nn.functional.embedding(Tensor([32, 65],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 66],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 67],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 67],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 68],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 68],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 69],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337223,9 +337235,7 @@ paddle.nn.functional.embedding(Tensor([32, 70],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([32, 70],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 71],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 72],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 72],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 73],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 73],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 74],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 75],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 76],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337269,7 +337279,6 @@ paddle.nn.functional.embedding(Tensor([32, 95],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([32, 95],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 96],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 96],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([32, 96],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 96],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 97],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([32, 97],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337313,7 +337322,6 @@ paddle.nn.functional.embedding(Tensor([360, 12],"int64"), weight=Tensor([1025, 1 paddle.nn.functional.embedding(Tensor([360, 13],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([360, 14],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([360, 6],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([360, 6],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([360, 9],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([360, 9],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([368, 10],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337325,7 +337333,6 @@ paddle.nn.functional.embedding(Tensor([368, 4],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([368, 4],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([368, 8],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([368, 9],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([368, 9],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([369],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([36],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([37],"int64"), weight=Tensor([512, 256],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337670,7 +337677,6 @@ paddle.nn.functional.embedding(Tensor([40, 66],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([40, 66],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 67],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 67],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([40, 67],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 69],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 69],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 70],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337681,7 +337687,6 @@ paddle.nn.functional.embedding(Tensor([40, 71],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([40, 71],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 72],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 72],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([40, 72],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 74],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 74],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 74],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337730,7 +337735,6 @@ paddle.nn.functional.embedding(Tensor([40, 93],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([40, 93],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 93],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 94],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([40, 94],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 95],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 95],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([40, 96],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337789,7 +337793,6 @@ paddle.nn.functional.embedding(Tensor([48, 103],"int64"), weight=Tensor([33712, paddle.nn.functional.embedding(Tensor([48, 104],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 104],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 105],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([48, 105],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 106],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 25],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 25],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337816,7 +337819,6 @@ paddle.nn.functional.embedding(Tensor([48, 48],"int64"), weight=Tensor([33712, 1 paddle.nn.functional.embedding(Tensor([48, 49],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 49],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 49],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([48, 49],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 51],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 51],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 51],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337837,7 +337839,6 @@ paddle.nn.functional.embedding(Tensor([48, 64],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([48, 65],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 65],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 66],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([48, 66],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 67],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 67],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 67],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -337886,7 +337887,6 @@ paddle.nn.functional.embedding(Tensor([48, 84],"int64"), weight=Tensor([33712, 5 paddle.nn.functional.embedding(Tensor([48, 85],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 85],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 86],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([48, 86],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 87],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 87],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([48, 88],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338144,7 +338144,6 @@ paddle.nn.functional.embedding(Tensor([56, 53],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([56, 53],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 53],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 54],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([56, 54],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 55],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 56],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 56],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338167,7 +338166,6 @@ paddle.nn.functional.embedding(Tensor([56, 65],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([56, 65],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 66],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 66],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([56, 66],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 67],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 67],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 68],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338180,7 +338178,6 @@ paddle.nn.functional.embedding(Tensor([56, 71],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([56, 71],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 72],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 72],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([56, 72],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 73],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 73],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([56, 73],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338474,7 +338471,6 @@ paddle.nn.functional.embedding(Tensor([64, 20],"int64"), weight=Tensor([33712, 5 paddle.nn.functional.embedding(Tensor([64, 23],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 24],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 24],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([64, 25],"int64"), weight=Tensor([6627, 512],"float32"), padding_idx=6626, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 27],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 27],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 29],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338516,7 +338512,6 @@ paddle.nn.functional.embedding(Tensor([64, 46],"int64"), weight=Tensor([33712, 5 paddle.nn.functional.embedding(Tensor([64, 47],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 47],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 47],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([64, 47],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 48],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 48],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 49],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338524,7 +338519,6 @@ paddle.nn.functional.embedding(Tensor([64, 50],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([64, 51],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 51],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 52],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([64, 52],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 53],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 54],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([64, 54],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338849,7 +338843,6 @@ paddle.nn.functional.embedding(Tensor([72, 51],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([72, 51],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 52],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 52],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([72, 52],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 53],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 53],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 54],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -338860,12 +338853,10 @@ paddle.nn.functional.embedding(Tensor([72, 55],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([72, 55],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 56],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 56],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([72, 56],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 56],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 57],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 57],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 58],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([72, 58],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 59],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 59],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([72, 60],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339256,7 +339247,6 @@ paddle.nn.functional.embedding(Tensor([80, 42],"int64"), weight=Tensor([257, 512 paddle.nn.functional.embedding(Tensor([80, 42],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 43],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 44],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([80, 44],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 45],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 45],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 46],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339278,7 +339268,6 @@ paddle.nn.functional.embedding(Tensor([80, 51],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([80, 51],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 51],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 52],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([80, 52],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 53],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 53],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([80, 54],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339313,7 +339302,6 @@ paddle.nn.functional.embedding(Tensor([87],"int64"), weight=Tensor([512, 256],"f paddle.nn.functional.embedding(Tensor([88, 12],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 12],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 14],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([88, 14],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 15],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 15],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 16],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339341,7 +339329,6 @@ paddle.nn.functional.embedding(Tensor([88, 36],"int64"), weight=Tensor([33712, 1 paddle.nn.functional.embedding(Tensor([88, 36],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 37],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 37],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([88, 37],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 38],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 38],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 39],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339378,7 +339365,6 @@ paddle.nn.functional.embedding(Tensor([88, 51],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([88, 52],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 52],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 53],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([88, 53],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 54],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 54],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 55],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339386,7 +339372,6 @@ paddle.nn.functional.embedding(Tensor([88, 56],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([88, 56],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 57],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 58],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([88, 58],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 8],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88, 8],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([88],"int64"), weight=Tensor([151936, 64],"float16"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339539,7 +339524,6 @@ paddle.nn.functional.embedding(Tensor([96, 18],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([96, 19],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 19],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 27],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([96, 27],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 28],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 29],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 29],"int64"), weight=Tensor([33712, 512],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -339561,7 +339545,6 @@ paddle.nn.functional.embedding(Tensor([96, 37],"int64"), weight=Tensor([1025, 10 paddle.nn.functional.embedding(Tensor([96, 37],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 38],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 38],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) -paddle.nn.functional.embedding(Tensor([96, 38],"int64"), weight=Tensor([33712, 1024],"float32"), padding_idx=0, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 39],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 39],"int64"), weight=Tensor([257, 512],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) paddle.nn.functional.embedding(Tensor([96, 40],"int64"), weight=Tensor([1025, 1024],"float32"), padding_idx=None, max_norm=None, norm_type=2.0, sparse=False, scale_grad_by_freq=False, name=None, ) @@ -345814,7 +345797,6 @@ paddle.nn.functional.linear(x=Tensor([13, 3, 37],"float32"), weight=Tensor([37, paddle.nn.functional.linear(x=Tensor([13, 3, 64],"float32"), weight=Tensor([64, 32],"float32"), bias=None, name=None, ) paddle.nn.functional.linear(x=Tensor([13, 3, 64],"float32"), weight=Tensor([64, 34],"float32"), bias=None, name=None, ) paddle.nn.functional.linear(x=Tensor([13, 32, 32],"float32"), weight=Tensor([32, 32],"float32"), bias=None, name=None, ) -paddle.nn.functional.linear(x=Tensor([13, 32],"float32"), weight=Tensor([32, 1],"float32"), bias=Tensor([1],"float32"), name=None, ) paddle.nn.functional.linear(x=Tensor([13, 32],"float32"), weight=Tensor([32, 2],"float32"), bias=None, name=None, ) paddle.nn.functional.linear(x=Tensor([13, 32],"float32"), weight=Tensor([32, 37],"float32"), bias=None, name=None, ) paddle.nn.functional.linear(x=Tensor([13, 32],"float32"), weight=Tensor([32, 3],"float32"), bias=None, name=None, ) @@ -348203,7 +348185,6 @@ paddle.nn.functional.log_softmax(Tensor([100000, 2],"float32"), ) paddle.nn.functional.log_softmax(Tensor([128, 1000],"float16"), axis=-1, ) paddle.nn.functional.log_softmax(Tensor([128, 159],"float32"), axis=-1, ) paddle.nn.functional.log_softmax(Tensor([128, 2],"float32"), axis=-1, ) -paddle.nn.functional.log_softmax(Tensor([16, 1000],"float16"), axis=-1, ) paddle.nn.functional.log_softmax(Tensor([2, 2, 1],"float32"), 0, ) paddle.nn.functional.log_softmax(Tensor([2, 2, 1],"float64"), 0, ) paddle.nn.functional.log_softmax(Tensor([2, 3, 4, 5],"float32"), -1, ) @@ -383705,7 +383686,6 @@ paddle.nn.functional.smooth_l1_loss(Tensor([1914, 50],"float32"), Tensor([1914, paddle.nn.functional.smooth_l1_loss(Tensor([200, 50],"float32"), Tensor([200, 50],"float32"), reduction="none", ) paddle.nn.functional.smooth_l1_loss(Tensor([4],"float32"), Tensor([4],"float32"), reduction="mean", delta=1.0, ) paddle.nn.functional.smooth_l1_loss(Tensor([8, 147, 8],"float32"), Tensor([8, 147, 8],"float32"), reduction="sum", ) -paddle.nn.functional.smooth_l1_loss(Tensor([8, 178, 8],"float32"), Tensor([8, 178, 8],"float32"), reduction="sum", ) paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"float32"), "none", None, ) paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"float32"), reduction="none", ) paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"float64"), "none", None, ) @@ -461676,7 +461656,6 @@ paddle.sum(Tensor([100, 76032],"float16"), axis=1, ) paddle.sum(Tensor([100, 77824],"float16"), axis=1, ) paddle.sum(Tensor([100, 78144],"float16"), axis=1, ) paddle.sum(Tensor([100, 82688],"float16"), axis=1, ) -paddle.sum(Tensor([100, 92416],"float16"), axis=1, ) paddle.sum(Tensor([1000, 1000],"float16"), ) paddle.sum(Tensor([1000, 10],"float16"), ) paddle.sum(Tensor([1000],"float16"), ) @@ -461706,18 +461685,14 @@ paddle.sum(Tensor([108, 67200],"float16"), axis=1, ) paddle.sum(Tensor([108, 70528],"float16"), axis=1, ) paddle.sum(Tensor([108, 87040],"float16"), axis=1, ) paddle.sum(Tensor([108, 89984],"float16"), axis=1, ) -paddle.sum(Tensor([108, 91840],"float16"), axis=1, ) paddle.sum(Tensor([108, 94848],"float16"), axis=1, ) paddle.sum(Tensor([10],"float16"), ) paddle.sum(Tensor([11008, 768],"bool"), ) -paddle.sum(Tensor([112, 102144],"float16"), axis=1, ) paddle.sum(Tensor([112, 54400],"float16"), axis=1, ) paddle.sum(Tensor([112, 60800],"float16"), axis=1, ) -paddle.sum(Tensor([112, 73984],"float16"), axis=1, ) paddle.sum(Tensor([116, 60800],"float16"), axis=1, ) paddle.sum(Tensor([116, 67200],"float16"), axis=1, ) paddle.sum(Tensor([116, 72960],"float16"), axis=1, ) -paddle.sum(Tensor([116, 73984],"float16"), axis=1, ) paddle.sum(Tensor([116, 82688],"float16"), axis=1, ) paddle.sum(Tensor([116, 91392],"float16"), axis=1, ) paddle.sum(Tensor([116, 92416],"float16"), axis=1, ) @@ -461775,9 +461750,7 @@ paddle.sum(Tensor([120, 92416],"float16"), axis=1, ) paddle.sum(Tensor([12288],"float16"), ) paddle.sum(Tensor([123, 1],"int32"), ) paddle.sum(Tensor([124, 54400],"float16"), axis=1, ) -paddle.sum(Tensor([124, 60800],"float16"), axis=1, ) paddle.sum(Tensor([124, 64000],"float16"), axis=1, ) -paddle.sum(Tensor([124, 82688],"float16"), axis=1, ) paddle.sum(Tensor([124, 84864],"float16"), axis=1, ) paddle.sum(Tensor([124, 91392],"float16"), axis=1, ) paddle.sum(Tensor([12582912],"float16"), ) @@ -461787,7 +461760,6 @@ paddle.sum(Tensor([128, 2],"float32"), axis=-1, ) paddle.sum(Tensor([128, 60800],"float16"), axis=1, ) paddle.sum(Tensor([128, 76160],"float16"), axis=1, ) paddle.sum(Tensor([128, 91392],"float16"), axis=1, ) -paddle.sum(Tensor([128, 92416],"float16"), axis=1, ) paddle.sum(Tensor([12],"float16"), axis=0, keepdim=True, ) paddle.sum(Tensor([13, 2, 4, 16, 16],"float32"), axis=2, ) paddle.sum(Tensor([13, 3, 3],"float32"), 2, ) @@ -461800,10 +461772,7 @@ paddle.sum(Tensor([13, 7],"int32"), axis=1, dtype="int64", ) paddle.sum(Tensor([13, 7],"int64"), axis=1, ) paddle.sum(Tensor([132, 54400],"float16"), axis=1, ) paddle.sum(Tensor([132, 60800],"float16"), axis=1, ) -paddle.sum(Tensor([132, 92416],"float16"), axis=1, ) -paddle.sum(Tensor([136, 112896],"float16"), axis=1, ) paddle.sum(Tensor([136, 73984],"float16"), axis=1, ) -paddle.sum(Tensor([136, 75392],"float16"), axis=1, ) paddle.sum(Tensor([136, 77824],"float16"), axis=1, ) paddle.sum(Tensor([136, 82688],"float16"), axis=1, ) paddle.sum(Tensor([140, 60800],"float16"), axis=1, ) @@ -461815,12 +461784,9 @@ paddle.sum(Tensor([144, 112896],"float16"), axis=1, ) paddle.sum(Tensor([144, 1],"int32"), ) paddle.sum(Tensor([144, 54400],"float16"), axis=1, ) paddle.sum(Tensor([144, 57600],"float16"), axis=1, ) -paddle.sum(Tensor([144, 67200],"float16"), axis=1, ) -paddle.sum(Tensor([144, 82688],"float16"), axis=1, ) paddle.sum(Tensor([148, 91392],"float16"), axis=1, ) paddle.sum(Tensor([148, 92416],"float16"), axis=1, ) paddle.sum(Tensor([148, 94848],"float16"), axis=1, ) -paddle.sum(Tensor([152, 107520],"float16"), axis=1, ) paddle.sum(Tensor([152, 75392],"float16"), axis=1, ) paddle.sum(Tensor([152, 82688],"float16"), axis=1, ) paddle.sum(Tensor([154, 1000],"float16"), axis=-1, ) @@ -461829,7 +461795,6 @@ paddle.sum(Tensor([156, 102144],"float16"), axis=1, ) paddle.sum(Tensor([156, 60800],"float16"), axis=1, ) paddle.sum(Tensor([156, 67200],"float16"), axis=1, ) paddle.sum(Tensor([156, 68224],"float16"), axis=1, ) -paddle.sum(Tensor([156, 74240],"float16"), axis=1, ) paddle.sum(Tensor([156, 82688],"float16"), axis=1, ) paddle.sum(Tensor([16, 10, 27],"float32"), -1, keepdim=True, name=None, ) paddle.sum(Tensor([16, 1000],"float16"), axis=-1, ) @@ -461916,7 +461881,6 @@ paddle.sum(Tensor([160, 102144],"float16"), axis=1, ) paddle.sum(Tensor([160, 54400],"float16"), axis=1, ) paddle.sum(Tensor([160, 56000],"float16"), axis=1, ) paddle.sum(Tensor([160, 60800],"float16"), axis=1, ) -paddle.sum(Tensor([160, 89984],"float16"), axis=1, ) paddle.sum(Tensor([16384],"float16"), ) paddle.sum(Tensor([164, 60800],"float16"), axis=1, ) paddle.sum(Tensor([164, 65664],"float16"), axis=1, ) @@ -461926,7 +461890,6 @@ paddle.sum(Tensor([16777216],"float16"), ) paddle.sum(Tensor([168, 92416],"float16"), axis=1, ) paddle.sum(Tensor([16],"float32"), ) paddle.sum(Tensor([172, 60800],"float16"), axis=1, ) -paddle.sum(Tensor([172, 80512],"float16"), axis=1, ) paddle.sum(Tensor([172, 82688],"float16"), axis=1, ) paddle.sum(Tensor([176, 60800],"float16"), axis=1, ) paddle.sum(Tensor([176, 69632],"float16"), axis=1, ) @@ -462075,21 +462038,17 @@ paddle.sum(Tensor([20, 82688],"float16"), axis=1, ) paddle.sum(Tensor([20, 85120],"float16"), axis=1, ) paddle.sum(Tensor([20, 89984],"float16"), axis=1, ) paddle.sum(Tensor([20, 91392],"float16"), axis=1, ) -paddle.sum(Tensor([20, 92352],"float16"), axis=1, ) paddle.sum(Tensor([20, 92416],"float16"), axis=1, ) paddle.sum(Tensor([20, 97280],"float16"), axis=1, ) paddle.sum(Tensor([20, 99712],"float16"), axis=1, ) paddle.sum(Tensor([2000],"int64"), ) paddle.sum(Tensor([204, 54400],"float16"), axis=1, ) -paddle.sum(Tensor([204, 62400],"float16"), axis=1, ) paddle.sum(Tensor([204, 67200],"float16"), axis=1, ) -paddle.sum(Tensor([204, 92416],"float16"), axis=1, ) paddle.sum(Tensor([208, 82688],"float16"), axis=1, ) paddle.sum(Tensor([212, 57600],"float16"), axis=1, ) paddle.sum(Tensor([212, 82688],"float16"), axis=1, ) paddle.sum(Tensor([216, 60800],"float16"), axis=1, ) paddle.sum(Tensor([216, 92416],"float16"), axis=1, ) -paddle.sum(Tensor([220, 60800],"float16"), axis=1, ) paddle.sum(Tensor([220, 63232],"float16"), axis=1, ) paddle.sum(Tensor([224, 54400],"float16"), axis=1, ) paddle.sum(Tensor([224, 59200],"float16"), axis=1, ) @@ -462107,7 +462066,6 @@ paddle.sum(Tensor([24, 63232],"float16"), axis=1, ) paddle.sum(Tensor([24, 64000],"float16"), axis=1, ) paddle.sum(Tensor([24, 67200],"float16"), axis=1, ) paddle.sum(Tensor([24, 68096],"float16"), axis=1, ) -paddle.sum(Tensor([24, 70528],"float16"), axis=1, ) paddle.sum(Tensor([24, 73984],"float16"), axis=1, ) paddle.sum(Tensor([24, 74240],"float16"), axis=1, ) paddle.sum(Tensor([24, 76032],"float16"), axis=1, ) @@ -462127,7 +462085,6 @@ paddle.sum(Tensor([24, 91840],"float16"), axis=1, ) paddle.sum(Tensor([24, 92416],"float16"), axis=1, ) paddle.sum(Tensor([24, 94848],"float16"), axis=1, ) paddle.sum(Tensor([24, 96768],"float16"), axis=1, ) -paddle.sum(Tensor([24, 97280],"float16"), axis=1, ) paddle.sum(Tensor([24, 99456],"float16"), axis=1, ) paddle.sum(Tensor([244, 82688],"float16"), axis=1, ) paddle.sum(Tensor([256, 1000],"float16"), axis=-1, ) @@ -462237,7 +462194,6 @@ paddle.sum(Tensor([36, 67200],"float16"), axis=1, ) paddle.sum(Tensor([36, 72960],"float16"), axis=1, ) paddle.sum(Tensor([36, 77824],"float16"), axis=1, ) paddle.sum(Tensor([36, 80256],"float16"), axis=1, ) -paddle.sum(Tensor([36, 80512],"float16"), axis=1, ) paddle.sum(Tensor([36, 82688],"float16"), axis=1, ) paddle.sum(Tensor([36, 84864],"float16"), axis=1, ) paddle.sum(Tensor([36, 86016],"float16"), axis=1, ) @@ -462373,7 +462329,6 @@ paddle.sum(Tensor([40, 112896],"float16"), axis=1, ) paddle.sum(Tensor([40, 54400],"float16"), axis=1, ) paddle.sum(Tensor([40, 56576],"float16"), axis=1, ) paddle.sum(Tensor([40, 59200],"float16"), axis=1, ) -paddle.sum(Tensor([40, 63232],"float16"), axis=1, ) paddle.sum(Tensor([40, 63936],"float16"), axis=1, ) paddle.sum(Tensor([40, 64000],"float16"), axis=1, ) paddle.sum(Tensor([40, 67200],"float16"), axis=1, ) @@ -462528,7 +462483,6 @@ paddle.sum(Tensor([60, 77824],"float16"), axis=1, ) paddle.sum(Tensor([60, 84864],"float16"), axis=1, ) paddle.sum(Tensor([60, 91392],"float16"), axis=1, ) paddle.sum(Tensor([60, 91840],"float16"), axis=1, ) -paddle.sum(Tensor([60, 92416],"float16"), axis=1, ) paddle.sum(Tensor([60, 94080],"float16"), axis=1, ) paddle.sum(Tensor([60, 96768],"float16"), axis=1, ) paddle.sum(Tensor([60, 99712],"float16"), axis=1, ) @@ -462599,7 +462553,6 @@ paddle.sum(Tensor([64, 84864],"float16"), axis=1, ) paddle.sum(Tensor([64, 89984],"float16"), axis=1, ) paddle.sum(Tensor([64, 91392],"float16"), axis=1, ) paddle.sum(Tensor([64, 92352],"float16"), axis=1, ) -paddle.sum(Tensor([64, 92416],"float16"), axis=1, ) paddle.sum(Tensor([64, 94080],"float16"), axis=1, ) paddle.sum(Tensor([64, 99712],"float16"), axis=1, ) paddle.sum(Tensor([640, 1000],"float16"), axis=-1, ) @@ -462619,7 +462572,6 @@ paddle.sum(Tensor([68, 112896],"float16"), axis=1, ) paddle.sum(Tensor([68, 67200],"float16"), axis=1, ) paddle.sum(Tensor([68, 73984],"float16"), axis=1, ) paddle.sum(Tensor([68, 82688],"float16"), axis=1, ) -paddle.sum(Tensor([68, 89216],"float16"), axis=1, ) paddle.sum(Tensor([68, 89984],"float16"), axis=1, ) paddle.sum(Tensor([68, 91392],"float16"), axis=1, ) paddle.sum(Tensor([68, 92416],"float16"), axis=1, ) @@ -462661,7 +462613,6 @@ paddle.sum(Tensor([76, 73984],"float16"), axis=1, ) paddle.sum(Tensor([76, 78336],"float16"), axis=1, ) paddle.sum(Tensor([76, 82688],"float16"), axis=1, ) paddle.sum(Tensor([76, 85120],"float16"), axis=1, ) -paddle.sum(Tensor([76, 89984],"float16"), axis=1, ) paddle.sum(Tensor([76, 92416],"float16"), axis=1, ) paddle.sum(Tensor([76, 97280],"float16"), axis=1, ) paddle.sum(Tensor([76, 99712],"float16"), axis=1, ) @@ -462770,7 +462721,6 @@ paddle.sum(Tensor([8, 94848],"float16"), axis=1, ) paddle.sum(Tensor([8, 97088],"float16"), axis=1, ) paddle.sum(Tensor([8, 99712],"float16"), axis=1, ) paddle.sum(Tensor([80, 102144],"float16"), axis=1, ) -paddle.sum(Tensor([80, 54400],"float16"), axis=1, ) paddle.sum(Tensor([80, 64000],"float16"), axis=1, ) paddle.sum(Tensor([80, 67200],"float16"), axis=1, ) paddle.sum(Tensor([80, 69888],"float16"), axis=1, ) @@ -462800,7 +462750,6 @@ paddle.sum(Tensor([84, 67200],"float16"), axis=1, ) paddle.sum(Tensor([84, 72960],"float16"), axis=1, ) paddle.sum(Tensor([84, 78336],"float16"), axis=1, ) paddle.sum(Tensor([84, 78400],"float16"), axis=1, ) -paddle.sum(Tensor([84, 91392],"float16"), axis=1, ) paddle.sum(Tensor([84, 97280],"float16"), axis=1, ) paddle.sum(Tensor([840, 1],"int32"), ) paddle.sum(Tensor([842, 1],"int32"), ) @@ -462823,7 +462772,6 @@ paddle.sum(Tensor([88, 89216],"float16"), axis=1, ) paddle.sum(Tensor([88, 91392],"float16"), axis=1, ) paddle.sum(Tensor([88, 92416],"float16"), axis=1, ) paddle.sum(Tensor([88, 94080],"float16"), axis=1, ) -paddle.sum(Tensor([88, 97280],"float16"), axis=1, ) paddle.sum(Tensor([8],"float32"), ) paddle.sum(Tensor([9, 8],"int64"), ) paddle.sum(Tensor([900, 1],"int32"), ) @@ -462859,7 +462807,6 @@ paddle.sum(Tensor([96, 60800],"float16"), axis=1, ) paddle.sum(Tensor([96, 62400],"float16"), axis=1, ) paddle.sum(Tensor([96, 76160],"float16"), axis=1, ) paddle.sum(Tensor([96, 77824],"float16"), axis=1, ) -paddle.sum(Tensor([96, 82688],"float16"), axis=1, ) paddle.sum(Tensor([96, 85120],"float16"), axis=1, ) paddle.sum(Tensor([96, 91392],"float16"), axis=1, ) paddle.sum(Tensor([96, 97280],"float16"), axis=1, )