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 8c18e893..4ba02b6b 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
@@ -227832,30 +227832,6 @@ paddle.increment(x=Tensor([1],"int32"), )
 paddle.increment(x=Tensor([1],"int64"), )
 paddle.increment(x=Tensor([1],"int64"), value=1.0, )
 paddle.incubate.nn.functional.blha_get_max_len(Tensor([10],"int32"), Tensor([10],"int32"), Tensor([10],"float32"), )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([101, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([2, 22016],"int32"), None, act_method="swiglu", compute_dtype="fp16", dequant_scales=Tensor([22016],"float32"), shift=None, smooth=None, quant_scale=0.0009313154732808471, quant_round_type=0, quant_max_bound=127.0, quant_min_bound=-127.0, )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([2, 22016],"int32"), None, act_method="swiglu", compute_dtype="fp16", dequant_scales=Tensor([22016],"float32"), shift=None, smooth=None, quant_scale=0.0010831302497535944, quant_round_type=0, quant_max_bound=127.0, quant_min_bound=-127.0, )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([2, 22016],"int32"), None, act_method="swiglu", compute_dtype="fp16", dequant_scales=Tensor([22016],"float32"), shift=None, smooth=None, quant_scale=0.0016999575309455395, quant_round_type=0, quant_max_bound=127.0, quant_min_bound=-127.0, )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([2, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([58, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([59, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([60, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([67, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([68, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([76, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([78, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([90, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([91, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(Tensor([98, 256],"float16"), Tensor([256],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 10],"int32"), bias=Tensor([10],"float16"), dequant_scales=Tensor([10],"float32"), act_method="gelu", compute_dtype="fp16", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float16"), bias=Tensor([512],"float16"), act_method="geglu", compute_dtype="default", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float16"), bias=Tensor([512],"float16"), act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float16"), bias=Tensor([512],"float16"), act_method="gelu", compute_dtype="default", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float16"), bias=Tensor([512],"float16"), act_method="gelu", compute_dtype="fp16", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float32"), bias=None, act_method="gelu", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float32"), bias=Tensor([512],"float32"), act_method="gelu", compute_dtype="default", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"float32"), bias=Tensor([512],"float32"), act_method="gelu", compute_dtype="fp32", )
-paddle.incubate.nn.functional.fused_bias_act(x=Tensor([2, 20, 512],"int32"), bias=Tensor([512],"float32"), dequant_scales=Tensor([512],"float32"), shift=Tensor([512],"float32"), smooth=Tensor([512],"float32"), act_method="gelu", compute_dtype="fp32", quant_scale=0.5, quant_round_type=1, quant_max_bound=127.0, quant_min_bound=-127.0, )
 paddle.incubate.nn.functional.fused_layer_norm(Tensor([1, 64],"float16"), norm_weight=None, norm_bias=None, epsilon=1e-06, begin_norm_axis=1, bias=None, residual=Tensor([1, 64],"float16"), )
 paddle.incubate.nn.functional.fused_layer_norm(Tensor([100, 512],"float16"), norm_weight=None, norm_bias=None, epsilon=1e-05, begin_norm_axis=1, bias=None, residual=Tensor([100, 512],"float16"), )
 paddle.incubate.nn.functional.fused_layer_norm(Tensor([101, 64],"float16"), norm_weight=None, norm_bias=None, epsilon=1e-06, begin_norm_axis=1, bias=None, residual=Tensor([101, 64],"float16"), )
@@ -288373,13679 +288349,6 @@ paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"i
 paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"int64"), "sum", None, )
 paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"int64"), reduction="mean", )
 paddle.nn.functional.soft_margin_loss(Tensor([5, 5],"float64"), Tensor([5, 5],"int64"), reduction="sum", )
-paddle.nn.functional.softmax(Tensor([10, 8, 153, 153],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 153, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 153, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 154, 105],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 154, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 154, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 154, 154],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 154, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 154, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 155, 105],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 155, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 155, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 155, 155],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 155, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 155, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 156, 105],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 156, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 156, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 156, 156],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 156, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 156, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 157, 105],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 157, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 157, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 157, 157],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 157, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 157, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 158, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 158, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 158, 158],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 158, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 158, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 159, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 159, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 159, 159],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 159, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 159, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 105],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 13],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 16],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 17],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 21],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 25],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 29],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 33],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 37],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 41],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 49],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 57],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 65],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 73],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 81],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 16, 9],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 160, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 160, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 160, 160],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 160, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 160, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 161, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 161, 161],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 161, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 161, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 162, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 162, 162],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 162, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 162, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 163, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 163, 163],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 163, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 163, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 164, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 164, 164],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 164, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 164, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 165, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 165, 165],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 165, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 165, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 166, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 166, 166],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 166, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 166, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 167, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 167, 167],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 167, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 167, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 168, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 168, 168],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 168, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 168, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 169, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 169, 169],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 169, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 105],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 129],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 13],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 17],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 21],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 25],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 29],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 33],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 37],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 41],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 49],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 57],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 65],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 73],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 81],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 89],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 97],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 17, 9],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 170, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 170, 170],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 171, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 171, 171],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 172, 137],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([10, 8, 173, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 173, 173],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 174, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 174, 174],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 175, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 175, 175],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 176, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 176, 176],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 177, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 177, 177],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([10, 8, 179, 137],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 179, 179],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 18, 105],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([10, 8, 18, 17],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([10, 8, 19, 105],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([10, 8, 19, 21],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 25],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 29],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 33],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 37],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 41],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 49],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 57],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 65],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 73],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 81],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([10, 8, 19, 89],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([96, 16, 50, 42],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 50, 43],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 16, 51, 48],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 51, 49],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 51, 50],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 51, 51],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 51, 52],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 51, 53],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 52, 10],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 52, 40],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 16, 52, 43],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 16, 53, 53],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 16, 9, 9],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 17],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([96, 8, 11, 11],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 8, 16, 16],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 8, 19, 19],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 8, 33, 33],"float32"), )
-paddle.nn.functional.softmax(Tensor([96, 8, 33, 40],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 8, 33, 42],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 8, 40, 40],"float32"), axis=-1, )
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-paddle.nn.functional.softmax(Tensor([96, 8, 42, 33],"float32"), )
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-paddle.nn.functional.softmax(Tensor([96, 8, 42, 42],"float32"), )
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-paddle.nn.functional.softmax(Tensor([960, 17],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([960, 196, 196],"float32"), axis=-1, )
-paddle.nn.functional.softmax(Tensor([960, 6, 49, 49],"float32"), -1, name=None, )
-paddle.nn.functional.softmax(Tensor([960, 8, 144, 144],"float32"), -1, name=None, )
-paddle.nn.functional.softmax(Tensor([960, 8, 49, 49],"float32"), -1, name=None, )
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-paddle.nn.functional.softmax(Tensor([964, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([968, 17],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([968, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([972, 17],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([972, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([973440, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([976, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([980, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([984, 17],"float32"), axis=1, )
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-paddle.nn.functional.softmax(Tensor([988, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([992, 17],"float32"), axis=1, )
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-paddle.nn.functional.softmax(Tensor([996, 17],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([996, 8],"float32"), axis=1, )
-paddle.nn.functional.softmax(Tensor([],"float32"), )
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-paddle.nn.functional.softmax(Tensor([],"float32"), axis=-1, dtype="float64", )
-paddle.nn.functional.softmax(Tensor([],"float32"), axis=0, dtype="float32", )
-paddle.nn.functional.softmax(Tensor([],"float32"), axis=0, dtype="float64", )
-paddle.nn.functional.softmax(x=Tensor([13, 4, 12, 12],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([16, 4, 12, 12],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([2, 3, 4],"float32"), )
-paddle.nn.functional.softmax(x=Tensor([2, 3, 4],"float64"), )
-paddle.nn.functional.softmax(x=Tensor([2, 3, 4],"float64"), axis=0, )
-paddle.nn.functional.softmax(x=Tensor([2, 3, 4],"float64"), axis=1, )
-paddle.nn.functional.softmax(x=Tensor([2, 3, 4],"float64"), axis=2, )
-paddle.nn.functional.softmax(x=Tensor([3, 4, 12, 12],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([32, 4, 12, 12],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([4, 4, 12, 12],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([416, 4, 30, 30],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([416, 4, 30, 7],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([416, 4, 50, 50],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([512, 4, 30, 30],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([512, 4, 30, 7],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([512, 4, 50, 50],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([52, 4, 30, 30],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([52, 4, 30, 7],"float32"), axis=-1, )
-paddle.nn.functional.softmax(x=Tensor([52, 4, 50, 50],"float32"), axis=-1, )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([1, 10],"float32"), Tensor([1, 1],"int64"), )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([100, 10],"float32"), Tensor([100, 1],"int64"), )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([2, 16, 32, 64],"float32"), Tensor([2, 1, 32, 64],"int64"), axis=1, )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([2, 16, 32, 64],"float32"), Tensor([2, 16, 1, 64],"int64"), axis=2, )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([2, 16, 32, 64],"float32"), Tensor([2, 16, 32, 1],"int64"), axis=-1, )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([2, 16, 32, 64],"float32"), Tensor([2, 16, 32, 1],"int64"), axis=3, )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([2, 16],"float32"), Tensor([2, 1],"int64"), )
-paddle.nn.functional.softmax_with_cross_entropy(Tensor([5, 2],"float32"), label=Tensor([5, 1],"int64"), soft_label=False, ignore_index=-100, numeric_stable_mode=True, return_softmax=False, axis=-1, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([100],"float32"), label=Tensor([1],"int64"), )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([12, 10],"float32"), label=Tensor([12, 1],"int64"), soft_label=False, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([16, 128],"float32"), label=Tensor([16, 1],"int64"), soft_label=False, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([18, 32],"float32"), label=Tensor([18, 1],"int64"), soft_label=False, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([2, 16],"float32"), label=Tensor([2, 1],"int64"), soft_label=False, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([4, 128],"float32"), label=Tensor([4, 1],"int64"), soft_label=False, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([6, 10],"float32"), label=Tensor([6, 1],"int64"), soft_label=False, )
-paddle.nn.functional.softmax_with_cross_entropy(logits=Tensor([8, 16],"float32"), label=Tensor([8, 1],"int64"), soft_label=False, )
 paddle.nn.functional.softplus(Tensor([1, 2, 3],"float32"), )
 paddle.nn.functional.softplus(Tensor([1, 2, 3],"float64"), )
 paddle.nn.functional.softplus(Tensor([10],"float64"), )
@@ -362539,216 +348842,6 @@ paddle.tensor_split(Tensor([7],"int64"), list[3,-1,16,], axis=0, )
 paddle.tensor_split(Tensor([7],"int64"), list[3,-1,5,2,16,], axis=0, )
 paddle.tensor_split(Tensor([7],"int64"), tuple(2,6,), )
 paddle.tensor_split(Tensor([7],"int64"), tuple(2,6,), axis=0, )
-paddle.tensordot(Tensor([0, 0, 5, 5],"float32"), Tensor([0, 0, 5, 5],"float32"), list[list[],list[],], )
-paddle.tensordot(Tensor([0, 5, 5, 5],"float64"), Tensor([0, 5, 5, 5],"float64"), list[list[],list[],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[0,], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[0,1,3,2,],list[0,2,1,3,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[0,1,],list[0,3,2,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[0,],list[],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,0,2,],list[0,1,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,0,3,2,],list[3,0,1,2,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,2,0,],list[1,2,3,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,2,3,0,],list[],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,2,],list[2,1,0,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,2,],list[3,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,3,0,],list[1,3,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,3,0,],list[3,0,2,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[1,],list[0,2,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[2,0,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[2,0,3,],list[2,0,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[2,1,0,],list[2,1,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[2,1,],list[0,2,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[2,3,0,],list[3,1,0,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[2,3,0,],list[3,1,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[3,1,2,0,],list[2,3,1,0,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[3,1,2,],list[0,3,2,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[3,1,2,],list[1,3,2,0,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[3,1,2,],list[2,3,1,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[3,1,2,],list[3,1,0,],], )
-paddle.tensordot(Tensor([1, 1, 1, 5],"float64"), Tensor([1, 5, 1, 1],"float64"), list[list[3,2,],list[3,],], )
-paddle.tensordot(Tensor([1, 1, 5, 5],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[1,0,3,],list[2,3,0,],], )
-paddle.tensordot(Tensor([1, 1, 5, 5],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[1,3,0,],list[3,0,2,],], )
-paddle.tensordot(Tensor([1, 1, 5, 5],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,1,],list[0,2,],], )
-paddle.tensordot(Tensor([1, 1, 5, 5],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,3,1,],list[1,0,2,],], )
-paddle.tensordot(Tensor([1, 1, 5, 5],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,2,],list[3,1,],], )
-paddle.tensordot(Tensor([1, 1, 5, 5],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,],list[],], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[0,], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[3,0,], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[list[0,],list[],], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[list[2,3,0,],list[3,1,0,],], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[list[2,3,0,],list[3,1,],], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[list[3,0,],list[2,1,],], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[list[3,1,2,0,],list[2,3,1,0,],], )
-paddle.tensordot(Tensor([1, 5, 5, 5],"float64"), Tensor([1, 1, 1, 5],"float64"), list[list[3,],list[],], )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), 0, )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), 1, )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), 2, )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), Tensor([1],"int64"), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), Tensor([2, 2],"int64"), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), list[1,], )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), list[Tensor([2],"int64"),Tensor([2],"int64"),], )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), list[list[1,2,],list[0,1,],], )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(1,), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(Tensor([2],"int64"),Tensor([2],"int64"),), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(list[1,2,],list[0,1,],), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(list[1,],), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(tuple(1,),), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(tuple(1,2,),tuple(0,1,),), )
-paddle.tensordot(Tensor([3, 4, 4],"float32"), Tensor([4, 4, 5],"float32"), tuple(tuple(2,1,),tuple(0,),), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), 0, )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), 1, )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), 2, )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), Tensor([1],"int64"), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), Tensor([2, 2],"int64"), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), list[1,], )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), list[Tensor([2],"int64"),Tensor([2],"int64"),], )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), list[list[1,2,],list[0,1,],], )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(1,), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(Tensor([2],"int64"),Tensor([2],"int64"),), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(list[1,2,],list[0,1,],), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(list[1,],), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(tuple(1,),), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(tuple(1,2,),tuple(0,1,),), )
-paddle.tensordot(Tensor([3, 4, 4],"float64"), Tensor([4, 4, 5],"float64"), tuple(tuple(2,1,),tuple(0,),), )
-paddle.tensordot(Tensor([5, 0, 5, 0],"float32"), Tensor([5, 0, 5, 0],"float32"), list[list[],list[],], )
-paddle.tensordot(Tensor([5, 5, 0, 5],"float32"), Tensor([5, 5, 0, 5],"float32"), list[list[],list[],], )
-paddle.tensordot(Tensor([5, 5, 5, 0],"float32"), Tensor([5, 5, 5, 0],"float32"), list[list[],list[],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([1, 1, 1, 1],"float64"), list[list[0,1,3,2,],list[0,2,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([1, 1, 1, 1],"float64"), list[list[1,2,0,],list[1,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([1, 1, 1, 1],"float64"), list[list[1,2,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([1, 1, 1, 1],"float64"), list[list[2,0,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([1, 1, 1, 1],"float64"), list[list[3,1,0,2,],list[2,3,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([1, 1, 1, 1],"float64"), list[list[3,],list[],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[0,], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[3,0,], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[0,2,3,],list[0,1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[0,3,],list[3,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[0,],list[],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[1,3,0,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[1,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,3,0,],list[1,2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,3,],list[1,3,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,3,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[2,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,0,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,1,2,],list[2,3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,1,2,],list[3,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,1,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,2,0,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,2,1,],list[2,0,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,2,],list[3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 1],"float64"), Tensor([5, 5, 1, 5],"float64"), list[list[3,],list[],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[3,0,], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[3,1,2,], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[0,1,3,],list[0,3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[0,2,3,],list[0,1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[0,2,3,],list[0,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[0,3,],list[3,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,0,2,],list[0,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,0,3,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,0,3,],list[2,3,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,0,],list[2,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,2,0,],list[1,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,2,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,2,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,3,0,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,3,0,],list[3,0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,3,],list[1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,3,],list[3,1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,],list[0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,],list[1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[1,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,0,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,0,3,],list[2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,1,0,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,1,],list[0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,3,0,],list[1,2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,3,0,],list[3,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,3,0,],list[3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,3,1,],list[1,0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,3,],list[1,3,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,3,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[2,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,0,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,0,],list[3,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,2,],list[0,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,2,],list[1,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,2,],list[2,3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,2,],list[3,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,2,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,1,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,2,0,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,2,0,],list[3,2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,2,1,],list[2,0,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,2,],list[3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,2,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[3,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float32"), Tensor([5, 5, 5, 5],"float32"), list[list[],list[0,3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[3,0,], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[3,1,2,], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[0,1,2,],list[2,0,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[0,1,3,],list[0,3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[0,1,],list[0,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[0,2,3,],list[0,1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[0,2,3,],list[0,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[0,3,],list[3,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,0,2,],list[0,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,0,3,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,0,3,],list[2,3,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,0,],list[2,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,2,0,],list[1,2,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,2,0,],list[1,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,2,],list[1,2,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,2,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,2,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,3,0,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,3,0,],list[3,0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,3,],list[1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,3,],list[3,1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,],list[0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,],list[1,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[1,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,0,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,0,3,],list[2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,1,0,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,1,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,1,],list[0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,3,0,],list[1,2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,3,0,],list[3,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,3,0,],list[3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,3,1,],list[1,0,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,3,],list[1,3,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,3,],list[1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[2,],list[0,1,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,0,],list[2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,0,],list[3,2,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,2,],list[0,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,2,],list[1,2,3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,2,],list[1,3,2,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,2,],list[2,3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,2,],list[3,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,2,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,1,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,2,0,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,2,0,],list[3,2,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,2,1,],list[2,0,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,2,],list[3,1,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,2,],list[3,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[3,],list[2,1,0,],], )
-paddle.tensordot(Tensor([5, 5, 5, 5],"float64"), Tensor([5, 5, 5, 5],"float64"), list[list[],list[0,3,1,],], )
-paddle.tensordot(x=Tensor([2, 3, 3, 4],"float64"), y=Tensor([3, 4, 3, 4],"float64"), )
-paddle.tensordot(x=Tensor([2, 3, 3, 4],"float64"), y=Tensor([3, 4, 3, 4],"float64"), axes=0, )
-paddle.tensordot(x=Tensor([2, 3, 4, 4],"float64"), y=Tensor([2, 3, 4, 4],"float64"), axes=0, )
-paddle.tensordot(x=Tensor([2, 3, 4, 4],"float64"), y=Tensor([3, 4, 4, 4],"float64"), axes=0, )
-paddle.tensordot(x=Tensor([2, 7, 4, 2],"float64"), y=Tensor([7, 7, 4, 2],"float64"), axes=list[tuple(1,2,3,),tuple(0,2,3,),], )
-paddle.tensordot(x=Tensor([2, 7, 4, 2],"float64"), y=Tensor([7, 7, 4, 2],"float64"), axes=tuple(list[1,2,3,],list[0,2,3,],), )
-paddle.tensordot(x=Tensor([2, 7, 4, 2],"float64"), y=Tensor([7, 7, 4, 2],"float64"), axes=tuple(list[1,2,3,],list[0,2,3,],list[4,5,6,],), )
-paddle.tensordot(x=Tensor([3, 3],"float32"), y=Tensor([3, 3],"float32"), axes=2, )
-paddle.tensordot(x=Tensor([3, 4, 3, 4],"float64"), y=Tensor([4, 4, 3, 4],"float64"), axes=1, )
-paddle.tensordot(x=Tensor([4, 2, 3, 5, 4],"float64"), y=Tensor([2, 4, 3, 5, 8],"float64"), axes=list[list[0,1,2,3,],list[1,0,],], )
 paddle.tile(Tensor([1, 1, 10],"int64"), list[1,10,1,], )
 paddle.tile(Tensor([1, 1, 10],"int64"), list[13,10,1,], )
 paddle.tile(Tensor([1, 1, 128],"int64"), repeat_times=list[1,128,1,], )
diff --git a/tester/api_config/monitor_config/big_tensor/GPU/monitoring_configs.txt b/tester/api_config/monitor_config/big_tensor/GPU/monitoring_configs.txt
index 9a2b179a..8b51bbd8 100644
--- a/tester/api_config/monitor_config/big_tensor/GPU/monitoring_configs.txt
+++ b/tester/api_config/monitor_config/big_tensor/GPU/monitoring_configs.txt
@@ -1739,11 +1739,6 @@ paddle.incubate.softmax_mask_fuse_upper_triangle(x=Tensor([4194304, 1, 32, 32],"
 paddle.incubate.softmax_mask_fuse_upper_triangle(x=Tensor([4194305, 1, 32, 32],"float16"), )
 paddle.incubate.softmax_mask_fuse_upper_triangle(x=Tensor([6497, 7, 224, 224],"float32"), )
 paddle.incubate.softmax_mask_fuse_upper_triangle(x=Tensor([7, 318318, 32, 32],"float32"), )
-paddle.index_add(Tensor([100, 100, 228171],"float32"), Tensor([20],"int32"), 1, Tensor([100, 20, 228171],"float32"), )
-paddle.index_add(Tensor([100, 22817014],"float32"), Tensor([20],"int32"), 0, Tensor([20, 22817014],"float32"), )
-paddle.index_add(Tensor([100, 42949673],"float16"), Tensor([20],"int64"), 0, Tensor([20, 42949673],"float16"), )
-paddle.index_add(Tensor([4, 3, 35651585],"float32"), Tensor([16],"int64"), 1, Tensor([4, 16, 35651585],"float32"), )
-paddle.index_add(Tensor([71303169, 3, 2],"float32"), Tensor([16],"int64"), 1, Tensor([71303169, 16, 2],"float32"), )
 paddle.index_put(Tensor([110, 42, 16601, 56],"float16"), tuple(Tensor([16, 16],"int32"),Tensor([16, 16],"int32"),Tensor([16601],"bool"),), Tensor([16, 16, 56],"float16"), True, )
 paddle.index_put(Tensor([20742740, 110],"float32"), tuple(Tensor([21],"int32"),Tensor([21],"int32"),), Tensor([21],"float32"), False, )
 paddle.index_put(Tensor([44, 97612894],"float16"), tuple(Tensor([44],"bool"),), Tensor([97612894],"float16"), True, )
@@ -2927,10 +2922,6 @@ paddle.scatter(Tensor([4294967297],"float16"), Tensor([10],"int64"), Tensor([10]
 paddle.scatter(Tensor([64],"int32"), Tensor([12],"int64"), Tensor([2281701379],"int32"), overwrite=True, )
 paddle.scatter(Tensor([67108865, 64],"float16"), Tensor([5551],"int32"), Tensor([5551, 64],"float16"), overwrite=True, )
 paddle.scatter(Tensor([67108865, 64],"float16"), Tensor([7485],"int32"), Tensor([7485, 64],"float16"), overwrite=True, )
-paddle.scatter_nd_add(Tensor([1, 1140850690, 2],"float32"), Tensor([1, 3],"int64"), Tensor([1],"float32"), )
-paddle.scatter_nd_add(Tensor([2, 1140850690, 1],"int32"), Tensor([1, 3],"int64"), Tensor([1],"int32"), )
-paddle.scatter_nd_add(Tensor([3, 5, 15211343, 10],"float32"), Tensor([3, 2],"int64"), Tensor([3, 15211343, 10],"float32"), )
-paddle.scatter_nd_add(Tensor([3, 5, 9, 16901492],"float32"), Tensor([3, 2],"int64"), Tensor([3, 9, 16901492],"float32"), )
 paddle.searchsorted(Tensor([1024],"bfloat16"), Tensor([4294967297],"bfloat16"), )
 paddle.searchsorted(sorted_sequence=Tensor([5],"int32"), values=Tensor([2281701379],"int32"), )
 paddle.searchsorted(sorted_sequence=Tensor([5],"int64"), values=Tensor([1140850690, 2],"int64"), )