[FEATURE SUPPORT] add pytorch geru kernel

README.md

@@ -23,7 +23,7 @@ The following common BLAS kernels have been implemented in multiple frameworks.
 | [axpby](./docs/axpby.md) | update vector| $y = \alpha x + \beta y$ | $3n$ | $3n$ | [✅](./kernel_course/python_ops/axpby.py) | [✅](./kernel_course/pytorch_ops/axpby.py) | [✅](./kernel_course/triton_ops/axpby.py) | ❌ | [✅](./tests/test_axpby.py) |
 | [dot](./docs/dot.md) | dot product | $z = x^\top y$ | $2n$ | $2n$ | [✅](./kernel_course/python_ops/dot.py) | [✅](./kernel_course/pytorch_ops/dot.py) | [✅](./kernel_course/triton_ops/dot.py) | ❌ | [✅](./tests/test_dot.py) |
 | [gemv](./docs/gemv.md) | general matrix-vector multiply | $y = \alpha A x + \beta y$ | $2mn$ | $mn + n + 2m$ | [✅](./kernel_course/python_ops/gemv.py) | [✅](./kernel_course/pytorch_ops/gemv.py) | [✅](./kernel_course/triton_ops/gemv.py) | ❌ | [✅](./tests/test_gemv.py) |
-| [geru](./docs/geru.md) | general rank-1 update | $A = A + \alpha x y^\top$ | $2mn$ | $2mn + m + n$ | [✅](./kernel_course/python_ops/geru.py) | ❌ | ❌ | ❌ | ❌ |
+| [geru](./docs/geru.md) | general rank-1 update | $A = A + \alpha x y^\top$ | $2mn$ | $2mn + m + n$ | [✅](./kernel_course/python_ops/geru.py) | [✅](./kernel_course/pytorch_ops/geru.py) | ❌ | ❌ | ❌ |
 | gemm | general matrix-matrix multiply | $C = \alpha A B + \beta C$ | $2mnk$ | $mk + nk + 2mn$ | ❌ | ❌ | ❌ | ❌ | ❌ |
 
 

kernel_course/pytorch_ops/geru.py

@@ -0,0 +1,25 @@
+import torch
+
+
+def geru(
+    A: torch.Tensor,
+    x: torch.Tensor,
+    y: torch.Tensor,
+    alpha: float,
+):
+    """
+    Updates tensor `A` by adding the outer product of vectors `x` and `y` scaled by `alpha` using PyTorch operations.
+
+    Args:
+        A (torch.Tensor): Matrix tensor to be updated.
+        x (torch.Tensor): Vector tensor.
+        y (torch.Tensor): Vector tensor.
+        alpha (float): Scaling factor for the outer product of `x` and `y`.
+
+    Returns:
+        torch.Tensor: The updated tensor `A`.
+    """
+
+    A += torch.mul(torch.ger(x, y), alpha)
+
+    return A