Add Matmul function for Torch Frontend (#10476)

Co-authored-by: MahmoudAshraf97 <[email protected]>

ivy/functional/frontends/torch/linalg.py

@@ -181,3 +181,9 @@ def solve(input, other, *, out=None):
 @with_unsupported_dtypes({"1.11.0 and below": ("bfloat16", "float16")}, "torch")
 def tensorsolve(A, B, dims=None, *, out=None):
     return ivy.tensorsolve(A, B, axes=dims, out=out)
+
+
+@to_ivy_arrays_and_back
+@with_unsupported_dtypes({"1.11.0 and below": ("bfloat16", "float16")}, "torch")
+def matmul(input, other, *, out=None):
+    return ivy.matmul(input, other, out=out)

ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py

@@ -847,3 +847,37 @@ def test_torch_tensorsolve(
         A=A,
         B=B,
     )
+
+
+@handle_frontend_test(
+    fn_tree="torch.linalg.matmul",
+    dtype_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        shape=(3, 3),
+        num_arrays=2,
+        shared_dtype=True,
+        min_value=-1e04,
+        max_value=1e04,
+    ),
+    test_with_out=st.just(False),
+)
+def test_torch_matmul(
+    *,
+    dtype_x,
+    frontend,
+    fn_tree,
+    on_device,
+    test_flags,
+):
+    input_dtype, x = dtype_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        test_flags=test_flags,
+        input=x[0],
+        other=x[1],
+        rtol=1e-03,
+        atol=1e-06,
+    )