Fix negative dimension handling in narrow_copy (#22969)

Summary:
Pull Request resolved: #22969

Resolves: #13556

Normalize negative `dim` values before validating `narrow_copy` arguments. This prevents valid negative dimensions from reaching tensor size checks unnormalized and causing a runtime assertion.

Adds regression coverage for copying with `dim=-1`.

Reviewed By: mergennachin

Differential Revision: D121015244

Author: JakeStevens

kernels/portable/cpu/op_narrow_copy.cpp

@@ -25,16 +25,18 @@ Tensor& narrow_copy_out(
     Tensor& out) {
   (void)ctx;
 
+  ET_KERNEL_CHECK(ctx, dim_is_valid(dim, in.dim()), InvalidArgument, out);
+
+  if (dim < 0) {
+    dim += in.dim();
+  }
+
   ET_KERNEL_CHECK(
       ctx,
       check_narrow_copy_args(in, dim, start, length, out),
       InvalidArgument,
       out);
 
-  if (dim < 0) {
-    dim += in.dim();
-  }
-
   // @lint-ignore CLANGTIDY facebook-hte-CArray
   Tensor::SizesType target_sizes[kTensorDimensionLimit];
   size_t target_ndim = 0;

kernels/test/op_narrow_copy_test.cpp

@@ -67,6 +67,20 @@ TEST_F(OpNarrowCopyOutTest, AllDtypesSupported) {
 #undef TEST_ENTRY
 }
 
+TEST_F(OpNarrowCopyOutTest, NegativeDimSupported) {
+  TensorFactory<ScalarType::Int> tf;
+
+  Tensor input = tf.make({2, 3}, {1, 2, 3, 4, 5, 6});
+  Tensor out = tf.zeros({2, 2});
+  Tensor expected = tf.make({2, 2}, {2, 3, 5, 6});
+
+  Tensor ret =
+      op_narrow_copy_out(input, /*dim=*/-1, /*start=*/1, /*length=*/2, out);
+
+  EXPECT_TENSOR_EQ(ret, out);
+  EXPECT_TENSOR_EQ(ret, expected);
+}
+
 TEST_F(OpNarrowCopyOutTest, EmptyInputSupported) {
   TensorFactory<ScalarType::Int> tf;