update

Author: snnn

onnxruntime/core/providers/cuda/nn/pool.cc

@@ -179,7 +179,7 @@ Status Pool<T, PoolType, NHWC>::ComputeInternal(OpKernelContext* context) const
       // The second dim of x_dims is channel(C).
       // Put the remaining part in kernel_shape
       kernel_shape.assign(x_dims.begin() + 2, x_dims.end());
-      pads.assign(kernel_shape.size(), 0);
+      pads.assign(kernel_shape.size() * 2, 0);
       strides.assign(kernel_shape.size(), 1);
     }
   }

onnxruntime/test/providers/cpu/nn/pool_op_test.cc

@@ -202,6 +202,19 @@ TEST(PoolTest, MaxPool1D_wrong_kernel_shape) {
   test.Run(OpTester::ExpectResult::kExpectFailure, "[ShapeInferenceError] Attribute kernel_shape has incorrect size", {kCudaNHWCExecutionProvider, kTensorrtExecutionProvider});
 }
 
+TEST(PoolTest, MaxPool1D_global_pooling) {
+  OpTester test("GlobalMaxPool");
+
+  std::vector<float> x_vals = {1, 2, 3, 4, 5, 6, 7, 8};
+  std::vector<int64_t> x_dims = {1, 2, 4};
+  std::vector<int64_t> expected_dims = {1, 2, 1};
+  std::vector<float> expected_vals = {4, 8};
+
+  test.AddInput<float>("X", x_dims, x_vals);
+  test.AddOutput<float>("Y", expected_dims, expected_vals);
+  test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kCudaNHWCExecutionProvider, kTensorrtExecutionProvider});
+}
+
 TEST(PoolTest, MaxPool1D_case1) {
   OpTester test("MaxPool");