[QNN EP] Fix Pool builder assert in Debug build. (#25788)

### Description
In PoolOpBuilder, 
- Revise the check to exploit ORT macros.
- Fix invoking the function for 5D cases.

### Motivation and Context
Refer to #25778.
Pool builder incorrectly invokes a function calculating 4D shape in 5D input, which originally expects 3D cases only. However, the check used assert to validate the shape, which did not work in Release nor RelWithDebInfo builds.

onnxruntime/core/providers/qnn/builder/opbuilder/pool_op_builder.cc

@@ -93,15 +93,16 @@ Status PoolOpBuilder::IsOpSupported(QnnModelWrapper& qnn_model_wrapper,
   return Status::OK();
 }
 
-static std::vector<uint32_t> AmendOutputShapeForRank3Pool(
+Status AmendOutputShapeForRank3Pool(
     gsl::span<const uint32_t> input_shape,   // {N, H, W, C}
     gsl::span<const uint32_t> kernel_shape,  // {k_h, k_w}
     gsl::span<const uint32_t> strides,       // {s_h, s_w}
-    gsl::span<const uint32_t> pads) {
-  assert(input_shape.size() == 4 &&
-         kernel_shape.size() == 2 &&
-         strides.size() == 2 &&
-         pads.size() == 4);
+    gsl::span<const uint32_t> pads,
+    std::vector<uint32_t>& output_shape) {
+  ORT_RETURN_IF_NOT(input_shape.size() == 4, "Expecting input rank 4 for amending 1D Pool output shape.");
+  ORT_RETURN_IF_NOT(kernel_shape.size() == 2, "Expecting kernel size 2 for amending 1D Pool output shape.");
+  ORT_RETURN_IF_NOT(strides.size() == 2, "Expecting strides size 2 for amending 1D Pool output shape.");
+  ORT_RETURN_IF_NOT(pads.size() == 4, "Expecting pad size 4 for amending 1D Pool output shape.");
 
   const uint32_t N = input_shape[0];
   const uint32_t H = input_shape[1];
@@ -120,7 +121,13 @@ static std::vector<uint32_t> AmendOutputShapeForRank3Pool(
                        ? 0
                        : (padded_W - kernel_shape[1]) / strides[1] + 1;
 
-  return {N, out_H, out_W, C};
+  output_shape.resize(4);
+  output_shape[0] = N;
+  output_shape[1] = out_H;
+  output_shape[2] = out_W;
+  output_shape[3] = C;
+
+  return Status::OK();
 }
 
 Status PoolOpBuilder::SetCommonPoolParams(const NodeAttrHelper& node_helper,
@@ -177,10 +184,7 @@ Status PoolOpBuilder::SetCommonPoolParams(const NodeAttrHelper& node_helper,
   if (auto_pad.compare("NOTSET") != 0) {
     if (output_shape.size() == 3) {
       // Calculate rank-4 output shape for rank-3 input.
-      output_shape = AmendOutputShapeForRank3Pool(input_shape,
-                                                  filter_size,
-                                                  stride,
-                                                  pad_amount);
+      ORT_RETURN_IF_ERROR(AmendOutputShapeForRank3Pool(input_shape, filter_size, stride, pad_amount, output_shape));
     }
 
     for (size_t axis = 0; axis < rank - 2; ++axis) {
@@ -365,14 +369,6 @@ Status PoolOpBuilder::ProcessAttributesAndOutputs(QnnModelWrapper& qnn_model_wra
                                             std::move(output_shape)));
   }
 
-  // Calculate rank-4 output shape for rank-3 input.
-  std::vector<uint32_t> onnx_in_shape;
-  ORT_RETURN_IF_NOT(qnn_model_wrapper.GetOnnxShape(inputs[0].node_arg, onnx_in_shape), "Cannot get shape");
-  if (onnx_in_shape.size() == 3) {
-    onnx_in_shape = {onnx_in_shape[0], 1, onnx_in_shape[1], onnx_in_shape[2]};
-  }
-  auto pooled_shape = AmendOutputShapeForRank3Pool(onnx_in_shape, filter_size, stride, pad_amount);
-
   // Construct param wrappers.
   ORT_RETURN_IF_NOT(SetPoolParam(node_unit,
                                  param_filter_size,
@@ -443,6 +439,16 @@ Status PoolOpBuilder::ProcessAttributesAndOutputs(QnnModelWrapper& qnn_model_wra
 
     return Status::OK();
   }
+
+  // Calculate rank-4 output shape for rank-3 input.
+  std::vector<uint32_t> onnx_in_shape;
+  ORT_RETURN_IF_NOT(qnn_model_wrapper.GetOnnxShape(inputs[0].node_arg, onnx_in_shape), "Cannot get shape");
+  if (onnx_in_shape.size() == 3) {
+    onnx_in_shape = {onnx_in_shape[0], 1, onnx_in_shape[1], onnx_in_shape[2]};
+  }
+  std::vector<uint32_t> pooled_shape;
+  ORT_RETURN_IF_ERROR(AmendOutputShapeForRank3Pool(onnx_in_shape, filter_size, stride, pad_amount, pooled_shape));
+
   const auto& outputs = node_unit.Outputs();
   const std::string real_out = outputs[0].node_arg.Name();
   const std::string pool_out = real_out + "_reshape_after";