[Fix #11447] Use correct type for tensor shape vectors (#11448)

* [Fix] Use correct type for tensor shape vectors

* Replacing std::vector with absl::InlinedVector

* Remove explicit use of absl:: namespace;
Add back explicit size in constructors.

* Remove explicit size for InlinedVector

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

@@ -5,6 +5,7 @@
 #include <cmath>
 
 #include "core/common/common.h"
+#include "core/common/inlined_containers.h"
 #include "core/framework/op_kernel.h"
 #include "core/util/math.h"
 #include "core/util/math_cpuonly.h"
@@ -37,17 +38,17 @@ ACLNEPool PoolOperation(onnxruntime::OpKernelContext* context,
   const Tensor* X = context->Input<Tensor>(0);
   const TensorShape& x_shape = X->Shape();
 
-  std::vector<int64_t> pads = pool_attrs.pads;
-  std::vector<int64_t> strides = pool_attrs.strides;
-  std::vector<int64_t> kernel_shape = pool_attrs.kernel_shape;
+  auto pads = pool_attrs.pads;
+  auto strides = pool_attrs.strides;
+  auto kernel_shape = pool_attrs.kernel_shape;
 
   if (pool_attrs.global_pooling) {
     const auto& input_dims = x_shape.GetDims();
     kernel_shape.assign(input_dims.begin() + 2, input_dims.end());
     pads.assign(kernel_shape.size(), 0);
   }
 
-  std::vector<int64_t> output_dims = pool_attrs.SetOutputSize(x_shape, x_shape[1], &pads);
+  const auto& output_dims = pool_attrs.SetOutputSize(x_shape, x_shape[1], &pads);
   Tensor* Y = context->Output(0, TensorShape(output_dims));
 
   ACLNEPool tpool;
@@ -63,11 +64,11 @@ ACLNEPool PoolOperation(onnxruntime::OpKernelContext* context,
     if (pool_attrs.global_pooling) {
       layer->configure(tpool.in.get(), tpool.out.get(), arm_compute::PoolingLayerInfo(pool_type));
     } else {
-      std::vector<int64_t> aclStrides(2);
+      TensorShapeVector aclStrides(2);
       aclStrides[0] = (strides.size() == 2) ? strides[1] : 1;
       aclStrides[1] = strides[0];
 
-      std::vector<int64_t> aclPads(4);
+      InlinedVector<int64_t> aclPads(4);
     // The pad order in acl is: pad_left, pad_right, pad_top, pad_bottom
       if (pads.size() == 2) {
         if (strides.size() == 1) {
@@ -91,7 +92,7 @@ ACLNEPool PoolOperation(onnxruntime::OpKernelContext* context,
       arm_compute::PadStrideInfo aclPadStride = arm_compute::PadStrideInfo(aclStrides[0], aclStrides[1],
                                                                            aclPads[0], aclPads[1], aclPads[2], aclPads[3], arm_compute::DimensionRoundingType::FLOOR);
 
-      std::vector<int64_t> aclKernelShape(2);
+      TensorShapeVector aclKernelShape(2);
       aclKernelShape[0] = (kernel_shape.size() > 1) ? kernel_shape[1] : 1;
       aclKernelShape[1] = kernel_shape[0];
 
@@ -145,8 +146,8 @@ Status Pool<T, PoolType>::Compute(OpKernelContext* context) const {
 
   const Tensor* X = context->Input<Tensor>(0);
 
-  std::vector<int64_t> dilations(PoolBase::pool_attrs_.dilations);
-  std::vector<int64_t> aclDilations(2);
+  TensorShapeVector dilations(PoolBase::pool_attrs_.dilations);
+  InlinedVector<int64_t> aclDilations(2);
   aclDilations[0] = (dilations.size() == 2) ? dilations[1] : 1;
   aclDilations[1] = (!dilations.empty()) ? dilations[0] : 1;
 
@@ -191,8 +192,8 @@ template <typename T>
 Status MaxPoolV8<T>::Compute(OpKernelContext* context) const {
   const Tensor* X = context->Input<Tensor>(0);
 
-  std::vector<int64_t> dilations(PoolBase::pool_attrs_.dilations);
-  std::vector<int64_t> aclDilations(2);
+  TensorShapeVector dilations(PoolBase::pool_attrs_.dilations);
+  InlinedVector<int64_t> aclDilations(2);
   aclDilations[0] = (dilations.size() == 2) ? dilations[1] : 1;
   aclDilations[1] = (!dilations.empty()) ? dilations[0] : 1;