arm_compute v18.05
diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
index 448343a..0edb6f2 100644
--- a/utils/GraphUtils.cpp
+++ b/utils/GraphUtils.cpp
@@ -24,18 +24,36 @@
#include "utils/GraphUtils.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/SubTensor.h"
#include "utils/Utils.h"
-#ifdef ARM_COMPUTE_CL
-#include "arm_compute/core/CL/OpenCL.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#endif /* ARM_COMPUTE_CL */
-
#include <iomanip>
using namespace arm_compute::graph_utils;
+namespace
+{
+std::pair<arm_compute::TensorShape, arm_compute::PermutationVector> compute_permutation_paramaters(const arm_compute::TensorShape &shape,
+ arm_compute::DataLayout data_layout)
+{
+ // Set permutation parameters if needed
+ arm_compute::TensorShape permuted_shape = shape;
+ arm_compute::PermutationVector perm;
+ // Permute only if num_dimensions greater than 2
+ if(shape.num_dimensions() > 2)
+ {
+ perm = (data_layout == arm_compute::DataLayout::NHWC) ? arm_compute::PermutationVector(2U, 0U, 1U) : arm_compute::PermutationVector(1U, 2U, 0U);
+
+ arm_compute::PermutationVector perm_shape = (data_layout == arm_compute::DataLayout::NCHW) ? arm_compute::PermutationVector(2U, 0U, 1U) : arm_compute::PermutationVector(1U, 2U, 0U);
+ arm_compute::permute(permuted_shape, perm_shape);
+ }
+
+ return std::make_pair(permuted_shape, perm);
+}
+} // namespace
+
void TFPreproccessor::preprocess(ITensor &tensor)
{
Window window;
@@ -111,6 +129,45 @@
return ret;
}
+NumPyAccessor::NumPyAccessor(std::string npy_path, TensorShape shape, DataType data_type, std::ostream &output_stream)
+ : _npy_tensor(), _filename(std::move(npy_path)), _output_stream(output_stream)
+{
+ NumPyBinLoader loader(_filename);
+
+ TensorInfo info(shape, 1, data_type);
+ _npy_tensor.allocator()->init(info);
+ _npy_tensor.allocator()->allocate();
+
+ loader.access_tensor(_npy_tensor);
+}
+
+template <typename T>
+void NumPyAccessor::access_numpy_tensor(ITensor &tensor)
+{
+ const int num_elements = tensor.info()->total_size();
+ int num_mismatches = utils::compare_tensor<T>(tensor, _npy_tensor);
+ float percentage_mismatches = static_cast<float>(num_mismatches) / num_elements;
+
+ _output_stream << "Results: " << 100.f - (percentage_mismatches * 100) << " % matches with the provided output[" << _filename << "]." << std::endl;
+}
+
+bool NumPyAccessor::access_tensor(ITensor &tensor)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&tensor, 1, DataType::F32);
+ ARM_COMPUTE_ERROR_ON(_npy_tensor.info()->dimension(0) != tensor.info()->dimension(0));
+
+ switch(tensor.info()->data_type())
+ {
+ case DataType::F32:
+ access_numpy_tensor<float>(tensor);
+ break;
+ default:
+ ARM_COMPUTE_ERROR("NOT SUPPORTED!");
+ }
+
+ return false;
+}
+
PPMAccessor::PPMAccessor(std::string ppm_path, bool bgr, std::unique_ptr<IPreprocessor> preprocessor)
: _ppm_path(std::move(ppm_path)), _bgr(bgr), _preprocessor(std::move(preprocessor))
{
@@ -123,8 +180,15 @@
// Open PPM file
ppm.open(_ppm_path);
- ARM_COMPUTE_ERROR_ON_MSG(ppm.width() != tensor.info()->dimension(0) || ppm.height() != tensor.info()->dimension(1),
- "Failed to load image file: dimensions [%d,%d] not correct, expected [%d,%d].", ppm.width(), ppm.height(), tensor.info()->dimension(0), tensor.info()->dimension(1));
+ // Get permutated shape and permutation parameters
+ TensorShape permuted_shape = tensor.info()->tensor_shape();
+ arm_compute::PermutationVector perm;
+ if(tensor.info()->data_layout() != DataLayout::NCHW)
+ {
+ std::tie(permuted_shape, perm) = compute_permutation_paramaters(tensor.info()->tensor_shape(), tensor.info()->data_layout());
+ }
+ ARM_COMPUTE_ERROR_ON_MSG(ppm.width() != permuted_shape.x() || ppm.height() != permuted_shape.y(),
+ "Failed to load image file: dimensions [%d,%d] not correct, expected [%d,%d].", ppm.width(), ppm.height(), permuted_shape.x(), permuted_shape.y());
// Fill the tensor with the PPM content (BGR)
ppm.fill_planar_tensor(tensor, _bgr);
@@ -325,8 +389,8 @@
return true;
}
-NumPyBinLoader::NumPyBinLoader(std::string filename)
- : _filename(std::move(filename))
+NumPyBinLoader::NumPyBinLoader(std::string filename, DataLayout file_layout)
+ : _filename(std::move(filename)), _file_layout(file_layout)
{
}
@@ -371,30 +435,57 @@
}
}
+ bool are_layouts_different = (_file_layout != tensor.info()->data_layout());
+
// Validate tensor ranks
ARM_COMPUTE_ERROR_ON_MSG(shape.size() != tensor_shape.num_dimensions(), "Tensor ranks mismatch");
+ // Set permutation parameters if needed
+ TensorShape permuted_shape = tensor_shape;
+ arm_compute::PermutationVector perm;
+ if(are_layouts_different)
+ {
+ std::tie(permuted_shape, perm) = compute_permutation_paramaters(tensor_shape, tensor.info()->data_layout());
+ }
+
// Validate shapes
for(size_t i = 0; i < shape.size(); ++i)
{
- ARM_COMPUTE_ERROR_ON_MSG(tensor_shape[i] != shape[i], "Tensor dimensions mismatch");
+ ARM_COMPUTE_ERROR_ON_MSG(permuted_shape[i] != shape[i], "Tensor dimensions mismatch");
}
- // Read data
- if(tensor.info()->padding().empty() && (dynamic_cast<SubTensor *>(&tensor) == nullptr))
+ // Validate shapes and copy tensor
+ if(!are_layouts_different || perm.num_dimensions() <= 2)
{
- // If tensor has no padding read directly from stream.
- stream.read(reinterpret_cast<char *>(tensor.buffer()), tensor.info()->total_size());
+ // Read data
+ if(tensor.info()->padding().empty() && (dynamic_cast<SubTensor *>(&tensor) == nullptr))
+ {
+ // If tensor has no padding read directly from stream.
+ stream.read(reinterpret_cast<char *>(tensor.buffer()), tensor.info()->total_size());
+ }
+ else
+ {
+ // If tensor has padding accessing tensor elements through execution window.
+ Window window;
+ window.use_tensor_dimensions(tensor_shape);
+
+ execute_window_loop(window, [&](const Coordinates & id)
+ {
+ stream.read(reinterpret_cast<char *>(tensor.ptr_to_element(id)), tensor.info()->element_size());
+ });
+ }
}
else
{
// If tensor has padding accessing tensor elements through execution window.
Window window;
- window.use_tensor_dimensions(tensor_shape);
+ window.use_tensor_dimensions(permuted_shape);
execute_window_loop(window, [&](const Coordinates & id)
{
- stream.read(reinterpret_cast<char *>(tensor.ptr_to_element(id)), tensor.info()->element_size());
+ Coordinates coords(id);
+ arm_compute::permute(coords, perm);
+ stream.read(reinterpret_cast<char *>(tensor.ptr_to_element(coords)), tensor.info()->element_size());
});
}
return true;