arm_compute v19.08
diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
index 6be289a..00165cd 100644
--- a/utils/GraphUtils.cpp
+++ b/utils/GraphUtils.cpp
@@ -140,12 +140,14 @@
return ret;
}
-NumPyAccessor::NumPyAccessor(std::string npy_path, TensorShape shape, DataType data_type, std::ostream &output_stream)
+NumPyAccessor::NumPyAccessor(std::string npy_path, TensorShape shape, DataType data_type, DataLayout data_layout, std::ostream &output_stream)
: _npy_tensor(), _filename(std::move(npy_path)), _output_stream(output_stream)
{
- NumPyBinLoader loader(_filename);
+ NumPyBinLoader loader(_filename, data_layout);
TensorInfo info(shape, 1, data_type);
+ info.set_data_layout(data_layout);
+
_npy_tensor.allocator()->init(info);
_npy_tensor.allocator()->allocate();
@@ -184,6 +186,20 @@
return false;
}
+SaveNumPyAccessor::SaveNumPyAccessor(std::string npy_name, const bool is_fortran)
+ : _npy_name(std::move(npy_name)), _is_fortran(is_fortran)
+{
+}
+
+bool SaveNumPyAccessor::access_tensor(ITensor &tensor)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&tensor, 1, DataType::F32);
+
+ utils::save_to_npy(tensor, _npy_name, _is_fortran);
+
+ return false;
+}
+
ImageAccessor::ImageAccessor(std::string filename, bool bgr, std::unique_ptr<IPreprocessor> preprocessor)
: _already_loaded(false), _filename(std::move(filename)), _bgr(bgr), _preprocessor(std::move(preprocessor))
{