COMPMID-802 Add NHWC data format support for NEON im2col.
Change-Id: I86e678179106a2b83d1c6a7cfe562df91b0f9eb2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/124000
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
diff --git a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h
index ecfce24..5aa803f 100644
--- a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h
+++ b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h
@@ -111,7 +111,7 @@
void run(const Window &window, const ThreadInfo &info) override;
private:
- /** Template function to run the im2col optimised for the fully connected layer case
+ /** Template function to run the im2col optimised for the fully connected and flatten layers case
*
* @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
*/
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index c3d5b64..e174227 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -107,13 +107,6 @@
return shape_vector_sum_row;
}
-inline TensorShape compute_im2col_shape(const ITensorInfo &input)
-{
- TensorShape shape_im2col{ input.tensor_shape() };
- shape_im2col.collapse(3);
-
- return shape_im2col;
-}
inline TensorShape compute_col2im_shape(const ITensorInfo &input, std::pair<unsigned int, unsigned int> convolved_dims)
{
TensorShape col2im_shape{ input.tensor_shape() };
@@ -159,7 +152,25 @@
return scale_out_shape;
}
-inline TensorShape compute_im2col_shape(const ITensorInfo *input, const int num_input_dimensions = 3)
+inline TensorShape compute_im2col_conv_shape(const ITensorInfo *input, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation)
+{
+ // The output shape will be the 2D shape used as input for GEMM [ out_channels * kernel_area, num_elems_per_out_channel ]
+
+ TensorShape output_shape{ input->tensor_shape() };
+
+ const DataLayout data_layout = input->data_layout();
+ const int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+ const int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+ const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+
+ std::pair<unsigned int, unsigned int> out_dims = scaled_dimensions(output_shape[width_idx], output_shape[height_idx], kernel_dims.width, kernel_dims.height, conv_info, dilation);
+ output_shape.set(width_idx, (output_shape[channel_idx] * kernel_dims.area() + (has_bias ? 1 : 0)));
+ output_shape.set(height_idx, (out_dims.first * out_dims.second));
+ output_shape.set(channel_idx, 1);
+
+ return output_shape;
+}
+inline TensorShape compute_im2col_fc_shape(const ITensorInfo *input, const int num_input_dimensions = 3)
{
TensorShape output_shape{ input->tensor_shape() };
@@ -167,6 +178,21 @@
return output_shape;
}
+inline TensorShape compute_im2col_flatten_shape(const ITensorInfo *input)
+{
+ // The output shape will be the flatten version of the input (i.e. [ width * height * channels, 1, 1, ... ] ). Used for FlattenLayer.
+
+ ARM_COMPUTE_ERROR_ON(input->num_dimensions() < 3);
+
+ TensorShape output_shape{ input->tensor_shape() };
+
+ const size_t flatten_shape = input->dimension(0) * input->dimension(1) * input->dimension(2);
+ output_shape.set(0, flatten_shape);
+ output_shape.remove_dimension(1);
+ output_shape.remove_dimension(1);
+
+ return output_shape;
+}
inline TensorShape compute_interleave_custom_shape(const TensorShape &input, const int x_interleave, const int y_interleave)
{
TensorShape output_shape{ input };
diff --git a/arm_compute/runtime/NEON/functions/NEIm2Col.h b/arm_compute/runtime/NEON/functions/NEIm2Col.h
index cf4999b..caa8a01 100644
--- a/arm_compute/runtime/NEON/functions/NEIm2Col.h
+++ b/arm_compute/runtime/NEON/functions/NEIm2Col.h
@@ -26,6 +26,7 @@
#include "arm_compute/runtime/NEON/INESimpleFunction.h"
+#include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h"
#include "arm_compute/core/Size2D.h"
#include "arm_compute/core/Types.h"
@@ -34,9 +35,11 @@
class ITensor;
/** Basic function to run @ref NEIm2ColKernel */
-class NEIm2Col : public INESimpleFunction
+class NEIm2Col : public IFunction
{
public:
+ /** Default constructor */
+ NEIm2Col();
/** Configure the im2col NEON kernel
*
* @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
@@ -46,9 +49,10 @@
* @param[in] kernel_dims The kernel dimensions (width and height).
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] has_bias In case biases are provided expands the matrix with 1.
- * @param[in] is_fully_connected Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments
+ * @param[in] is_fully_connected (Optional) Determines whether this function will be called by @ref NEFullyConnectedLayer in order to validate the arguments
+ * @param[in] is_flatten (Optional) Determines whether this function will be called by @ref NEFlattenLayer in order to validate the arguments
*/
- void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected = false);
+ void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected = false, bool is_flatten = false);
/** Static function to check if given info will lead to a valid configuration of @ref NEIm2Col
*
* @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
@@ -58,11 +62,19 @@
* @param[in] kernel_dims The kernel dimensions (width and height).
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] has_bias In case biases are provided expands the matrix with 1.
- * @param[in] is_fully_connected Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments
+ * @param[in] is_fully_connected Determines whether this function will be called by @ref NEFullyConnectedLayer in order to validate the arguments
+ * @param[in] is_flatten Determines whether this function will be called by @ref NEFlattenLayer in order to validate the arguments
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected, bool is_flatten);
+
+ // Inherited methods overridden:
+ void run() override;
+
+private:
+ NEIm2ColKernel _kernel;
+ unsigned int _y_dim;
};
}
#endif /* __ARM_COMPUTE_NEIM2COL_H__ */
diff --git a/src/core/NEON/kernels/NEIm2ColKernel.cpp b/src/core/NEON/kernels/NEIm2ColKernel.cpp
index 348722c..5e165a6 100644
--- a/src/core/NEON/kernels/NEIm2ColKernel.cpp
+++ b/src/core/NEON/kernels/NEIm2ColKernel.cpp
@@ -53,27 +53,26 @@
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::QASYMM8 && has_bias);
ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
+ TensorShape expected_output_shape;
if(is_flatten) /* Called by FlattenLayer */
{
- size_t flatten_shape = input->tensor_shape().x() * input->tensor_shape().y() * input->tensor_shape().z();
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != flatten_shape);
+ expected_output_shape = misc::shape_calculator::compute_im2col_flatten_shape(input);
}
else if(!is_fully_connected) /* Called by ConvolutionLayer */
{
- std::pair<unsigned int, unsigned int> out_dims = scaled_dimensions(input->dimension(0), input->dimension(1), kernel_dims.width, kernel_dims.height, conv_info, dilation);
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != (input->dimension(2) * kernel_dims.area() + (has_bias ? 1 : 0)));
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != (out_dims.first * out_dims.second));
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(2) != 1);
+ expected_output_shape = misc::shape_calculator::compute_im2col_conv_shape(input, kernel_dims, conv_info, has_bias, dilation);
}
else /* Called by FullyConnectedLayer */
{
const int num_batch_dimensions = std::max(0, static_cast<int>(output->tensor_shape().num_dimensions()) - 1);
const int num_input_dimensions = input->tensor_shape().num_dimensions() - num_batch_dimensions;
- TensorInfo expected_output = output->clone()->set_tensor_shape(misc::shape_calculator::compute_im2col_shape(input, num_input_dimensions));
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output, output);
+ expected_output_shape = misc::shape_calculator::compute_im2col_fc_shape(input, num_input_dimensions);
}
+ TensorInfo expected_output = output->clone()->set_tensor_shape(expected_output_shape);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output, output);
+
return Status{};
}
@@ -194,12 +193,17 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
- const int kernel_depth = _input->info()->dimension(2);
- const int input_w = _input->info()->dimension(0);
- const int input_h = _input->info()->dimension(1);
- const int input_stride_x = _input->info()->strides_in_bytes().x();
- const int input_stride_y = _input->info()->strides_in_bytes().y();
- const int input_stride_z = _input->info()->strides_in_bytes().z();
+ const DataLayout data_layout = _input->info()->data_layout();
+ const unsigned int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+ const unsigned int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+ const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+
+ const int kernel_depth = _input->info()->dimension(channel_idx);
+ const int input_w = _input->info()->dimension(width_idx);
+ const int input_h = _input->info()->dimension(height_idx);
+ const int input_stride_x = _input->info()->strides_in_bytes()[width_idx];
+ const int input_stride_y = _input->info()->strides_in_bytes()[height_idx];
+ const int input_stride_z = _input->info()->strides_in_bytes()[channel_idx];
const int offset = is_data_type_quantized(_input->info()->data_type()) ? _input->info()->quantization_info().offset : 0;
int pad_left = 0;
@@ -222,9 +226,9 @@
// Setup output window
Window window_out(window);
- window_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _output->info()->strides_in_bytes().y() / _output->info()->element_size()));
- window_out.set(Window::DimY, Window::Dimension(window.y().start() * _convolved_dims.first, window.y().end() * _convolved_dims.first, _convolved_dims.first));
- window_out.set(Window::DimZ, Window::Dimension(0, 1, 1));
+ window_out.set(width_idx, Window::Dimension(0, _output->info()->dimension(width_idx), _output->info()->strides_in_bytes()[width_idx + 1] / _output->info()->strides_in_bytes()[width_idx]));
+ window_out.set(height_idx, Window::Dimension(window[height_idx].start() * _convolved_dims.first, window[height_idx].end() * _convolved_dims.first, _convolved_dims.first));
+ window_out.set(channel_idx, Window::Dimension(0, 1, 1));
// Create iterators
Iterator in(_input, window_in);
@@ -232,8 +236,8 @@
execute_window_loop(window, [&](const Coordinates & id)
{
- const int top_left_x = id.x() * stride_x + start_x;
- const int top_left_y = id.y() * stride_y + start_y;
+ const int top_left_x = id[width_idx] * stride_x + start_x;
+ const int top_left_y = id[height_idx] * stride_y + start_y;
// Get pointers
const uint8_t *const input_ptr = in.ptr();
@@ -327,13 +331,18 @@
ARM_COMPUTE_UNUSED(is_fully_connected, is_flatten);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, is_fully_connected, is_flatten, dilation));
+ const DataLayout data_layout = input->info()->data_layout();
+ const unsigned int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+ const unsigned int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+ const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+
_input = input;
_output = output;
_conv_info = conv_info;
_kernel_width = kernel_dims.width;
_kernel_height = kernel_dims.height;
_dilation = dilation;
- _convolved_dims = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1),
+ _convolved_dims = scaled_dimensions(input->info()->dimension(width_idx), input->info()->dimension(height_idx),
_kernel_width, _kernel_height,
_conv_info, _dilation);
_has_bias = has_bias;
@@ -402,9 +411,9 @@
ARM_COMPUTE_ERROR("Data type not supported");
break;
}
- window.set(Window::DimX, Window::Dimension(0, _convolved_dims.first, 1));
- window.set(Window::DimY, Window::Dimension(0, _convolved_dims.second, 1));
- window.set(Window::DimZ, Window::Dimension(0, 1, 1));
+ window.set(width_idx, Window::Dimension(0, _convolved_dims.first, 1));
+ window.set(height_idx, Window::Dimension(0, _convolved_dims.second, 1));
+ window.set(channel_idx, Window::Dimension(0, 1, 1));
}
// The NEIm2ColKernel doesn't need padding so update_window_and_padding() can be skipped
diff --git a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
index 676706f..5dd1f00 100644
--- a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
+++ b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
@@ -114,7 +114,7 @@
// If the fully connected layer is called after a convolution layer, the input tensor must be linearized
// Initialize output tensor for im2col
- TensorShape shape_im2col = compute_im2col_shape(input->info());
+ TensorShape shape_im2col = compute_im2col_fc_shape(input->info());
_im2col_output.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col));
// Configure im2col kernel
@@ -244,7 +244,7 @@
bool is_quantized = is_data_type_quantized_asymmetric(input->data_type());
const GPUTarget gpu_target = CLScheduler::get().target();
- const ITensorInfo &im2col_input = TensorInfo(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_im2col_shape(input)));
+ const ITensorInfo &im2col_input = TensorInfo(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_im2col_fc_shape(input)));
const ITensorInfo &reshaped_weights = TensorInfo(weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_transposed_shape(*weights)));
const ITensorInfo &gemmlowp_output = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32));
diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
index b310ad3..958d081 100644
--- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
+++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
@@ -188,7 +188,7 @@
if(_linearize_input)
{
- _im2col_output.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_im2col_shape(input->info(), num_input_dimensions)));
+ _im2col_output.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_im2col_fc_shape(input->info(), num_input_dimensions)));
// Configure im2col kernel
_memory_group.manage(&_im2col_output);
@@ -288,7 +288,7 @@
if(linearize_input)
{
- im2col_output->set_tensor_shape(compute_im2col_shape(input, num_input_dimensions));
+ im2col_output->set_tensor_shape(compute_im2col_fc_shape(input, num_input_dimensions));
ARM_COMPUTE_RETURN_ON_ERROR(NEIm2ColKernel::validate(input, im2col_output.get(), Size2D(1, 1), PadStrideInfo(1, 1, 0, 0), false, true));
diff --git a/src/runtime/NEON/functions/NEIm2Col.cpp b/src/runtime/NEON/functions/NEIm2Col.cpp
index b962db9..6b95cb0 100644
--- a/src/runtime/NEON/functions/NEIm2Col.cpp
+++ b/src/runtime/NEON/functions/NEIm2Col.cpp
@@ -23,19 +23,30 @@
*/
#include "arm_compute/runtime/NEON/functions/NEIm2Col.h"
-#include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "support/ToolchainSupport.h"
using namespace arm_compute;
-void NEIm2Col::configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected)
+NEIm2Col::NEIm2Col()
+ : _kernel(), _y_dim(1)
{
- auto k = arm_compute::support::cpp14::make_unique<NEIm2ColKernel>();
- k->configure(input, output, kernel_dims, conv_info, has_bias, is_fully_connected);
- _kernel = std::move(k);
}
-Status NEIm2Col::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected)
+void NEIm2Col::configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected, bool is_flatten)
{
- return NEIm2ColKernel::validate(input, output, kernel_dims, conv_info, has_bias, is_fully_connected);
+ _y_dim = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT);
+
+ _kernel.configure(input, output, kernel_dims, conv_info, has_bias, is_fully_connected, is_flatten);
+}
+
+Status NEIm2Col::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected, bool is_flatten)
+{
+ return NEIm2ColKernel::validate(input, output, kernel_dims, conv_info, has_bias, is_fully_connected, is_flatten);
+}
+
+void NEIm2Col::run()
+{
+ NEScheduler::get().schedule(&_kernel, _y_dim);
}
diff --git a/tests/validation/NEON/Im2Col.cpp b/tests/validation/NEON/Im2Col.cpp
index 96dd6f8..ce00128 100644
--- a/tests/validation/NEON/Im2Col.cpp
+++ b/tests/validation/NEON/Im2Col.cpp
@@ -23,10 +23,13 @@
*/
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEIm2Col.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/datasets/ShapeDatasets.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/Im2ColFixture.h"
namespace arm_compute
{
@@ -34,6 +37,12 @@
{
namespace validation
{
+namespace
+{
+const auto conv_args = combine(combine(combine(framework::dataset::make("KernelDims", { Size2D(3U, 3U), Size2D(5U, 5U) }), framework::dataset::make("PadStride", { PadStrideInfo(1U, 1U, 0U, 0U), PadStrideInfo(1U, 1U, 1U, 1U), PadStrideInfo(2U, 2U, 0U, 2U) })),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(0.5f, 10))),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }));
+} // namespace
TEST_SUITE(NEON)
TEST_SUITE(Im2Col)
@@ -45,7 +54,7 @@
TensorInfo(TensorShape(10U, 12U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point
TensorInfo(TensorShape(10U, 12U, 2U), 1, DataType::QASYMM8), // Bias not supported with QASYMM8
TensorInfo(TensorShape(10U, 12U, 2U), 1, DataType::QASYMM8), // Mismatching shapes
- TensorInfo(TensorShape(10U, 12U, 2U), 1, DataType::QASYMM8),
+ TensorInfo(TensorShape(10U, 12U, 2U, 2U), 1, DataType::QASYMM8),
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(3U, 4U, 10U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(3U, 4U, 10U, 2U), 1, DataType::F16),
@@ -58,12 +67,67 @@
framework::dataset::make("Expected", { false, false, false, false, false, true })),
input_info, output_info, has_bias, expected)
{
- bool status = bool(NEIm2Col::validate(&input_info, &output_info, Size2D(3U, 3U), PadStrideInfo(), has_bias, false));
+ bool status = bool(NEIm2Col::validate(&input_info, &output_info, Size2D(3U, 3U), PadStrideInfo(), has_bias, false, false));
ARM_COMPUTE_EXPECT(status == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
+template <typename T>
+using NEIm2ColFixture = Im2ColValidationFixture<Tensor, Accessor, NEIm2Col, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEIm2ColFixture<float>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)),
+ conv_args))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEIm2ColFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)),
+ conv_args))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEIm2ColFixture<half>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)),
+ conv_args))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEIm2ColFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F16)),
+ conv_args))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+
+TEST_SUITE_END()
+
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEIm2ColFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::QASYMM8)),
+ conv_args))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEIm2ColFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::QASYMM8)),
+ conv_args))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/fixtures/FlattenLayerFixture.h b/tests/validation/fixtures/FlattenLayerFixture.h
index 3de0ba4..ef94ea8 100644
--- a/tests/validation/fixtures/FlattenLayerFixture.h
+++ b/tests/validation/fixtures/FlattenLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -27,6 +27,7 @@
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/Tensor.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
@@ -43,6 +44,8 @@
{
namespace validation
{
+using namespace arm_compute::misc::shape_calculator;
+
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class FlattenLayerValidationFixture : public framework::Fixture
{
@@ -51,8 +54,13 @@
void setup(TensorShape shape, DataType data_type)
{
_fractional_bits = is_data_type_fixed_point(data_type) ? 4 : 0;
- _target = compute_target(shape, data_type);
- _reference = compute_reference(shape, data_type);
+
+ TensorShape shape_flatten;
+ TensorInfo input_info(shape, 1, data_type, _fractional_bits);
+ shape_flatten = compute_im2col_flatten_shape(&input_info);
+
+ _target = compute_target(shape, shape_flatten, data_type);
+ _reference = compute_reference(shape, shape_flatten, data_type);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(_target.info()->tensor_shape(), _reference.shape());
}
@@ -73,11 +81,8 @@
}
}
- TensorType compute_target(const TensorShape &shape, DataType data_type)
+ TensorType compute_target(const TensorShape &shape, const TensorShape &shape_flatten, DataType data_type)
{
- TensorShape shape_flatten(shape);
- shape_flatten.collapse(3);
-
// Create tensors
TensorType src = create_tensor<TensorType>(shape, data_type, 1, _fractional_bits);
TensorType dst = create_tensor<TensorType>(shape_flatten, data_type, 1, _fractional_bits);
@@ -105,7 +110,7 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
+ SimpleTensor<T> compute_reference(const TensorShape &shape, const TensorShape &shape_flatten, DataType data_type)
{
// Create reference
SimpleTensor<T> src{ shape, data_type, 1, _fractional_bits };
@@ -113,7 +118,7 @@
// Fill reference
fill(src);
- return reference::flatten_layer<T>(src);
+ return reference::flatten_layer<T>(src, shape_flatten);
}
TensorType _target{};
diff --git a/tests/validation/fixtures/Im2ColFixture.h b/tests/validation/fixtures/Im2ColFixture.h
new file mode 100644
index 0000000..f403aa9
--- /dev/null
+++ b/tests/validation/fixtures/Im2ColFixture.h
@@ -0,0 +1,132 @@
+/*
+ * Copyright (c) 2017-2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_TEST_IM2COL_FIXTURE
+#define ARM_COMPUTE_TEST_IM2COL_FIXTURE
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/reference/Im2Col.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+using namespace arm_compute::misc::shape_calculator;
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class Im2ColValidationFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape, DataType data_type, const Size2D &kernel_dims, const PadStrideInfo &conv_info, const QuantizationInfo &quant_info, const DataLayout &data_layout)
+ {
+ _kernel_dims = kernel_dims;
+ _conv_info = conv_info;
+ _quant_info = quant_info;
+ _data_layout = data_layout;
+ _has_bias = data_type != DataType::QASYMM8;
+
+ if(_data_layout == DataLayout::NHWC)
+ {
+ permute(shape, PermutationVector(2U, 0U, 1U));
+ }
+
+ TensorShape output_shape;
+ TensorInfo input_info(shape, 1, data_type);
+ input_info.set_data_layout(_data_layout);
+ output_shape = compute_im2col_conv_shape(&input_info, _kernel_dims, _conv_info, _has_bias, Size2D(1U, 1U));
+
+ _target = compute_target(shape, output_shape, data_type);
+ _reference = compute_reference(shape, output_shape, data_type);
+ }
+
+protected:
+ template <typename U>
+ void fill(U &&tensor)
+ {
+ library->fill_tensor_uniform(tensor, 0);
+ }
+
+ TensorType compute_target(const TensorShape &shape, const TensorShape &output_shape, DataType data_type)
+ {
+ // Create tensors
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1, 0, _quant_info, _data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, _quant_info, _data_layout);
+
+ // Create and configure function
+ FunctionType im2col_func;
+ im2col_func.configure(&src, &dst, _kernel_dims, _conv_info, _has_bias);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Fill tensors
+ fill(AccessorType(src));
+
+ // Compute function
+ im2col_func.run();
+
+ return dst;
+ }
+
+ SimpleTensor<T> compute_reference(const TensorShape &shape, const TensorShape &output_shape, DataType data_type)
+ {
+ // Create reference
+ SimpleTensor<T> src{ shape, data_type, 1, 0, _quant_info, _data_layout };
+
+ // Fill reference
+ fill(src);
+
+ return reference::im2col<T>(src, output_shape, _kernel_dims, _conv_info, _has_bias);
+ }
+
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+ Size2D _kernel_dims{};
+ PadStrideInfo _conv_info{};
+ DataLayout _data_layout{};
+ QuantizationInfo _quant_info{};
+ bool _has_bias{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_IM2COL_FIXTURE */
diff --git a/tests/validation/reference/FlattenLayer.cpp b/tests/validation/reference/FlattenLayer.cpp
index 611701d..44f4d93 100644
--- a/tests/validation/reference/FlattenLayer.cpp
+++ b/tests/validation/reference/FlattenLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -34,12 +34,8 @@
namespace reference
{
template <typename T>
-SimpleTensor<T> flatten_layer(const SimpleTensor<T> &src)
+SimpleTensor<T> flatten_layer(const SimpleTensor<T> &src, const TensorShape &shape_flatten)
{
- TensorShape shape_flatten(src.shape());
- shape_flatten.set(0, src.shape()[0] * src.shape()[1] * src.shape()[2]);
- shape_flatten.remove_dimension(1);
- shape_flatten.remove_dimension(1);
SimpleTensor<T> dst(shape_flatten, src.data_type(), 1, src.fixed_point_position());
// Note: Since the reference implementation does not use padding bytes, we can copy directly the content of the source tensor
@@ -48,10 +44,10 @@
return dst;
}
-template SimpleTensor<float> flatten_layer(const SimpleTensor<float> &src);
-template SimpleTensor<half> flatten_layer(const SimpleTensor<half> &src);
-template SimpleTensor<qint8_t> flatten_layer(const SimpleTensor<qint8_t> &src);
-template SimpleTensor<qint16_t> flatten_layer(const SimpleTensor<qint16_t> &src);
+template SimpleTensor<float> flatten_layer(const SimpleTensor<float> &src, const TensorShape &shape_flatten);
+template SimpleTensor<half> flatten_layer(const SimpleTensor<half> &src, const TensorShape &shape_flatten);
+template SimpleTensor<qint8_t> flatten_layer(const SimpleTensor<qint8_t> &src, const TensorShape &shape_flatten);
+template SimpleTensor<qint16_t> flatten_layer(const SimpleTensor<qint16_t> &src, const TensorShape &shape_flatten);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/FlattenLayer.h b/tests/validation/reference/FlattenLayer.h
index b1286fe..5ccd429 100644
--- a/tests/validation/reference/FlattenLayer.h
+++ b/tests/validation/reference/FlattenLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -36,7 +36,7 @@
namespace reference
{
template <typename T>
-SimpleTensor<T> flatten_layer(const SimpleTensor<T> &src);
+SimpleTensor<T> flatten_layer(const SimpleTensor<T> &src, const TensorShape &shape_flatten);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/Im2Col.cpp b/tests/validation/reference/Im2Col.cpp
new file mode 100644
index 0000000..825f0a6
--- /dev/null
+++ b/tests/validation/reference/Im2Col.cpp
@@ -0,0 +1,109 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "Im2Col.h"
+
+#include "Permute.h"
+
+#include "arm_compute/core/Types.h"
+#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/Utils.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+void im2col_nchw(const SimpleTensor<T> &src, SimpleTensor<T> &dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias)
+{
+ // Create reference
+ const int pad_x = conv_info.pad().first;
+ const int pad_y = conv_info.pad().second;
+ const int stride_x = conv_info.stride().first;
+ const int stride_y = conv_info.stride().second;
+ const int kernel_width = kernel_dims.width;
+ const int kernel_height = kernel_dims.height;
+ const int src_width = src.shape().x();
+ const int src_height = src.shape().y();
+ const int src_depth = src.shape().z();
+ const int batches = src.shape().total_size_upper(3);
+ const int pad_val = is_data_type_quantized_asymmetric(src.data_type()) ? src.quantization_info().offset : 0;
+
+ int dst_idx = 0;
+ for(int b = 0; b < batches; ++b)
+ {
+ for(int y = -pad_y; y <= (src_height + pad_y - kernel_height); y += stride_y)
+ {
+ for(int x = -pad_x; x <= (src_width + pad_x - kernel_width); x += stride_x)
+ {
+ for(int z = 0; z < src_depth; ++z)
+ {
+ for(int patch_y = y; patch_y < (y + kernel_height); ++patch_y)
+ {
+ for(int patch_x = x; patch_x < (x + kernel_width); ++patch_x)
+ {
+ dst[dst_idx++] = tensor_elem_at(src, Coordinates(patch_x, patch_y, z, b), BorderMode::CONSTANT, static_cast<T>(pad_val));
+ }
+ }
+ }
+
+ if(has_bias)
+ {
+ dst[dst_idx++] = static_cast<T>(1);
+ }
+ }
+ }
+ }
+}
+
+template <typename T>
+SimpleTensor<T> im2col(const SimpleTensor<T> &src, const TensorShape &dst_shape, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias)
+{
+ SimpleTensor<T> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+
+ if(src.data_layout() == DataLayout::NHWC)
+ {
+ SimpleTensor<T> src_nchw = reference::permute<T>(src, PermutationVector(1U, 2U, 0U));
+ SimpleTensor<T> dst_nchw = reference::permute<T>(dst, PermutationVector(1U, 2U, 0U));
+
+ im2col_nchw(src_nchw, dst_nchw, kernel_dims, conv_info, has_bias);
+
+ return reference::permute<T>(dst_nchw, PermutationVector(2U, 0U, 1U));
+ }
+
+ im2col_nchw(src, dst, kernel_dims, conv_info, has_bias);
+
+ return dst;
+}
+
+template SimpleTensor<uint8_t> im2col(const SimpleTensor<uint8_t> &src, const TensorShape &output_shape, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
+template SimpleTensor<half> im2col(const SimpleTensor<half> &src, const TensorShape &output_shape, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
+template SimpleTensor<float> im2col(const SimpleTensor<float> &src, const TensorShape &output_shape, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/reference/Im2Col.h b/tests/validation/reference/Im2Col.h
new file mode 100644
index 0000000..4fe6ea9
--- /dev/null
+++ b/tests/validation/reference/Im2Col.h
@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2017-2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_TEST_IM2COL_H__
+#define __ARM_COMPUTE_TEST_IM2COL_H__
+
+#include "tests/SimpleTensor.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> im2col(const SimpleTensor<T> &src, const TensorShape &dst_shape, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_IM2COL_H__ */
diff --git a/tests/validation/reference/Permute.cpp b/tests/validation/reference/Permute.cpp
index 4a12ca6..db347e5 100644
--- a/tests/validation/reference/Permute.cpp
+++ b/tests/validation/reference/Permute.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -42,7 +42,7 @@
permute(dst_shape, perm);
// Create reference
- SimpleTensor<T> dst{ dst_shape, src.data_type() };
+ SimpleTensor<T> dst{ dst_shape, src.data_type(), src.num_channels(), src.fixed_point_position(), src.quantization_info() };
// Compute reference
for(int i = 0; i < src.num_elements(); ++i)
@@ -60,6 +60,8 @@
template SimpleTensor<uint8_t> permute(const SimpleTensor<uint8_t> &src, PermutationVector perm);
template SimpleTensor<uint16_t> permute(const SimpleTensor<uint16_t> &src, PermutationVector perm);
template SimpleTensor<uint32_t> permute(const SimpleTensor<uint32_t> &src, PermutationVector perm);
+template SimpleTensor<float> permute(const SimpleTensor<float> &src, PermutationVector perm);
+template SimpleTensor<half> permute(const SimpleTensor<half> &src, PermutationVector perm);
} // namespace reference
} // namespace validation
} // namespace test