COMPMID-1933: Implement NEHeightConcatenateLayer.
Added support to concactenate tensors along the Y axis in NEConcatenateLayer.
Change-Id: Ib714bfcf9954cc35918efa7d52fc9164bb08bdf6
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/841
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/NEON/NEKernels.h b/arm_compute/core/NEON/NEKernels.h
index 5b1b701..1ce3821 100644
--- a/arm_compute/core/NEON/NEKernels.h
+++ b/arm_compute/core/NEON/NEKernels.h
@@ -89,6 +89,7 @@
#include "arm_compute/core/NEON/kernels/NEHOGDescriptorKernel.h"
#include "arm_compute/core/NEON/kernels/NEHOGDetectorKernel.h"
#include "arm_compute/core/NEON/kernels/NEHarrisCornersKernel.h"
+#include "arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h"
#include "arm_compute/core/NEON/kernels/NEHistogramKernel.h"
#include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h"
#include "arm_compute/core/NEON/kernels/NEIntegralImageKernel.h"
diff --git a/arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h b/arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h
new file mode 100644
index 0000000..540de68
--- /dev/null
+++ b/arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h
@@ -0,0 +1,84 @@
+/*
+ * Copyright (c) 2019 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_NEHEIGHTCONCATENATELAYERKERNEL_H__
+#define __ARM_COMPUTE_NEHEIGHTCONCATENATELAYERKERNEL_H__
+
+#include "arm_compute/core/NEON/INEKernel.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/** Interface for the height concatenate kernel.
+ * The input tensor will be concatenated into the output tensor.
+ */
+class NEHeightConcatenateLayerKernel : public INEKernel
+{
+public:
+ const char *name() const override
+ {
+ return "NEHeightConcatenateLayerKernel";
+ }
+ /** Default constructor */
+ NEHeightConcatenateLayerKernel();
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NEHeightConcatenateLayerKernel(const NEHeightConcatenateLayerKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NEHeightConcatenateLayerKernel &operator=(const NEHeightConcatenateLayerKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ NEHeightConcatenateLayerKernel(NEHeightConcatenateLayerKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ NEHeightConcatenateLayerKernel &operator=(NEHeightConcatenateLayerKernel &&) = default;
+ /** Default destructor */
+ ~NEHeightConcatenateLayerKernel() = default;
+ /** Initialise the kernel's inputs and output
+ *
+ * @param[in] input Input tensor. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
+ * @param[in] height_offset The starting offset on the Y axis for the output tensor.
+ * @param[in,out] output Output tensor. Data types supported: Same as @p input.
+ *
+ */
+ void configure(const ITensor *input, unsigned int height_offset, ITensor *output);
+ /** Static function to check if given info will lead to a valid configuration of @ref NEHeightConcatenateLayerKernel
+ *
+ * @param[in] input Input tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
+ * @param[in] height_offset The starting offset on the Y axis for the output tensor.
+ * @param[in] output Output tensor info. Data types supported: Same as @p input.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, unsigned int height_offset, const ITensorInfo *output);
+
+ // Inherited methods overridden:
+ void run(const Window &window, const ThreadInfo &info) override;
+
+private:
+ const ITensor *_input;
+ ITensor *_output;
+ unsigned int _height_offset;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NEHEIGHTCONCATENATELAYERKERNEL_H__ */
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 9d36405..6782cda 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -1222,30 +1222,30 @@
return out_shape;
}
-/** Calculate the width concatenate output shape of a vector of tensors
+/** Calculate the concatenate output shape of the concatenate operation along a single axis
*
- * @param[in] inputs_vector Vector containing the shapes of the inputs
+ * @param[in] input Vector containing the shapes of the inputs
+ * @param[in] axis Axis along which to concatenate the input tensors
*
* @return the calculated shape
*/
template <typename T>
-inline TensorShape calculate_width_concatenate_shape(const std::vector<T *> &inputs_vector)
+inline TensorShape calculate_concatenate_shape(const std::vector<T *> &input, size_t axis)
{
- TensorShape out_shape = extract_shape(inputs_vector[0]);
+ TensorShape out_shape = extract_shape(input[0]);
- size_t width = 0;
- for(const auto &tensor : inputs_vector)
+ size_t new_size = 0;
+ for(const auto &tensor : input)
{
ARM_COMPUTE_ERROR_ON(tensor == nullptr);
const TensorShape shape = extract_shape(tensor);
- width += shape.x();
+ new_size += shape[axis];
}
- out_shape.set(0, width);
+ out_shape.set(axis, new_size);
return out_shape;
}
-
/** Calculate the stack output shape of a tensor
*
* @param[in] a Input tensor info
diff --git a/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h b/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
index 2cdc720..b70d6eb 100644
--- a/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,6 +26,7 @@
#include "arm_compute/runtime/IFunction.h"
+#include "arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h"
#include "arm_compute/core/Types.h"
#include <memory>
@@ -41,6 +42,7 @@
/** Basic function to execute concatenate tensors along a given axis. This function calls the following kernels:
*
* -# @ref NEWidthConcatenateLayer (if underlying concatenation axis is 0).
+ * -# @ref NEHeightConcatenateLayerKernel (if underlying concatenation axis is 1).
* -# @ref NEDepthConcatenateLayer (if underlying concatenation axis is 2).
*/
class NEConcatenateLayer : public IFunction
@@ -51,21 +53,21 @@
/** Initialise the kernel's inputs vector and output.
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
- * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayer and @ref NEDepthConcatenateLayer.
+ * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayer, @ref NEHeightConcatenateLayerKernel and @ref NEDepthConcatenateLayer.
*
* @param[in,out] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32.
* @param[out] output Output tensor. Data types supported: Same as @p input.
- * @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0 and 2.
+ * @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0, 1 and 2.
*/
void configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis);
/** Static function to check if given info will lead to a valid configuration of @ref NEConcatenateLayer
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
- * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayer and @ref NEDepthConcatenateLayer.
+ * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayer, @ref NEHeightConcatenateLayerKernel and @ref NEDepthConcatenateLayer.
*
* @param[in] inputs_vector The vectors containing all the tensors info to concatenate. Data types supported: QASYMM8/F16/F32.
* @param[in] output Output tensor info. Data types supported: Same as @p input.
- * @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0 and 2.
+ * @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0, 1 and 2.
*
* @return a status
*/
@@ -75,7 +77,13 @@
void run() override;
private:
- std::unique_ptr<IFunction> _concat_function;
+ void configure_h_concatenate(std::vector<ITensor *> inputs_vector, ITensor *output);
+ static Status validate_h_concatenate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output);
+
+ std::unique_ptr<IFunction> _concat_function;
+ std::unique_ptr<NEHeightConcatenateLayerKernel[]> _hconcat_kernels;
+ unsigned int _num_inputs;
+ unsigned int _axis;
};
-}
+} // namespace arm_compute
#endif /* __ARM_COMPUTE_NECONCATENATELAYER_H__ */
diff --git a/src/core/NEON/kernels/NEHeightConcatenateLayerKernel.cpp b/src/core/NEON/kernels/NEHeightConcatenateLayerKernel.cpp
new file mode 100644
index 0000000..b8e204c
--- /dev/null
+++ b/src/core/NEON/kernels/NEHeightConcatenateLayerKernel.cpp
@@ -0,0 +1,139 @@
+/*
+ * Copyright (c) 2019 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 "arm_compute/core/NEON/kernels/NEHeightConcatenateLayerKernel.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/NEAsymm.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <cstdint>
+
+using namespace arm_compute;
+
+namespace
+{
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+{
+ const unsigned int num_elems_processed_per_iteration = 16 / output->element_size();
+
+ // The window needs to be based on input as we copy all the widths of input
+ Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+ AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
+ bool window_changed = update_window_and_padding(win, input_access, output_access);
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+
+Status validate_arguments(const ITensorInfo *input, unsigned int height_offset, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+ // Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1,
+ DataType::U8, DataType::S8, DataType::QASYMM8,
+ DataType::U16, DataType::S16, DataType::F16,
+ DataType::U32, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimX) != output->dimension(Window::DimX));
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimY) + height_offset > output->dimension(Window::DimY));
+ for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(i) != output->dimension(i));
+ }
+
+ return Status{};
+}
+} // namespace
+
+NEHeightConcatenateLayerKernel::NEHeightConcatenateLayerKernel()
+ : _input(nullptr), _output(nullptr), _height_offset(0)
+{
+}
+
+void NEHeightConcatenateLayerKernel::configure(const ITensor *input, unsigned int height_offset, ITensor *output)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), height_offset, output->info()));
+
+ _input = input;
+ _output = output;
+ _height_offset = height_offset;
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(input->info(), output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
+
+ INEKernel::configure(std::get<1>(win_config));
+}
+
+Status NEHeightConcatenateLayerKernel::validate(const ITensorInfo *input, unsigned int height_offset, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, height_offset, output));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
+ return Status{};
+}
+
+void NEHeightConcatenateLayerKernel::run(const Window &window, const ThreadInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+
+ // Offset output pointer to the correct position
+ uint8_t *output_ptr = _output->buffer() + _output->info()->offset_first_element_in_bytes() + _height_offset * _output->info()->strides_in_bytes()[Window::DimY];
+
+ // Create iterators
+ Iterator input(_input, window);
+ Iterator output(_output, window);
+ const DataType dt = _input->info()->data_type();
+ const QuantizationInfo &input_qinfo = _input->info()->quantization_info();
+ const QuantizationInfo &output_qinfo = _output->info()->quantization_info();
+ if(dt == DataType::QASYMM8 && input_qinfo != output_qinfo)
+ {
+ execute_window_loop(window, [&](const Coordinates &)
+ {
+ vst1q_u8(output_ptr + output.offset(), vquantize(vdequantize(vld1q_u8(input.ptr()), input_qinfo), output_qinfo));
+ },
+ input, output);
+ }
+ else
+ {
+ execute_window_loop(window, [&](const Coordinates &)
+ {
+ const auto in_ptr = input.ptr();
+ const auto out_ptr = output_ptr + output.offset();
+
+ wrapper::vstore(out_ptr, wrapper::vloadq(in_ptr));
+ },
+ input, output);
+ }
+}
diff --git a/src/graph/nodes/ConcatenateLayerNode.cpp b/src/graph/nodes/ConcatenateLayerNode.cpp
index ade3f6e..3ce09d0 100644
--- a/src/graph/nodes/ConcatenateLayerNode.cpp
+++ b/src/graph/nodes/ConcatenateLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -71,10 +71,9 @@
shapes.emplace_back(&input_descriptor.shape);
}
- // Calculate output shape
- if(axis_idx == 0)
+ if(axis_idx < 2)
{
- output_descriptor.shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(shapes);
+ output_descriptor.shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(shapes, axis_idx);
}
else if(axis_idx == 2)
{
@@ -138,4 +137,4 @@
v.visit(*this);
}
} // namespace graph
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute
diff --git a/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp b/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp
index d0801a6..6e42377 100644
--- a/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp
@@ -51,7 +51,7 @@
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->clone();
- const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimX);
auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
switch(num_inputs)
@@ -90,7 +90,7 @@
{
inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
}
- const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimX);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
index 21ab47d..f764a12 100644
--- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,6 +26,9 @@
#include "arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h"
#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
+
#include "arm_compute/core/Error.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
@@ -35,15 +38,66 @@
namespace arm_compute
{
NEConcatenateLayer::NEConcatenateLayer()
- : _concat_function(nullptr)
+ : _concat_function(nullptr),
+ _hconcat_kernels(),
+ _num_inputs(0),
+ _axis(Window::DimX)
{
}
+Status NEConcatenateLayer::validate_h_concatenate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
+ ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2);
+
+ // Output auto inizialitation if not yet initialized
+ TensorInfo tmp_output_info = *output->clone();
+ TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY);
+ auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
+
+ unsigned int offset = 0;
+ for(const auto &input : inputs_vector)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
+ ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+ offset += input->dimension(Window::DimY);
+ }
+
+ return Status{};
+}
+
+void NEConcatenateLayer::configure_h_concatenate(std::vector<ITensor *> inputs_vector, ITensor *output)
+{
+ _num_inputs = inputs_vector.size();
+
+ std::vector<ITensorInfo *> inputs_vector_info;
+ for(unsigned int i = 0; i < _num_inputs; ++i)
+ {
+ ARM_COMPUTE_ERROR_ON_NULLPTR(inputs_vector.at(i));
+ inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
+ }
+ TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY);
+
+ // Output auto inizialitation if not yet initialized
+ auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
+ ARM_COMPUTE_ERROR_THROW_ON(validate_h_concatenate(inputs_vector_info, output->info()));
+
+ unsigned int offset = 0;
+
+ _hconcat_kernels = arm_compute::support::cpp14::make_unique<NEHeightConcatenateLayerKernel[]>(_num_inputs);
+
+ for(unsigned int i = 0; i < _num_inputs; ++i)
+ {
+ _hconcat_kernels[i].configure(inputs_vector.at(i), offset, output);
+ offset += inputs_vector.at(i)->info()->dimension(Window::DimY);
+ }
+}
+
void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis)
{
ARM_COMPUTE_ERROR_ON(output == nullptr);
-
- switch(get_data_layout_dimension_index(output->info()->data_layout(), axis))
+ _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis);
+ switch(_axis)
{
case 0:
{
@@ -52,6 +106,11 @@
_concat_function = std::move(func);
break;
}
+ case 1:
+ {
+ configure_h_concatenate(inputs_vector, output);
+ break;
+ }
case 2:
{
auto func = support::cpp14::make_unique<NEDepthConcatenateLayer>();
@@ -73,6 +132,9 @@
case 0:
ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayer::validate(inputs_vector, output));
break;
+ case 1:
+ ARM_COMPUTE_RETURN_ON_ERROR(NEConcatenateLayer::validate_h_concatenate(inputs_vector, output));
+ break;
case 2:
ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayer::validate(inputs_vector, output));
break;
@@ -84,7 +146,28 @@
void NEConcatenateLayer::run()
{
- ARM_COMPUTE_ERROR_ON(_concat_function == nullptr);
- _concat_function->run();
+ switch(_axis)
+ {
+ case 0:
+ case 2:
+ {
+ ARM_COMPUTE_ERROR_ON(_concat_function == nullptr);
+ _concat_function->run();
+ break;
+ }
+ case 1:
+ {
+ for(unsigned i = 0; i < _num_inputs; ++i)
+ {
+ NEScheduler::get().schedule(_hconcat_kernels.get() + i, Window::DimY);
+ }
+ break;
+ }
+ default:
+ {
+ ARM_COMPUTE_ERROR("Axis not supported.");
+ break;
+ }
+ }
}
} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp b/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp
index 17c352b..9fce13c 100644
--- a/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp
@@ -48,7 +48,7 @@
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->clone();
- TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
+ TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimX);
auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
unsigned int width_offset = 0;
@@ -71,7 +71,7 @@
{
inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
}
- TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
+ TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimX);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h
index fddc773..b6923c1 100644
--- a/tests/datasets/ShapeDatasets.h
+++ b/tests/datasets/ShapeDatasets.h
@@ -732,11 +732,11 @@
}
};
-/** Data set containing tensor shapes for WidthConcatenateLayer. */
-class WidthConcatenateLayerShapes final : public ShapeDataset
+/** Data set containing tensor shapes for ConcatenateLayer. */
+class ConcatenateLayerShapes final : public ShapeDataset
{
public:
- WidthConcatenateLayerShapes()
+ ConcatenateLayerShapes()
: ShapeDataset("Shape",
{
TensorShape{ 232U, 65U, 3U },
diff --git a/tests/validation/CL/WidthConcatenateLayer.cpp b/tests/validation/CL/WidthConcatenateLayer.cpp
index 647e041..493320b 100644
--- a/tests/validation/CL/WidthConcatenateLayer.cpp
+++ b/tests/validation/CL/WidthConcatenateLayer.cpp
@@ -24,14 +24,14 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLWidthConcatenateLayer.h"
+#include "arm_compute/runtime/CL/functions/CLConcatenateLayer.h"
#include "tests/CL/CLAccessor.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/WidthConcatenateLayerFixture.h"
+#include "tests/validation/fixtures/ConcatenateLayerFixture.h"
namespace arm_compute
{
@@ -72,8 +72,7 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(CLWidthConcatenateLayer::validate(inputs_vector_info_raw,
- &output_info.clone()->set_is_resizable(false)));
+ bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw,&output_info.clone()->set_is_resizable(false),DataLayoutDimension::WIDTH ));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
@@ -93,26 +92,30 @@
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Create and configure function
- CLWidthConcatenateLayer concat_layer;
+ CLConcatenateLayer concat_layer;
- concat_layer.configure({ &src1, &src2, &src3 }, &dst);
+ concat_layer.configure({ &src1, &src2, &src3 }, &dst, DataLayoutDimension::WIDTH);
}
template <typename T>
-using CLWidthConcatenateLayerFixture = WidthConcatenateLayerValidationFixture<CLTensor, ICLTensor, CLAccessor, CLWidthConcatenateLayer, T>;
+using CLWidthConcatenateLayerFixture = ConcatenateLayerValidationFixture<CLTensor, ICLTensor, CLAccessor, CLConcatenateLayer, T>;
TEST_SUITE(Float)
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLWidthConcatenateLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLWidthConcatenateLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
framework::dataset::make("DataType",
- DataType::F16)))
+ DataType::F16)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLWidthConcatenateLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(concat(datasets::Large2DShapes(), datasets::Small4DShapes()),
- framework::dataset::make("DataType",
- DataType::F16)))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLWidthConcatenateLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(concat(datasets::Large2DShapes(), datasets::Small4DShapes()),
+ framework::dataset::make("DataType",
+ DataType::F16)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(CLAccessor(_target), _reference);
@@ -120,15 +123,18 @@
TEST_SUITE_END()
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLWidthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLWidthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
framework::dataset::make("DataType",
- DataType::F32)))
+ DataType::F32)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLWidthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::WidthConcatenateLayerShapes(), framework::dataset::make("DataType",
- DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLWidthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::ConcatenateLayerShapes(), framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("Axis", 0)))
{
// Validate output
validate(CLAccessor(_target), _reference);
@@ -138,15 +144,17 @@
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
framework::dataset::make("DataType",
- DataType::QASYMM8)))
+ DataType::QASYMM8)),
+ framework::dataset::make("Axis", 0)))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(datasets::WidthConcatenateLayerShapes(), framework::dataset::make("DataType",
- DataType::QASYMM8)))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::ConcatenateLayerShapes(), framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ framework::dataset::make("Axis", 0)))
{
// Validate output
validate(CLAccessor(_target), _reference);
diff --git a/tests/validation/Helpers.cpp b/tests/validation/Helpers.cpp
index 11c454e..e9612f2 100644
--- a/tests/validation/Helpers.cpp
+++ b/tests/validation/Helpers.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -98,17 +98,18 @@
return out_shape;
}
-TensorShape calculate_width_concatenate_shape(const std::vector<TensorShape> &input_shapes)
+TensorShape calculate_concatenate_shape(const std::vector<TensorShape> &input_shapes, size_t axis)
{
ARM_COMPUTE_ERROR_ON(input_shapes.empty());
-
TensorShape out_shape = input_shapes[0];
+ ARM_COMPUTE_ERROR_ON(axis >= out_shape.num_dimensions());
- int width = std::accumulate(input_shapes.begin(), input_shapes.end(), 0, [](int sum, const TensorShape & shape)
+ const int new_size = std::accumulate(input_shapes.begin(), input_shapes.end(), 0, [&](int sum, const TensorShape & shape)
{
- return sum + shape.x();
+ ARM_COMPUTE_ERROR_ON(axis >= shape.num_dimensions());
+ return sum + shape[axis];
});
- out_shape.set(0, width);
+ out_shape.set(axis, new_size);
return out_shape;
}
diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h
index 4d1d214..2e8c667 100644
--- a/tests/validation/Helpers.h
+++ b/tests/validation/Helpers.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -128,13 +128,14 @@
*/
TensorShape calculate_depth_concatenate_shape(const std::vector<TensorShape> &input_shapes);
-/** Calculate output tensor shape give a vector of input tensor to concatenate
+/** Calculate output tensor shape for the concatenate operation along a given axis
*
* @param[in] input_shapes Shapes of the tensors to concatenate across width.
+ * @param[in] axis Axis to use for the concatenate operation
*
* @return The shape of output concatenated tensor.
*/
-TensorShape calculate_width_concatenate_shape(const std::vector<TensorShape> &input_shapes);
+TensorShape calculate_concatenate_shape(const std::vector<TensorShape> &input_shapes, size_t axis);
/** Parameters of Harris Corners algorithm. */
struct HarrisCornersParameters
diff --git a/tests/validation/NEON/HeightConcatenateLayer.cpp b/tests/validation/NEON/HeightConcatenateLayer.cpp
new file mode 100644
index 0000000..f5400f9
--- /dev/null
+++ b/tests/validation/NEON/HeightConcatenateLayer.cpp
@@ -0,0 +1,131 @@
+/*
+ * Copyright (c) 2019 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 "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.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/ConcatenateLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+TEST_SUITE(NEON)
+TEST_SUITE(HeightConcatenateLayer)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+ framework::dataset::make("InputInfo1", { TensorInfo(TensorShape(23U, 15U, 5U), 1, DataType::F32), // Mismatching data type input/output
+ TensorInfo(TensorShape(22U, 27U, 5U), 1, DataType::F32), // Mismatching y dimension
+ TensorInfo(TensorShape(11U, 25U, 5U), 1, DataType::F32), // Mismatching total height
+ TensorInfo(TensorShape(16U, 25U, 5U), 1, DataType::F32)
+ }),
+ framework::dataset::make("InputInfo2", { TensorInfo(TensorShape(23U, 15U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(22U, 127U, 5U), 1, DataType::F32),
+ TensorInfo(TensorShape(11U, 26U, 5U), 1, DataType::F32),
+ TensorInfo(TensorShape(16U, 25U, 5U), 1, DataType::F32)
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(23U, 30U, 5U), 1, DataType::F16),
+ TensorInfo(TensorShape(22U, 12U, 5U), 1, DataType::F32),
+ TensorInfo(TensorShape(11U, 7U, 5U), 1, DataType::F32),
+ TensorInfo(TensorShape(16U, 50U, 5U), 1, DataType::F32)
+ })),
+ framework::dataset::make("Expected", { false, false, false, true })),
+ input_info1, input_info2, output_info,expected)
+{
+ std::vector<TensorInfo> inputs_vector_info;
+ inputs_vector_info.emplace_back(std::move(input_info1));
+ inputs_vector_info.emplace_back(std::move(input_info2));
+
+ std::vector<ITensorInfo *> inputs_vector_info_raw;
+ for(auto &input : inputs_vector_info)
+ {
+ inputs_vector_info_raw.emplace_back(&input);
+ }
+
+ bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), DataLayoutDimension::HEIGHT));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using NEHeightConcatenateLayerFixture = ConcatenateLayerValidationFixture<Tensor, ITensor, Accessor, NEConcatenateLayer, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEHeightConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+ framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("Axis", 1)))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEHeightConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::ConcatenateLayerShapes(), framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("Axis", 1)))
+
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEHeightConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+ framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ framework::dataset::make("Axis", 1)))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEHeightConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::ConcatenateLayerShapes(),
+ framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ framework::dataset::make("Axis", 1)))
+{
+ // Validate output
+ validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // QASYMM8
+TEST_SUITE_END() // Quantized
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/NEON/WidthConcatenateLayer.cpp b/tests/validation/NEON/WidthConcatenateLayer.cpp
index 6e94e92..dba14eb 100644
--- a/tests/validation/NEON/WidthConcatenateLayer.cpp
+++ b/tests/validation/NEON/WidthConcatenateLayer.cpp
@@ -22,7 +22,7 @@
* SOFTWARE.
*/
#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "tests/NEON/Accessor.h"
@@ -31,7 +31,7 @@
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "tests/validation/Validation.h"
-#include "tests/validation/fixtures/WidthConcatenateLayerFixture.h"
+#include "tests/validation/fixtures/ConcatenateLayerFixture.h"
namespace arm_compute
{
@@ -72,27 +72,30 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(NEWidthConcatenateLayer::validate(inputs_vector_info_raw,
- &output_info.clone()->set_is_resizable(false)));
+ bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw,
+ &output_info.clone()->set_is_resizable(false),DataLayoutDimension::WIDTH));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
-
template <typename T>
-using NEWidthConcatenateLayerFixture = WidthConcatenateLayerValidationFixture<Tensor, ITensor, Accessor, NEWidthConcatenateLayer, T>;
+using NEWidthConcatenateLayerFixture = ConcatenateLayerValidationFixture<Tensor, ITensor, Accessor, NEConcatenateLayer, T>;
TEST_SUITE(Float)
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEWidthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+FIXTURE_DATA_TEST_CASE(RunSmall, NEWidthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
framework::dataset::make("DataType",
- DataType::F32)))
+ DataType::F32)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(Accessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEWidthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::WidthConcatenateLayerShapes(), framework::dataset::make("DataType",
- DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunLarge, NEWidthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::ConcatenateLayerShapes(), framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(Accessor(_target), _reference);
@@ -102,15 +105,19 @@
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
+FIXTURE_DATA_TEST_CASE(RunSmall, NEWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
framework::dataset::make("DataType",
- DataType::QASYMM8)))
+ DataType::QASYMM8)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(Accessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(datasets::WidthConcatenateLayerShapes(), framework::dataset::make("DataType",
- DataType::QASYMM8)))
+FIXTURE_DATA_TEST_CASE(RunLarge, NEWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::ConcatenateLayerShapes(), framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ framework::dataset::make("Axis", 0)))
+
{
// Validate output
validate(Accessor(_target), _reference);
diff --git a/tests/validation/fixtures/WidthConcatenateLayerFixture.h b/tests/validation/fixtures/ConcatenateLayerFixture.h
similarity index 74%
rename from tests/validation/fixtures/WidthConcatenateLayerFixture.h
rename to tests/validation/fixtures/ConcatenateLayerFixture.h
index 47a03ed..db09957 100644
--- a/tests/validation/fixtures/WidthConcatenateLayerFixture.h
+++ b/tests/validation/fixtures/ConcatenateLayerFixture.h
@@ -33,7 +33,7 @@
#include "tests/framework/Asserts.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/Helpers.h"
-#include "tests/validation/reference/WidthConcatenateLayer.h"
+#include "tests/validation/reference/ConcatenateLayer.h"
#include <random>
@@ -44,11 +44,11 @@
namespace validation
{
template <typename TensorType, typename ITensorType, typename AccessorType, typename FunctionType, typename T>
-class WidthConcatenateLayerValidationFixture : public framework::Fixture
+class ConcatenateLayerValidationFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type)
+ void setup(TensorShape shape, DataType data_type, unsigned int axis)
{
// Create input shapes
std::mt19937 gen(library->seed());
@@ -78,12 +78,12 @@
{
// Decrease the dimension by a small percentage. Don't increase
// as that could make tensor too large.
- s.set(0, s[0] + 2 * static_cast<int>(s[0] * change_dis(gen)));
+ s.set(axis, s[axis] + 2 * static_cast<int>(s[axis] * change_dis(gen)));
}
}
- _target = compute_target(shapes, qinfo, data_type);
- _reference = compute_reference(shapes, qinfo, data_type);
+ _target = compute_target(shapes, qinfo, data_type, axis);
+ _reference = compute_reference(shapes, qinfo, data_type, axis);
}
protected:
@@ -93,7 +93,7 @@
library->fill_tensor_uniform(tensor, i);
}
- TensorType compute_target(std::vector<TensorShape> shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type)
+ TensorType compute_target(const std::vector<TensorShape> &shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type, unsigned int axis)
{
std::vector<TensorType> srcs;
std::vector<ITensorType *> src_ptrs;
@@ -107,13 +107,26 @@
src_ptrs.emplace_back(&srcs.back());
}
- TensorShape dst_shape = misc::shape_calculator::calculate_width_concatenate_shape(src_ptrs);
-
- TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, qinfo[shapes.size()]);
+ const TensorShape dst_shape = misc::shape_calculator::calculate_concatenate_shape(src_ptrs, axis);
+ TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, qinfo[shapes.size()]);
// Create and configure function
- FunctionType width_concat;
- width_concat.configure(src_ptrs, &dst);
+ FunctionType concat;
+ switch(axis)
+ {
+ case 0:
+ concat.configure(src_ptrs, &dst, DataLayoutDimension::WIDTH);
+ break;
+ case 1:
+ concat.configure(src_ptrs, &dst, DataLayoutDimension::HEIGHT);
+ break;
+ case 2:
+ concat.configure(src_ptrs, &dst, DataLayoutDimension::CHANNEL);
+ break;
+ default:
+ ARM_COMPUTE_ERROR("Not supported");
+ break;
+ }
for(auto &src : srcs)
{
@@ -140,12 +153,12 @@
}
// Compute function
- width_concat.run();
+ concat.run();
return dst;
}
- SimpleTensor<T> compute_reference(std::vector<TensorShape> shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type)
+ SimpleTensor<T> compute_reference(const std::vector<TensorShape> &shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type, unsigned int axis)
{
std::vector<SimpleTensor<T>> srcs;
@@ -156,10 +169,9 @@
fill(srcs.back(), j);
}
- const TensorShape dst_shape = calculate_width_concatenate_shape(shapes);
+ const TensorShape dst_shape = calculate_concatenate_shape(shapes, axis);
SimpleTensor<T> dst{ dst_shape, data_type, 1, qinfo[shapes.size()] };
-
- return reference::widthconcatenate_layer<T>(srcs, dst);
+ return reference::concatenate_layer<T>(srcs, dst, axis);
}
TensorType _target{};
diff --git a/tests/validation/fixtures/LSTMLayerFixture.h b/tests/validation/fixtures/LSTMLayerFixture.h
index b30f1e5..2cf83b8 100644
--- a/tests/validation/fixtures/LSTMLayerFixture.h
+++ b/tests/validation/fixtures/LSTMLayerFixture.h
@@ -29,11 +29,11 @@
#include "tests/framework/Fixture.h"
#include "tests/validation/reference/ActivationLayer.h"
#include "tests/validation/reference/ArithmeticOperations.h"
+#include "tests/validation/reference/ConcatenateLayer.h"
#include "tests/validation/reference/FullyConnectedLayer.h"
#include "tests/validation/reference/GEMM.h"
#include "tests/validation/reference/PixelWiseMultiplication.h"
#include "tests/validation/reference/Transpose.h"
-#include "tests/validation/reference/WidthConcatenateLayer.h"
namespace arm_compute
{
@@ -415,7 +415,7 @@
scratch_inputs.emplace_back(std::move(cell_state_out));
scratch_inputs.emplace_back(std::move(forget_gate));
scratch_inputs.emplace_back(std::move(output));
- scratch = reference::widthconcatenate_layer(scratch_inputs, scratch);
+ scratch = reference::concatenate_layer(scratch_inputs, scratch, Window::DimX);
_reference_scratch = std::move(scratch);
return output_state_out;
}
diff --git a/tests/validation/reference/WidthConcatenateLayer.cpp b/tests/validation/reference/ConcatenateLayer.cpp
similarity index 74%
rename from tests/validation/reference/WidthConcatenateLayer.cpp
rename to tests/validation/reference/ConcatenateLayer.cpp
index 3854339..1440878 100644
--- a/tests/validation/reference/WidthConcatenateLayer.cpp
+++ b/tests/validation/reference/ConcatenateLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -21,9 +21,10 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#include "WidthConcatenateLayer.h"
+#include "ConcatenateLayer.h"
#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/Permute.h"
namespace arm_compute
{
@@ -33,24 +34,22 @@
{
namespace reference
{
+namespace
+{
template <typename T>
SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst)
{
// Create reference
std::vector<TensorShape> shapes;
-
for(const auto &src : srcs)
{
shapes.emplace_back(src.shape());
}
-
// Compute reference
int width_offset = 0;
const int width_out = dst.shape().x();
-
// Set output tensor to 0
std::fill_n(dst.data(), dst.num_elements(), 0);
-
for(const auto &src : srcs)
{
ARM_COMPUTE_ERROR_ON(width_offset >= width_out);
@@ -89,13 +88,43 @@
}
width_offset += width;
}
-
return dst;
}
template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst);
template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst);
template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst);
+} // namespace
+
+template <typename T>
+SimpleTensor<T> concatenate_layer(std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst, unsigned int axis)
+{
+ switch(axis)
+ {
+ case Window::DimX:
+ {
+ return widthconcatenate_layer(srcs, dst);
+ }
+ case Window::DimY:
+ {
+ for(auto &t : srcs)
+ {
+ t = reference::permute<T>(t, PermutationVector(1U, 0U));
+ }
+ dst = reference::permute<T>(dst, PermutationVector(1U, 0U));
+ return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(1U, 0U));
+ }
+ default:
+ {
+ ARM_COMPUTE_ERROR("Not supported");
+ return dst;
+ }
+ }
+}
+
+template SimpleTensor<float> concatenate_layer(std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst, unsigned int axis);
+template SimpleTensor<half> concatenate_layer(std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst, unsigned int axis);
+template SimpleTensor<uint8_t> concatenate_layer(std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst, unsigned int axis);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/WidthConcatenateLayer.h b/tests/validation/reference/ConcatenateLayer.h
similarity index 81%
rename from tests/validation/reference/WidthConcatenateLayer.h
rename to tests/validation/reference/ConcatenateLayer.h
index 0f1f428..14fd097 100644
--- a/tests/validation/reference/WidthConcatenateLayer.h
+++ b/tests/validation/reference/ConcatenateLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -21,8 +21,8 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#ifndef __ARM_COMPUTE_TEST_WIDTHCONCATENATE_LAYER_H__
-#define __ARM_COMPUTE_TEST_WIDTHCONCATENATE_LAYER_H__
+#ifndef __ARM_COMPUTE_TEST_CONCATENATE_LAYER_H__
+#define __ARM_COMPUTE_TEST_CONCATENATE_LAYER_H__
#include "tests/SimpleTensor.h"
@@ -37,9 +37,9 @@
namespace reference
{
template <typename T>
-SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst);
+SimpleTensor<T> concatenate_layer(std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst, unsigned int axis);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_WIDTHCONCATENATE_LAYER_H__ */
+#endif /* __ARM_COMPUTE_TEST_CONCATENATE_LAYER_H__ */