diff options
| -rw-r--r-- | arm_compute/core/utils/misc/ShapeCalculator.h | 2 | ||||
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEBatchToSpaceLayer.h | 15 | ||||
| -rw-r--r-- | docs/user_guide/release_version_and_change_log.dox | 3 | ||||
| -rw-r--r-- | src/core/NEON/kernels/NEBatchToSpaceLayerKernel.cpp | 92 | ||||
| -rw-r--r-- | src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h | 19 | ||||
| -rw-r--r-- | src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp | 12 | ||||
| -rw-r--r-- | tests/validation/NEON/BatchToSpaceLayer.cpp | 86 |
7 files changed, 120 insertions, 109 deletions
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h index 916da1bd9d..9b1ebf63c2 100644 --- a/arm_compute/core/utils/misc/ShapeCalculator.h +++ b/arm_compute/core/utils/misc/ShapeCalculator.h @@ -1201,7 +1201,7 @@ inline TensorShape compute_split_shape(const ITensorInfo *input, unsigned int ax * * @return the calculated shape */ -inline TensorShape compute_space_to_batch_shape(const ITensorInfo *input, const int block_x, const int block_y, const Size2D &padding_left, const Size2D &padding_right) +inline TensorShape compute_space_to_batch_shape(const ITensorInfo *input, int block_x, int block_y, const Size2D &padding_left, const Size2D &padding_right) { TensorShape output_shape{ input->tensor_shape() }; diff --git a/arm_compute/runtime/NEON/functions/NEBatchToSpaceLayer.h b/arm_compute/runtime/NEON/functions/NEBatchToSpaceLayer.h index 92df8913ab..b33ba435a8 100644 --- a/arm_compute/runtime/NEON/functions/NEBatchToSpaceLayer.h +++ b/arm_compute/runtime/NEON/functions/NEBatchToSpaceLayer.h @@ -64,16 +64,18 @@ public: * @param[in] input Tensor input. Supported tensor rank: 4. Data types supported: All. * @param[in] block_shape 1-D tensor with shape [M]. Data types supported: S32 * @param[out] output Tensor output. Data types supported: same as @p input - * @param[in] crop_info Information about how the output shape is cropped after batch to space is performed + * + * @deprecated This method for dynamic block shape is not fully mature and will be removed in 23.08 release */ - void configure(const ITensor *input, const ITensor *block_shape, ITensor *output, const CropInfo &crop_info = CropInfo{}); + ARM_COMPUTE_DEPRECATED_REL(23.05) + void configure(const ITensor *input, const ITensor *block_shape, ITensor *output); /** Set the input and output tensors. (Static block shape). * * @param[in] input Tensor input. Supported tensor rank: 4. Data types supported: All. * @param[in] block_shape_x Block shape x value. * @param[in] block_shape_y Block shape y value. * @param[out] output Tensor output. Data types supported: same as @p input - * @param[in] crop_info Information about how the output shape is cropped after batch to space is performed + * @param[in] crop_info Specifies how the output shape is cropped after batch to space is performed */ void configure(const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info = CropInfo{}); /** Static function to check if given info will lead to a valid configuration of @ref CLBatchToSpaceLayer @@ -81,18 +83,19 @@ public: * @param[in] input Tensor input info. Supported tensor rank: 4. Data types supported: All. * @param[in] block_shape block shape tensor info with shape [M]. Data types supported: S32 * @param[out] output Tensor output info. Data types supported: same as @p input - * @param[in] crop_info Information about how the output shape is cropped after batch to space is performed * * @return a status + * @deprecated This method for dynamic block shape is not fully mature and will be removed in 23.08 release */ - static Status validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output, const CropInfo &crop_info = CropInfo{}); + ARM_COMPUTE_DEPRECATED_REL(23.05) + static Status validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output); /** Static function to check if given info will lead to a valid configuration of @ref CLBatchToSpaceLayer (Static block shape). * * @param[in] input Tensor input info. Supported tensor rank: 4. Data types supported: All. * @param[in] block_shape_x Block shape x value. * @param[in] block_shape_y Block shape y value. * @param[out] output Tensor output info. Data types supported: same as @p input - * @param[in] crop_info Information about how the output shape is cropped after batch to space is performed + * @param[in] crop_info Specifies how the output shape is cropped after batch to space is performed * * @return a status */ diff --git a/docs/user_guide/release_version_and_change_log.dox b/docs/user_guide/release_version_and_change_log.dox index 1bfb468ef1..aa9061f2b8 100644 --- a/docs/user_guide/release_version_and_change_log.dox +++ b/docs/user_guide/release_version_and_change_log.dox @@ -40,6 +40,9 @@ If there is more than one release in a month then an extra sequential number is @note Starting from release 22.05, 'master' branch is no longer being used, it has been replaced by 'main'. Please update your clone jobs accordingly. @section S2_2_changelog Changelog +v23.05 Public major release + - Deprecate dynamic block shape in @ref NEBatchToSpaceLayer + v23.02.1 Public patch release - Allow mismatching data layouts between the source tensor and weights for \link cpu::CpuGemmDirectConv2d CpuGemmDirectConv2d \endlink with fixed format kernels. - Fixes for experimental CPU only Bazel and CMake builds. diff --git a/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.cpp b/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.cpp index 84c727df73..83fb5f6f51 100644 --- a/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.cpp +++ b/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.cpp @@ -25,6 +25,7 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" +#include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" @@ -53,7 +54,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_inf return Status{}; } -Status validate_arguments_static(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const ITensorInfo *output) +Status validate_arguments_static(const ITensorInfo *input, int block_shape_x, int block_shape_y, const ITensorInfo *output, const CropInfo &crop_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); @@ -66,14 +67,12 @@ Status validate_arguments_static(const ITensorInfo *input, const int block_shape // Validate output if initialized if(output->total_size() != 0) { - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); - ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] != (block_shape_x * input->tensor_shape()[idx_width])); - ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_height] != (block_shape_y * input->tensor_shape()[idx_height])); - ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_channel] != input->tensor_shape()[idx_channel]); ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + + const TensorShape expected_output_shape = compute_batch_to_space_shape(input->data_layout(), input->tensor_shape(), block_shape_x, block_shape_y, crop_info); + const TensorInfo expected_output = output->clone()->set_tensor_shape(expected_output_shape); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &expected_output); } return Status{}; @@ -81,7 +80,7 @@ Status validate_arguments_static(const ITensorInfo *input, const int block_shape } // namespace NEBatchToSpaceLayerKernel::NEBatchToSpaceLayerKernel() - : _input(nullptr), _block_shape(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _block_shape_x(), _block_shape_y() + : _input(nullptr), _block_shape(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _block_shape_x(), _block_shape_y(), _crop_info() { } @@ -96,28 +95,29 @@ void NEBatchToSpaceLayerKernel::configure(const ITensor *input, const ITensor *b _data_layout = input->info()->data_layout(); // Configure kernel window - Window win = calculate_max_window(*input->info(), Steps()); + Window win = calculate_max_window(*output->info(), Steps()); ICPPKernel::configure(win); } -void NEBatchToSpaceLayerKernel::configure(const ITensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ITensor *output) +void NEBatchToSpaceLayerKernel::configure(const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); const TensorShape output_shape = compute_batch_to_space_shape(input->info()->data_layout(), input->info()->tensor_shape(), block_shape_x, block_shape_y); - // Output auto inizialitation if not yet initialized + // Output auto initialization if not yet initialized auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, output->info())); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, output->info(), crop_info)); _input = input; _output = output; _block_shape_x = block_shape_x; _block_shape_y = block_shape_y; _data_layout = input->info()->data_layout(); + _crop_info = crop_info; // Configure kernel window - Window win = calculate_max_window(*input->info(), Steps()); + Window win = calculate_max_window(*output->info(), Steps()); ICPPKernel::configure(win); } @@ -128,10 +128,10 @@ Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input, const ITens return Status{}; } -Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input, const int32_t block_shape_x, const int32_t block_shape_y, const ITensorInfo *output) +Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input, int32_t block_shape_x, int32_t block_shape_y, const ITensorInfo *output, const CropInfo &crop_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output, crop_info)); return Status{}; } @@ -148,18 +148,10 @@ void NEBatchToSpaceLayerKernel::run(const Window &window, const ThreadInfo &info _block_shape_y = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(1))); } - const int batch_size = _input->info()->dimension(3); - const int r = (batch_size / (_block_shape_x * _block_shape_y)); - const int element_size = _input->info()->element_size(); - - Window slice_in = window.first_slice_window_3D(); - Window slice_out = window.first_slice_window_4D(); + const int batch_size = _output->info()->dimension(3); + const int element_size = _output->info()->element_size(); - // The slice_out slice does not move - slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); - slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); - slice_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); - slice_out.set(3, Window::Dimension(0, 0, 0)); + Window slice_out = window.first_slice_window_3D(); int batch_id = 0; // Main loop for NCHW and NHWC @@ -167,47 +159,55 @@ void NEBatchToSpaceLayerKernel::run(const Window &window, const ThreadInfo &info { do { - Iterator in(_input, slice_in); - execute_window_loop(slice_in, [&](const Coordinates & id) + Iterator out(_output, slice_out); + execute_window_loop(slice_out, [&](const Coordinates & id) { const int x = id.x(); const int y = id.y(); const int z = id.z(); - - const int w = batch_id % r; - const int out_x = x * _block_shape_x + (batch_id / r) % _block_shape_x; - const int out_y = y * _block_shape_y + (batch_id / r) / _block_shape_x; - Coordinates output_coords{ out_x, out_y, z, w }; - memcpy(_output->ptr_to_element(output_coords), in.ptr(), element_size); + // Translate x, y to uncropped version + const int x_c = x + _crop_info.left; + const int y_c = y + _crop_info.top; + + const int in_batch = batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size; + const int in_x = x_c / _block_shape_x; + const int in_y = y_c / _block_shape_y; + Coordinates input_coords{ in_x, in_y, z, in_batch }; + memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); }, - in); + out); ++batch_id; } - while(window.slide_window_slice_3D(slice_in)); + while(window.slide_window_slice_3D(slice_out)); } else { + // For NHWC we can perform a block copy on the Channel (first) dimension. Thus we do not need to iterate over this dimension + slice_out.set(0U, Window::Dimension(0U, 1U, 1U)); do { - Iterator in(_input, slice_in); - execute_window_loop(slice_in, [&](const Coordinates & id) + Iterator out(_output, slice_out); + execute_window_loop(slice_out, [&](const Coordinates & id) { - const int z = id.x(); const int x = id.y(); const int y = id.z(); - const int w = batch_id % r; - const int out_x = x * _block_shape_x + (batch_id / r) % _block_shape_x; - const int out_y = y * _block_shape_y + (batch_id / r) / _block_shape_x; - Coordinates output_coords{ z, out_x, out_y, w }; - memcpy(_output->ptr_to_element(output_coords), in.ptr(), element_size); + // Translate x, y to uncropped version + const int x_c = x + _crop_info.left; + const int y_c = y + _crop_info.top; + + const int in_batch = batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size; + const int in_x = x_c / _block_shape_x; + const int in_y = y_c / _block_shape_y; + Coordinates input_coords{ 0, in_x, in_y, in_batch }; + memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size * _input->info()->dimension(0)); }, - in); + out); ++batch_id; } - while(window.slide_window_slice_3D(slice_in)); + while(window.slide_window_slice_3D(slice_out)); } } } // namespace arm_compute diff --git a/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h b/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h index 26e8224922..5eceee0904 100644 --- a/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h +++ b/src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2020, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -24,6 +24,7 @@ #ifndef ARM_COMPUTE_NEBATCHTOSPACELAYERKERNEL_H #define ARM_COMPUTE_NEBATCHTOSPACELAYERKERNEL_H +#include "arm_compute/core/Types.h" #include "src/core/NEON/INEKernel.h" namespace arm_compute @@ -55,6 +56,8 @@ public: * @param[in] input Tensor input. Supported tensor rank: 4. Data types supported: All. * @param[in] block_shape 1-D tensor with shape [M]. Data types supported: S32 * @param[out] output Tensor output. Data types supported: same as @p input + * + * @deprecated This method for dynamic block shape is not fully mature and will be removed in 23.08 release */ void configure(const ITensor *input, const ITensor *block_shape, ITensor *output); /** Initialise the kernel's inputs and output (Static block shape). @@ -63,8 +66,9 @@ public: * @param[in] block_shape_x Block shape x value. * @param[in] block_shape_y Block shape y value. * @param[out] output Tensor output. Data types supported: same as @p input + * @param[in] crop_info Specifies how the output shape is cropped after batch to space is performed */ - void configure(const ITensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ITensor *output); + void configure(const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info = CropInfo{}); /** Static function to check if given info will lead to a valid configuration of @ref NEBatchToSpaceLayerKernel * * @param[in] input Tensor input. Supported tensor rank: 4. Data types supported: All. @@ -72,6 +76,8 @@ public: * @param[in] output Tensor output. Data types supported: same as @p input * * @return a status + * + * @deprecated This method for dynamic block shape is not fully mature and will be removed in 23.08 release */ static Status validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output); /** Static function to check if given info will lead to a valid configuration of @ref NEBatchToSpaceLayerKernel (Static block shape). @@ -80,10 +86,11 @@ public: * @param[in] block_shape_x Block shape x value. * @param[in] block_shape_y Block shape y value. * @param[in] output Tensor output. Data types supported: same as @p input + * @param[in] crop_info Specifies how the output shape is cropped after batch to space is performed * * @return a status */ - static Status validate(const ITensorInfo *input, const int32_t block_shape_x, const int32_t block_shape_y, const ITensorInfo *output); + static Status validate(const ITensorInfo *input, int32_t block_shape_x, int32_t block_shape_y, const ITensorInfo *output, const CropInfo &crop_info = CropInfo{}); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; @@ -93,9 +100,9 @@ private: const ITensor *_block_shape; /**< Block shape tensor */ ITensor *_output; /**< Destination tensor */ DataLayout _data_layout; /**< Data layout to be used at run-time */ - - int32_t _block_shape_x; - int32_t _block_shape_y; + int32_t _block_shape_x; + int32_t _block_shape_y; + CropInfo _crop_info; /**< Information related to cropping performed on output after the operation */ }; } // namespace arm_compute #endif /* ARM_COMPUTE_NEBATCHTOSPACELAYERKERNEL_H */ diff --git a/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp b/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp index b62fdad7a1..e258028d05 100644 --- a/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp +++ b/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp @@ -33,9 +33,8 @@ namespace arm_compute { -void NEBatchToSpaceLayer::configure(const ITensor *input, const ITensor *block_shape, ITensor *output, const CropInfo &crop_info) +void NEBatchToSpaceLayer::configure(const ITensor *input, const ITensor *block_shape, ITensor *output) { - ARM_COMPUTE_UNUSED(crop_info); ARM_COMPUTE_LOG_PARAMS(input, block_shape, output); auto k = std::make_unique<NEBatchToSpaceLayerKernel>(); k->configure(input, block_shape, output); @@ -44,21 +43,18 @@ void NEBatchToSpaceLayer::configure(const ITensor *input, const ITensor *block_s void NEBatchToSpaceLayer::configure(const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info) { - ARM_COMPUTE_UNUSED(crop_info); auto k = std::make_unique<NEBatchToSpaceLayerKernel>(); - k->configure(input, block_shape_x, block_shape_y, output); + k->configure(input, block_shape_x, block_shape_y, output, crop_info); _kernel = std::move(k); } -Status NEBatchToSpaceLayer::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output, const CropInfo &crop_info) +Status NEBatchToSpaceLayer::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output) { - ARM_COMPUTE_UNUSED(crop_info); return NEBatchToSpaceLayerKernel::validate(input, block_shape, output); } Status NEBatchToSpaceLayer::validate(const ITensorInfo *input, int32_t block_shape_x, int32_t block_shape_y, const ITensorInfo *output, const CropInfo &crop_info) { - ARM_COMPUTE_UNUSED(crop_info); - return NEBatchToSpaceLayerKernel::validate(input, block_shape_x, block_shape_y, output); + return NEBatchToSpaceLayerKernel::validate(input, block_shape_x, block_shape_y, output, crop_info); } } // namespace arm_compute diff --git a/tests/validation/NEON/BatchToSpaceLayer.cpp b/tests/validation/NEON/BatchToSpaceLayer.cpp index a305dcbcc4..8cf11b7b95 100644 --- a/tests/validation/NEON/BatchToSpaceLayer.cpp +++ b/tests/validation/NEON/BatchToSpaceLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021 Arm Limited. + * Copyright (c) 2019-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -49,55 +49,38 @@ using NEBatchToSpaceLayerFixture = BatchToSpaceLayerValidationFixture<Tensor, Ac // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blockx > blocky - TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blocky > blockx - TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Mismatching data types - TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Wrong data type block shape - TensorInfo(TensorShape(32U, 13U, 2U, 2U, 4U), 1, DataType::F32), // Wrong tensor shape - }), - framework::dataset::make("BlockShapeInfo",{ TensorInfo(TensorShape(2U, 2U), 1, DataType::S32), - TensorInfo(TensorShape(2U, 2U), 1, DataType::S32), - TensorInfo(TensorShape(2U, 4U), 1, DataType::S32), - TensorInfo(TensorShape(4U, 2U), 1, DataType::S32), - TensorInfo(TensorShape(2U, 2U), 1, DataType::F16), - TensorInfo(TensorShape(2U, 2U), 1, DataType::S32), - })), - framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(64U, 16U, 2U, 1U), 1, DataType::F32), - TensorInfo(TensorShape(32U, 32U, 2U, 1U), 1, DataType::F32), - TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F16), - TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), - })), - framework::dataset::make("Expected", { true, true, true, false, false, false})), - input_info, block_shape_info, output_info, expected) -{ - bool has_error = bool(NEBatchToSpaceLayer::validate(&input_info.clone()->set_is_resizable(false), &block_shape_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))); - ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS); -} -DATA_TEST_CASE(ValidateStatic, framework::DatasetMode::ALL, zip(zip(zip(zip( +DATA_TEST_CASE(ValidateStatic, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), - TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blockx > blocky - TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // blockx != blocky && blocky > blockx - TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Mismatching data types - TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Negative block shapes - TensorInfo(TensorShape(32U, 16U, 2U, 4U, 4U), 1, DataType::F32), // Wrong tensor shape + TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Supported: blockx != blocky && blockx > blocky + TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Supported: blockx != blocky && blocky > blockx + TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Invalid: Mismatching data types + TensorInfo(TensorShape(16U, 8U, 2U, 4U), 1, DataType::F32), // Invalid: Negative block shapes + TensorInfo(TensorShape(32U, 16U, 2U, 4U, 4U), 1, DataType::F32),// Unsupported tensor rank + TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Invalid output tensor shape (invalid batch dimension) + TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Invalid output tensor shape (invalid spatial dimension) + TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Supported: correct tensor shape with cropping + TensorInfo(TensorShape(16U, 8U, 2U, 16U), 1, DataType::F32), // Invalid tensor shape with cropping }), - framework::dataset::make("BlockShapeX", { 2, 4, 2, 2, 2, 2 })), - framework::dataset::make("BlockShapeY", { 2, 2, 4, 2, -2, 2 })), + framework::dataset::make("BlockShapeX", { 2, 4, 2, 2, 2, 2, 2, 2, 2, 2 })), + framework::dataset::make("BlockShapeY", { 2, 2, 4, 2, -2, 2, 2, 2, 2, 2 })), + framework::dataset::make("CropInfo", { + CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{}, CropInfo{3, 2, 1, 3}, CropInfo{3, 2, 1, 3} + })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F32), - TensorInfo(TensorShape(64U, 16U, 2U, 1U), 1, DataType::F32), - TensorInfo(TensorShape(32U, 32U, 2U, 1U), 1, DataType::F32), + TensorInfo(TensorShape(64U, 16U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 32U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F16), TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F32), TensorInfo(TensorShape(32U, 8U, 2U, 1U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 16U, 2U, 1U), 1, DataType::F32), + TensorInfo(TensorShape(33U, 32U, 2U, 4U), 1, DataType::F32), + TensorInfo(TensorShape(27, 12U, 2U, 4U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 16U, 2U, 4U), 1, DataType::F32), })), - framework::dataset::make("Expected", { true, true, true, false, false, false})), - input_info, block_shape_x, block_shape_y, output_info, expected) + framework::dataset::make("Expected", { true, true, true, false, false, false, false, false, true, false})), + input_info, block_shape_x, block_shape_y, crop_info, output_info, expected) { - bool has_error = bool(NEBatchToSpaceLayer::validate(&input_info.clone()->set_is_resizable(false), block_shape_x, block_shape_y, &output_info.clone()->set_is_resizable(false))); + bool has_error = bool(NEBatchToSpaceLayer::validate(&input_info.clone()->set_is_resizable(false), block_shape_x, block_shape_y, &output_info.clone()->set_is_resizable(false), crop_info)); ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS); } // clang-format on @@ -112,6 +95,16 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchToSpaceLayerFixture<float>, framework::D // Validate output validate(Accessor(_target), _reference); } + +FIXTURE_DATA_TEST_CASE(RunSmallWithCropping, NEBatchToSpaceLayerFixture<float>, framework::DatasetMode::PRECOMMIT, + combine(combine(datasets::SmallBatchToSpaceLayerWithCroppingDataset(), framework::dataset::make("DataType", + DataType::F32)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} + FIXTURE_DATA_TEST_CASE(RunLarge, NEBatchToSpaceLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeBatchToSpaceLayerDataset(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) @@ -129,6 +122,15 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchToSpaceLayerFixture<half>, framework::Da // Validate output validate(Accessor(_target), _reference); } +FIXTURE_DATA_TEST_CASE(RunSmallWithCropping, NEBatchToSpaceLayerFixture<half>, framework::DatasetMode::PRECOMMIT, + combine(combine(datasets::SmallBatchToSpaceLayerWithCroppingDataset(), framework::dataset::make("DataType", + DataType::F16)), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} + FIXTURE_DATA_TEST_CASE(RunLarge, NEBatchToSpaceLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeBatchToSpaceLayerDataset(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |