diff options
Diffstat (limited to 'src/runtime/NEON/functions/NEWinogradLayer.cpp')
| -rw-r--r-- | src/runtime/NEON/functions/NEWinogradLayer.cpp | 54 |
1 files changed, 40 insertions, 14 deletions
diff --git a/src/runtime/NEON/functions/NEWinogradLayer.cpp b/src/runtime/NEON/functions/NEWinogradLayer.cpp index e343583b36..0ac6d0966d 100644 --- a/src/runtime/NEON/functions/NEWinogradLayer.cpp +++ b/src/runtime/NEON/functions/NEWinogradLayer.cpp @@ -23,6 +23,7 @@ */ #include "arm_compute/runtime/NEON/functions/NEWinogradLayer.h" +#include "arm_compute/core/Error.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/NEON/NEScheduler.h" @@ -46,6 +47,33 @@ inline Tensor4DShape internal_get_input_shape(const arm_compute::ITensor *input) namespace arm_compute { +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, biases); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(0) != 3 && weights->dimension(0) != 5, "Only 3 and 5 kernels are supported"); + ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 4); + + if(biases != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases); + ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); + } + + // Get parameters from conv_info + unsigned int stride_x = 0; + unsigned int stride_y = 0; + std::tie(stride_x, stride_y) = conv_info.stride(); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(stride_y != 1 || stride_x != 1, "Winograd layer only supports unit strides."); + + ARM_COMPUTE_UNUSED(output); + + return Status{}; +} +} //namespace + NEWinogradLayer::NEWinogradLayer(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _batched_gemm_kernel(nullptr), _transform_input_kernel(nullptr), _transform_output_kernel(nullptr), _transform_weights_kernel(nullptr), _permute_input(), _permute_weights(), _permute_output(), _input_workspace(), _output_workspace(), _kernel_storage(), _input_nhwc(), _output_nhwc(), _weights_hwio(), _input(), _weights(), _output(), @@ -55,16 +83,9 @@ NEWinogradLayer::NEWinogradLayer(std::shared_ptr<IMemoryManager> memory_manager) void NEWinogradLayer::configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, biases); - ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) != 3 && weights->info()->dimension(0) != 5, "Only 3 and 5 kernels are supported"); - ARM_COMPUTE_ERROR_ON(weights->info()->num_dimensions() > 4); - - if(biases != nullptr) - { - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases); - ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1); - } + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, biases, output); + ARM_COMPUTE_UNUSED(conv_info); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), biases->info(), output->info(), conv_info)); _weights = weights; _input = input; @@ -119,19 +140,15 @@ void NEWinogradLayer::configure(const ITensor *input, const ITensor *weights, co constexpr size_t storage_alignment = 64; const size_t kernel_storage_size = transform_weights_kernel->get_weight_storage_size(out_channels, in_channels) * data_type_size; _kernel_storage.allocator()->init(TensorInfo(TensorShape{ (kernel_storage_size + storage_alignment - 1) }, 1, DataType::U8)); - _memory_group.manage(&_kernel_storage); - _memory_group.manage(&_input_nhwc); _kernel_storage.allocator()->allocate(); // Input storage const size_t input_storage_size = transform_input_kernel->get_input_storage_size(in_shape.n_batches, in_shape.n_channels, in_shape.n_rows, in_shape.n_cols, use_same_padding) * data_type_size; _input_workspace.allocator()->init(TensorInfo(TensorShape{ (input_storage_size + storage_alignment - 1) }, 1, DataType::U8)); - _memory_group.manage(&_input_workspace); _input_workspace.allocator()->allocate(); // Output storage const size_t output_storage_size = transform_output_kernel->get_output_storage_size(in_shape.n_batches, in_shape.n_rows, in_shape.n_cols, out_channels, use_same_padding) * data_type_size; _output_workspace.allocator()->init(TensorInfo(TensorShape{ (output_storage_size + storage_alignment - 1) }, 1, DataType::U8)); - _memory_group.manage(&_output_workspace); _output_workspace.allocator()->allocate(); // configure and allocate dst tensor to be used to convert from winograd domain to spatial domain when calling to reshape_output() @@ -227,4 +244,13 @@ void NEWinogradLayer::run() _permute_output.run(); _memory_group.release(); } + +Status NEWinogradLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, biases, output); + ARM_COMPUTE_RETURN_ERROR_ON(validate_arguments(input, weights, biases, output, conv_info)); + + return Status{}; +} + } // namespace arm_compute |