diff options
Diffstat (limited to 'src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp | 33 |
1 files changed, 31 insertions, 2 deletions
diff --git a/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp b/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp index 43292d1b22..3a102edd10 100644 --- a/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp +++ b/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp @@ -30,6 +30,7 @@ #include "arm_compute/core/ITensor.h" #include "arm_compute/core/NEON/NEFixedPoint.h" #include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include <algorithm> @@ -952,13 +953,15 @@ BorderSize NEDirectConvolutionLayerKernel::border_size() const void NEDirectConvolutionLayerKernel::configure(const ITensor *input, const ITensor *weights, ITensor *output, const PadStrideInfo &conv_info) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::F16, DataType::QS16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QS8, DataType::F16, DataType::QS16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QS16, DataType::F16, DataType::QS32, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) == 1 && (std::get<0>(conv_info.pad()) || std::get<1>(conv_info.pad())), "Pad > 0 not supported for 1x1 weights"); ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) == 3 && (std::get<0>(conv_info.pad()) > 1 || std::get<1>(conv_info.pad()) > 1), "Pad > 1 not supported for 3x3 weights"); ARM_COMPUTE_ERROR_ON_MSG(std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported."); + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(2) != input->info()->dimension(2)); + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != weights->info()->dimension(1)); + ARM_COMPUTE_ERROR_ON(weights->info()->num_dimensions() > 4); const unsigned int conv_stride_x = std::get<0>(conv_info.stride()); const unsigned int conv_pad_x = std::get<0>(conv_info.pad()); @@ -971,6 +974,32 @@ void NEDirectConvolutionLayerKernel::configure(const ITensor *input, const ITens _kernel_size = weights->info()->dimension(0); _border_size = BorderSize(conv_pad_y, conv_pad_x); + const unsigned int kernel_size = weights->info()->dimension(0); + + // Get convolved dimensions + unsigned int output_width = 0; + unsigned int output_height = 0; + std::tie(output_width, output_height) = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1), kernel_size, kernel_size, conv_info); + + TensorShape output_shape = input->info()->tensor_shape(); + output_shape.set(0, output_width); + output_shape.set(1, output_height); + output_shape.set(2, weights->info()->dimension(3)); + + DataType data_type = input->info()->data_type(); + + if(is_data_type_fixed_point(data_type)) + { + // Promote data type in case of fixed point + data_type = ((data_type == DataType::QS8) ? DataType::QS16 : DataType::QS32); + } + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, data_type, input->info()->fixed_point_position()); + + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, output->info()->data_type()); + Window win = calculate_max_window(*output->info()); switch(_kernel_size) |