diff options
author | Usama Arif <usama.arif@arm.com> | 2019-04-12 10:29:17 +0100 |
---|---|---|
committer | Pablo Marquez <pablo.tello@arm.com> | 2019-04-24 12:31:21 +0000 |
commit | 881f2ded860fc1db23810076b699c4492556c376 (patch) | |
tree | 6237444ceaf2d5098e0b546693b8c18955963012 /src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp | |
parent | 557d4aece64b2ed422ec853dbc2b7a4949ea56ca (diff) | |
download | ComputeLibrary-881f2ded860fc1db23810076b699c4492556c376.tar.gz |
COMPMID-2048: Add support for dilation in NEDepthwiseConvolution.
Change-Id: If9941e770779fbf918ba5ff0573da9378078b969
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/999
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Diffstat (limited to 'src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp')
-rw-r--r-- | src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp | 55 |
1 files changed, 37 insertions, 18 deletions
diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp index 4c602b3640..5133756993 100644 --- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp @@ -51,7 +51,8 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor ITensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, - const ActivationLayerInfo &act_info) + const ActivationLayerInfo &act_info, + const Size2D &dilation) { ARM_COMPUTE_UNUSED(act_info); @@ -87,8 +88,8 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor _permute_weights.configure(weights, &_permuted_weights, PermutationVector(1U, 2U, 0U)); _permuted_weights.info()->set_data_layout(DataLayout::NCHW); - // Configure optimized depthwise - _dwc_kernel.configure(&_permuted_input, &_permuted_weights, (_is_quantized) ? &_accumulator : &_permuted_output, conv_info, depth_multiplier); + // Configure depthwise + _dwc_kernel.configure(&_permuted_input, &_permuted_weights, (_is_quantized) ? &_accumulator : &_permuted_output, conv_info, depth_multiplier, dilation); // Configure border handler _border_handler.configure(&_permuted_input, _dwc_kernel.border_size(), BorderMode::CONSTANT, zero_value); @@ -99,7 +100,7 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor else { // Configure depthwise convolution kernel - _dwc_kernel.configure(input, weights, (_is_quantized) ? &_accumulator : output, conv_info, depth_multiplier); + _dwc_kernel.configure(input, weights, (_is_quantized) ? &_accumulator : output, conv_info, depth_multiplier, dilation); // Configure border handler _border_handler.configure(input, _dwc_kernel.border_size(), BorderMode::CONSTANT, zero_value); @@ -185,18 +186,25 @@ void NEDepthwiseConvolutionLayer3x3::configure(ITensor *input, const ActivationLayerInfo &act_info, const Size2D &dilation) { - ARM_COMPUTE_ERROR_ON(dilation.x() != 1 || dilation.y() != 1); - ARM_COMPUTE_UNUSED(dilation); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + // idx_w and idx_h only used for validation + const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH); + const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); + ARM_COMPUTE_UNUSED(idx_w); + ARM_COMPUTE_UNUSED(idx_h); + + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_w) + (weights->info()->dimension(idx_w) - 1) * (dilation.x() - 1) > input->info()->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_h) + (weights->info()->dimension(idx_h) - 1) * (dilation.y() - 1) > input->info()->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); + _original_weights = weights; _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); _has_bias = biases != nullptr; _is_optimized = NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input->info(), weights->info(), conv_info, - depth_multiplier); + depth_multiplier, dilation); _is_nchw = input->info()->data_layout() == DataLayout::NCHW; _permute = _is_optimized == _is_nchw; _is_prepared = false; @@ -209,7 +217,7 @@ void NEDepthwiseConvolutionLayer3x3::configure(ITensor *input, } else { - configure_generic(input, weights, biases, output, conv_info, depth_multiplier, act_info); + configure_generic(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } // Configure activation @@ -230,7 +238,11 @@ Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN); - ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() != 1 || dilation.y() != 1); + ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() < 1 || dilation.y() < 1); + const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); + const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) > input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) > input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); if(biases != nullptr) { @@ -239,7 +251,7 @@ Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(channel_idx)); } - if(!NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input, weights, conv_info, depth_multiplier)) + if(!NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input, weights, conv_info, depth_multiplier, dilation)) { const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); TensorInfo accumulator = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32)); @@ -356,12 +368,17 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh { const unsigned int channel_idx = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::CHANNEL); ARM_COMPUTE_UNUSED(channel_idx); - ARM_COMPUTE_ERROR_ON(dilation.x() != 1 || dilation.y() != 1); - ARM_COMPUTE_UNUSED(dilation); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_ERROR_ON((input->info()->dimension(channel_idx) * depth_multiplier) != weights->info()->dimension(channel_idx)); + // idx_w and idx_h only used for validation + const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH); + const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); + ARM_COMPUTE_UNUSED(idx_w); + ARM_COMPUTE_UNUSED(idx_h); + + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_w) + (weights->info()->dimension(idx_w) - 1) * (dilation.x() - 1) > input->info()->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_h) + (weights->info()->dimension(idx_h) - 1) * (dilation.y() - 1) > input->info()->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); _is_nhwc = input->info()->data_layout() == DataLayout::NHWC; @@ -392,7 +409,7 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh bool append_bias = (biases != nullptr) && !_is_quantized; // Calculate output shape - TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info, depth_multiplier); + TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info, depth_multiplier, dilation); // Output auto inizialitation if not yet initialized auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); @@ -420,7 +437,7 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh shape_im2col.set(1, conv_size); shape_im2col.set(2, weights_z); _input_reshaped.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col).set_data_layout(DataLayout::NCHW)); - _im2col_kernel.configure(input_to_use, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier); + _im2col_kernel.configure(input_to_use, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier, dilation); // Weights reshape configuration const TensorShape shape_weights_reshape(patch_size, weights_z); @@ -491,11 +508,13 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN); - ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() != 1 || dilation.y() != 1); + ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() < 1 || dilation.y() < 1); const unsigned int width_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); const unsigned int height_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(width_idx) + (weights->dimension(width_idx) - 1) * (dilation.x() - 1) > input->dimension(width_idx) + conv_info.pad_left() + conv_info.pad_right()); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(height_idx) + (weights->dimension(height_idx) - 1) * (dilation.y() - 1) > input->dimension(height_idx) + conv_info.pad_top() + conv_info.pad_bottom()); // Clone output to use auto init auto output_clone = output->clone(); @@ -522,7 +541,7 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); const bool append_bias = (biases != nullptr) && !is_quantized; - TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier); + TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); const size_t weights_w = weights_to_use->dimension(0); const size_t weights_h = weights_to_use->dimension(1); const size_t weights_z = weights_to_use->dimension(2); @@ -549,7 +568,7 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe shape_im2col.set(1, conv_size); shape_im2col.set(2, weights_z); TensorInfo input_reshaped(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col).set_data_layout(DataLayout::NCHW)); - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseIm2ColKernel::validate(input_to_use, &input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier)); + ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseIm2ColKernel::validate(input_to_use, &input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier, dilation)); // Weights reshape configuration const TensorShape shape_weights_reshape(patch_size, weights_z); |