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Diffstat (limited to 'src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp')
| -rw-r--r-- | src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp | 152 |
1 files changed, 152 insertions, 0 deletions
diff --git a/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp new file mode 100644 index 0000000000..27a348fa69 --- /dev/null +++ b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp @@ -0,0 +1,152 @@ +/* + * 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/graph/nodes/FusedConvolutionBatchNormalizationNode.h" + +#include "arm_compute/core/Utils.h" +#include "arm_compute/graph/Graph.h" +#include "arm_compute/graph/INodeVisitor.h" +#include "arm_compute/graph/Utils.h" + +namespace arm_compute +{ +namespace graph +{ +FusedConvolutionBatchNormalizationNode::FusedConvolutionBatchNormalizationNode(float epsilon, PadStrideInfo info, + unsigned int num_groups, + ConvolutionMethod method, + FastMathHint fast_math_hint, + QuantizationInfo out_quant_info, ActivationLayerInfo fused_activation) + : _epsilon(epsilon), _info(std::move(info)), _num_groups(num_groups), _method(method), _fast_math_hint(fast_math_hint), _out_quant_info(out_quant_info), _fused_activation(fused_activation) +{ + _input_edges.resize(7, EmptyEdgeID); + _outputs.resize(1, NullTensorID); +} + +void FusedConvolutionBatchNormalizationNode::set_convolution_method(ConvolutionMethod method) +{ + _method = method; +} + +float FusedConvolutionBatchNormalizationNode::epsilon() const +{ + return _epsilon; +} + +ConvolutionMethod FusedConvolutionBatchNormalizationNode::convolution_method() const +{ + return _method; +} + +void FusedConvolutionBatchNormalizationNode::set_fast_math_hint(FastMathHint hint) +{ + _fast_math_hint = hint; +} + +FastMathHint FusedConvolutionBatchNormalizationNode::fast_math_hint() const +{ + return _fast_math_hint; +} + +PadStrideInfo FusedConvolutionBatchNormalizationNode::convolution_info() const +{ + return _info; +} + +unsigned int FusedConvolutionBatchNormalizationNode::num_groups() const +{ + return _num_groups; +} + +ActivationLayerInfo FusedConvolutionBatchNormalizationNode::fused_activation() const +{ + return _fused_activation; +} + +void FusedConvolutionBatchNormalizationNode::set_fused_activation(ActivationLayerInfo fused_activation) +{ + _fused_activation = fused_activation; +} + +TensorDescriptor FusedConvolutionBatchNormalizationNode::compute_output_descriptor(const TensorDescriptor &input_descriptor, + const TensorDescriptor &weights_descriptor, + const PadStrideInfo &info) +{ + unsigned int output_width = 0; + unsigned int output_height = 0; + + const unsigned int input_width = get_dimension_size(input_descriptor, DataLayoutDimension::WIDTH); + const unsigned int input_height = get_dimension_size(input_descriptor, DataLayoutDimension::HEIGHT); + const unsigned int kernel_width = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH); + const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT); + + std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info); + + TensorDescriptor output_descriptor = input_descriptor; + output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), output_width); + output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), output_height); + output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]); + + return output_descriptor; +} + +bool FusedConvolutionBatchNormalizationNode::forward_descriptors() +{ + if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID)) + { + Tensor *dst = output(0); + ARM_COMPUTE_ERROR_ON(dst == nullptr); + dst->desc() = configure_output(0); + return true; + } + return false; +} + +TensorDescriptor FusedConvolutionBatchNormalizationNode::configure_output(size_t idx) const +{ + ARM_COMPUTE_UNUSED(idx); + const Tensor *src = input(0); + const Tensor *weights = input(1); + + ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr); + + TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info); + if(!_out_quant_info.empty()) + { + output_info.quant_info = _out_quant_info; + } + + return output_info; +} + +NodeType FusedConvolutionBatchNormalizationNode::type() const +{ + return FusedConvolutionBatchNormalizationNode::node_type; +} + +void FusedConvolutionBatchNormalizationNode::accept(INodeVisitor &v) +{ + v.visit(*this); +} +} // namespace graph +} // namespace arm_compute |