| /* |
| * 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.h" |
| |
| #include "support/ToolchainSupport.h" |
| |
| #include "tests/NEON/Accessor.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/reference/FullyConnectedLayer.h" |
| #include "tests/validation/reference/Permute.h" |
| |
| #include "utils/CommonGraphOptions.h" |
| #include "utils/GraphUtils.h" |
| #include "utils/Utils.h" |
| |
| #include "ValidateExample.h" |
| #include "graph_validate_utils.h" |
| |
| #include <utility> |
| |
| using namespace arm_compute::utils; |
| using namespace arm_compute::graph::frontend; |
| using namespace arm_compute::graph_utils; |
| using namespace arm_compute::graph; |
| using namespace arm_compute; |
| using namespace arm_compute::test; |
| using namespace arm_compute::test::validation; |
| |
| namespace |
| { |
| /** Fully connected command line options used to configure the graph examples |
| * |
| * (Similar to common options) |
| * The options in this object get populated when "parse()" is called on the parser used to construct it. |
| * The expected workflow is: |
| * |
| * CommandLineParser parser; |
| * CommonOptions options( parser ); |
| * parser.parse(argc, argv); |
| */ |
| class FullyConnectedOptions final : public CommonGraphValidateOptions |
| { |
| public: |
| explicit FullyConnectedOptions(CommandLineParser &parser) noexcept |
| : CommonGraphValidateOptions(parser), |
| width(parser.add_option<SimpleOption<int>>("width", 3)), |
| batch(parser.add_option<SimpleOption<int>>("batch", 1)), |
| input_scale(parser.add_option<SimpleOption<float>>("input_scale", 1.0f)), |
| input_offset(parser.add_option<SimpleOption<int>>("input_offset", 0)), |
| weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)), |
| weights_offset(parser.add_option<SimpleOption<int>>("weights_offset", 0)), |
| output_scale(parser.add_option<SimpleOption<float>>("output_scale", 1.0f)), |
| output_offset(parser.add_option<SimpleOption<int>>("output_offset", 0)), |
| num_outputs(parser.add_option<SimpleOption<int>>("num_outputs", 1)), |
| input_range_low(parser.add_option<SimpleOption<uint64_t>>("input_range_low")), |
| input_range_high(parser.add_option<SimpleOption<uint64_t>>("input_range_high")), |
| weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")), |
| weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high")) |
| { |
| width->set_help("Set Input dimension width"); |
| batch->set_help("Set Input dimension batch"); |
| input_scale->set_help("Quantization scale from QASYMM8"); |
| input_offset->set_help("Quantization offset from QASYMM8"); |
| weights_scale->set_help("Quantization scale from QASYMM8"); |
| weights_offset->set_help("Quantization offset from QASYMM8"); |
| output_scale->set_help("Quantization scale from QASYMM8"); |
| output_offset->set_help("Quantization offset from QASYMM8"); |
| num_outputs->set_help("Number of outputs."); |
| input_range_low->set_help("Lower bound for input randomization range"); |
| input_range_high->set_help("Lower bound for input randomization range"); |
| weights_range_low->set_help("Lower bound for input randomization range"); |
| weights_range_high->set_help("Lower bound for input randomization range"); |
| } |
| |
| /** Fill out the supplied parameters with user supplied parameters |
| * |
| * @param[out] os Output stream. |
| * @param[in] common_params Example parameters to output |
| * |
| * @return None. |
| */ |
| void consume_parameters(ExampleParams &common_params) |
| { |
| common_params.input.width = width->value(); |
| common_params.input.batch = batch->value(); |
| common_params.input.quant_info = QuantizationInfo(input_scale->value(), input_offset->value()); |
| common_params.input.range_low = input_range_low->value(); |
| common_params.input.range_high = input_range_high->value(); |
| |
| common_params.weights.quant_info = QuantizationInfo(weights_scale->value(), weights_offset->value()); |
| common_params.weights.range_low = weights_range_low->value(); |
| common_params.weights.range_high = weights_range_high->value(); |
| |
| common_params.output.quant_info = QuantizationInfo(output_scale->value(), output_offset->value()); |
| |
| common_params.data_type = data_type->value(); |
| common_params.fully_connected.num_outputs = num_outputs->value(); |
| } |
| |
| void print_parameters(::std::ostream &os, const ExampleParams &common_params) override |
| { |
| os << "Threads : " << common_params.common_params.threads << std::endl; |
| os << "Target : " << common_params.common_params.target << std::endl; |
| os << "Data type : " << common_params.data_type << std::endl; |
| os << "Input dimensions(X,Y, Channels, Batch) : (" << common_params.input.width << "," << common_params.input.height << "," << common_params.input.fm << "," << common_params.input.batch << ")" |
| << std::endl; |
| os << "Number of outputs : " << common_params.fully_connected.num_outputs << std::endl; |
| } |
| |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| FullyConnectedOptions(const FullyConnectedOptions &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| FullyConnectedOptions &operator=(const FullyConnectedOptions &) = delete; |
| /** Allow instances of this class to be moved */ |
| FullyConnectedOptions(FullyConnectedOptions &&) noexcept(true) = default; |
| /** Allow instances of this class to be moved */ |
| FullyConnectedOptions &operator=(FullyConnectedOptions &&) noexcept(true) = default; |
| /** Default destructor */ |
| ~FullyConnectedOptions() override = default; |
| |
| private: |
| SimpleOption<int> *width; /**< Input width */ |
| SimpleOption<int> *batch; /**< Input batch */ |
| SimpleOption<float> *input_scale; /**< Input Quantization scale from QASSYMM8 */ |
| SimpleOption<int> *input_offset; /**< Input Quantization offset from QASSYMM8 */ |
| SimpleOption<float> *weights_scale; /**< Weights Quantization scale from QASSYMM8 */ |
| SimpleOption<int> *weights_offset; /**< Weights Quantization offset from QASSYMM8 */ |
| SimpleOption<float> *output_scale; /**< Output Quantization scale from QASSYMM8 */ |
| SimpleOption<int> *output_offset; /**< Output Quantization offset from QASSYMM8 */ |
| SimpleOption<int> *num_outputs; /**< Number of outputs. */ |
| SimpleOption<uint64_t> *input_range_low; /**< Lower bound for input randomization range */ |
| SimpleOption<uint64_t> *input_range_high; /**< Upper bound for input randomization range */ |
| SimpleOption<uint64_t> *weights_range_low; /**< Lower bound for weights randomization range */ |
| SimpleOption<uint64_t> *weights_range_high; /**< Upper bound for weights randomization range */ |
| }; |
| |
| /** Fully Connected Layer Graph example validation accessor class */ |
| template <typename D> |
| class FullyConnectedVerifyAccessor final : public VerifyAccessor<D> |
| { |
| using BaseClassType = VerifyAccessor<D>; |
| using BaseClassType::BaseClassType; |
| using BaseClassType::_params; |
| using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type; |
| |
| // Inherited methods overriden: |
| void create_tensors(arm_compute::test::SimpleTensor<D> &src, |
| arm_compute::test::SimpleTensor<D> &weights, |
| arm_compute::test::SimpleTensor<TBias> &bias, |
| ITensor &tensor) override |
| { |
| // Calculate Tensor shapes for verification |
| const TensorShape input_shape = TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch); |
| const TensorDescriptor input_descriptor = TensorDescriptor(input_shape, _params.data_type, _params.input.quant_info); |
| const TensorDescriptor weights_descriptor = FullyConnectedLayerNode::compute_weights_descriptor(input_descriptor, |
| _params.fully_connected.num_outputs, |
| _params.fully_connected.info, |
| _params.weights.quant_info); |
| const TensorDescriptor output_desciptor = FullyConnectedLayerNode::compute_output_descriptor(input_descriptor, _params.fully_connected.num_outputs, _params.output.quant_info); |
| |
| //Create Input tensors |
| src = SimpleTensor<D> { input_descriptor.shape, _params.data_type, 1, input_descriptor.quant_info }; |
| weights = SimpleTensor<D> { weights_descriptor.shape, _params.data_type, 1, weights_descriptor.quant_info }; |
| bias = SimpleTensor<TBias> { TensorShape(tensor.info()->tensor_shape().x()), _params.data_type, 1, _params.input.quant_info }; |
| } |
| |
| TensorShape output_shape(ITensor &tensor) override |
| { |
| ARM_COMPUTE_UNUSED(tensor); |
| |
| const TensorShape input_shape = TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch); |
| const TensorDescriptor input_descriptor = TensorDescriptor(input_shape, _params.data_type, _params.input.quant_info); |
| const TensorDescriptor output_desciptor = FullyConnectedLayerNode::compute_output_descriptor(input_descriptor, _params.fully_connected.num_outputs, _params.output.quant_info); |
| |
| return output_desciptor.shape; |
| } |
| |
| arm_compute::test::SimpleTensor<D> reference(arm_compute::test::SimpleTensor<D> &src, |
| arm_compute::test::SimpleTensor<D> &weights, |
| arm_compute::test::SimpleTensor<TBias> &bias, |
| const arm_compute::TensorShape &output_shape) override |
| { |
| return reference::fully_connected_layer<D>(src, weights, bias, output_shape, _params.output.quant_info); |
| } |
| |
| float relative_tolerance() override |
| { |
| const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance |
| { |
| { |
| arm_compute::graph::Target::CL, |
| { { DataType::F16, 0.2f }, |
| { DataType::F32, 0.05f }, |
| { DataType::QASYMM8, 1.0f } |
| } |
| }, |
| { |
| arm_compute::graph::Target::NEON, |
| { { DataType::F16, 0.2f }, |
| { DataType::F32, 0.01f }, |
| { DataType::QASYMM8, 1.0f } |
| } |
| } |
| }; |
| |
| return relative_tolerance.at(_params.common_params.target).at(_params.data_type); |
| } |
| |
| float absolute_tolerance() override |
| { |
| const std::map<Target, const std::map<DataType, float>> absolute_tolerance |
| { |
| { |
| Target::CL, |
| { { DataType::F16, 0.0f }, |
| { DataType::F32, 0.0001f }, |
| { DataType::QASYMM8, 1.0f } |
| } |
| }, |
| { |
| Target::NEON, |
| { { DataType::F16, 0.3f }, |
| { DataType::F32, 0.1f }, |
| { DataType::QASYMM8, 1.0f } |
| } |
| } |
| }; |
| |
| return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); |
| } |
| |
| float tolerance_number() override |
| { |
| const std::map<Target, const std::map<DataType, float>> absolute_tolerance |
| { |
| { |
| Target::CL, |
| { { DataType::F16, 0.07f }, |
| { DataType::F32, 0.07f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| }, |
| { |
| Target::NEON, |
| { { DataType::F16, 0.07f }, |
| { DataType::F32, 0.0f }, |
| { DataType::QASYMM8, 0.0f } |
| } |
| } |
| }; |
| |
| return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); |
| } |
| }; |
| |
| } // namespace |
| |
| class GraphFullyConnectedValidateExample final : public GraphValidateExample<FullyConnectedLayer, FullyConnectedOptions, FullyConnectedVerifyAccessor> |
| { |
| using GraphValidateExample::graph; |
| |
| public: |
| GraphFullyConnectedValidateExample() |
| : GraphValidateExample("Fully_connected Graph example") |
| { |
| } |
| |
| FullyConnectedLayer GraphFunctionLayer(ExampleParams ¶ms) override |
| { |
| const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info); |
| const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info); |
| |
| const PixelValue weights_lower = PixelValue(params.weights.range_low, params.data_type, params.weights.quant_info); |
| const PixelValue weights_upper = PixelValue(params.weights.range_high, params.data_type, params.weights.quant_info); |
| |
| return FullyConnectedLayer(params.fully_connected.num_outputs, |
| get_random_accessor(weights_lower, weights_upper, 1), |
| get_random_accessor(lower, upper, 2), |
| params.fully_connected.info, params.weights.quant_info, params.output.quant_info); |
| } |
| }; |
| |
| /** Main program for Graph fully_connected test |
| * |
| * @param[in] argc Number of arguments |
| * @param[in] argv Arguments ( Input dimensions [width, batch] |
| * Fully connected [num_outputs,type] |
| * Verification[tolerance_number,absolute_tolerance,relative_tolerance] ) |
| * |
| */ |
| int main(int argc, char **argv) |
| { |
| return arm_compute::utils::run_example<GraphFullyConnectedValidateExample>(argc, argv); |
| } |