From 341b218eff8c75aa9862b333bb0012a03c14a1ef Mon Sep 17 00:00:00 2001 From: John Kesapides Date: Fri, 22 Feb 2019 10:05:29 +0000 Subject: COMPMID-1493 Create tests/validate_examples/graph_fully_connected Add graph example with validation for fully-connected layer Change-Id: I06fcc670b7097609f04eb040fedf56108c9484d2 Signed-off-by: John Kesapides Reviewed-on: https://review.mlplatform.org/c/764 Tested-by: Arm Jenkins Reviewed-by: Pablo Marquez Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins --- tests/validate_examples/graph_fully_connected.cpp | 596 +++++++++++++++++++++ tests/validation/reference/FullyConnectedLayer.cpp | 21 +- tests/validation/reference/FullyConnectedLayer.h | 5 +- 3 files changed, 614 insertions(+), 8 deletions(-) create mode 100644 tests/validate_examples/graph_fully_connected.cpp (limited to 'tests') diff --git a/tests/validate_examples/graph_fully_connected.cpp b/tests/validate_examples/graph_fully_connected.cpp new file mode 100644 index 0000000000..e4f51175f0 --- /dev/null +++ b/tests/validate_examples/graph_fully_connected.cpp @@ -0,0 +1,596 @@ +/* + * 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 + +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 +{ +/** Structure holding all the input tensor graph parameters */ +struct TensorParams +{ + int width{ 1 }; + int height{ 1 }; + int fm{ 1 }; + int batch{ 1 }; + QuantizationInfo quant_info{ 1.0f, 0 }; + uint64_t range_low{ 0 }; + uint64_t range_high{ 16 }; +}; +/** Structure holding all the verification graph parameters */ +struct VerificationParams +{ + float absolute_tolerance{ -1.f }; + float relative_tolerance{ -1.f }; + float tolerance_number{ -1.f }; +}; + +/** Structure holding all the common graph parameters */ +struct FrameworkParams +{ + bool help{ false }; + int threads{ 0 }; + arm_compute::graph::Target target{ arm_compute::graph::Target::NEON }; +}; + +/** Structure holding all the fully_connected layer graph parameters */ +struct FullyConnectedParams +{ + arm_compute::DataType data_type{ DataType::F32 }; + arm_compute::DataLayout data_layout{ DataLayout::NCHW }; + FullyConnectedLayerInfo info{}; + int num_outputs{ 1 }; +}; + +/** Structure holding all the graph Example parameters */ +struct ExampleParams +{ + FrameworkParams common_params{}; + TensorParams input{}; + TensorParams weights{}; + TensorParams output{}; + VerificationParams verification{}; + FullyConnectedParams fully_connected{}; +}; + +/** Formatted output of the fully_connectedParams type + * + * @param[out] os Output stream. + * @param[in] common_params fully_connected parameters to output + * + * @return Modified output stream. + */ +::std::ostream &operator<<(::std::ostream &os, const ExampleParams &common_params) +{ + std::string false_str = std::string("false"); + std::string true_str = std::string("true"); + + os << "Threads : " << common_params.common_params.threads << std::endl; + os << "Target : " << common_params.common_params.target << std::endl; + os << "Data type : " << common_params.fully_connected.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; + return os; +} + +/** 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: + explicit FullyConnectedOptions(CommandLineParser &parser) noexcept + : width(parser.add_option>("width", 3)), + batch(parser.add_option>("batch", 1)), + help(parser.add_option("help")), + threads(parser.add_option>("threads")), + target(), + data_type(), + absolute_tolerance(parser.add_option>("abs_tolerance", -1.0f)), + relative_tolerance(parser.add_option>("rel_tolerance", -1.0f)), + tolerance_number(parser.add_option>("tolerance_num", -1.0f)), + input_scale(parser.add_option>("input_scale", 1.0f)), + input_offset(parser.add_option>("input_offset", 0)), + weights_scale(parser.add_option>("weights_scale", 1.0f)), + weights_offset(parser.add_option>("weights_offset", 0)), + output_scale(parser.add_option>("output_scale", 1.0f)), + output_offset(parser.add_option>("output_offset", 0)), + num_outputs(parser.add_option>("num_outputs", 1)), + input_range_low(parser.add_option>("input_range_low")), + input_range_high(parser.add_option>("input_range_high")), + weights_range_low(parser.add_option>("weights_range_low")), + weights_range_high(parser.add_option>("weights_range_high")) + { + const std::set supported_targets + { + Target::NEON, + Target::CL, + Target::GC, + }; + + const std::set supported_data_types + { + DataType::F16, + DataType::F32, + DataType::QASYMM8, + }; + + target = parser.add_option>("target", supported_targets, Target::NEON); + data_type = parser.add_option>("type", supported_data_types, DataType::F32); + + target->set_help("Target to execute on"); + data_type->set_help("Data type to use"); + help->set_help("Show this help message"); + width->set_help("Set Input dimension width"); + batch->set_help("Set Input dimension batch"); + absolute_tolerance->set_help("Absolute tolerance used for verification"); + relative_tolerance->set_help("Absolute tolerance used for verification"); + tolerance_number->set_help("Absolute tolerance used for verification"); + 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"); + } + + /** 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() = default; + + SimpleOption *width; /**< Input width */ + SimpleOption *batch; /**< Input batch */ + ToggleOption *help; /**< show help message */ + SimpleOption *threads; /**< Number of threads option */ + EnumOption *target; /**< Graph execution target */ + EnumOption *data_type; /**< Graph data type */ + SimpleOption *absolute_tolerance; /**< Absolute tolerance used in verification */ + SimpleOption *relative_tolerance; /**< Relative tolerance used in verification */ + SimpleOption *tolerance_number; /**< Tolerance number used in verification */ + SimpleOption *input_scale; /**< Input Quantization scale from QASSYMM8 */ + SimpleOption *input_offset; /**< Input Quantization offset from QASSYMM8 */ + SimpleOption *weights_scale; /**< Weights Quantization scale from QASSYMM8 */ + SimpleOption *weights_offset; /**< Weights Quantization offset from QASSYMM8 */ + SimpleOption *output_scale; /**< Output Quantization scale from QASSYMM8 */ + SimpleOption *output_offset; /**< Output Quantization offset from QASSYMM8 */ + SimpleOption *num_outputs; /**< Number of outputs. */ + SimpleOption *input_range_low; /**< Lower bound for input randomization range */ + SimpleOption *input_range_high; /**< Upper bound for input randomization range */ + SimpleOption *weights_range_low; /**< Lower bound for weights randomization range */ + SimpleOption *weights_range_high; /**< Upper bound for weights randomization range */ +}; + +/** Consumes the fully_connected graph options and creates a structure containing any information + * + * @param[in] options Options to consume + * + * @return fully_connectedparams structure containing the common graph parameters + */ +ExampleParams consume_fully_connected_graph_parameters(FullyConnectedOptions &options) +{ + ExampleParams common_params; + + common_params.common_params.help = options.help->is_set() ? options.help->value() : false; + common_params.common_params.threads = options.threads->value(); + common_params.common_params.target = options.target->value(); + + common_params.input.width = options.width->value(); + common_params.input.batch = options.batch->value(); + common_params.input.quant_info.scale = options.input_scale->value(); + common_params.input.quant_info.offset = options.input_offset->value(); + common_params.input.range_low = options.input_range_low->value(); + common_params.input.range_high = options.input_range_high->value(); + + common_params.weights.quant_info.scale = options.weights_scale->value(); + common_params.weights.quant_info.offset = options.weights_offset->value(); + common_params.weights.range_low = options.weights_range_low->value(); + common_params.weights.range_high = options.weights_range_high->value(); + + common_params.output.quant_info.scale = options.output_scale->value(); + common_params.output.quant_info.offset = options.output_offset->value(); + + common_params.fully_connected.data_type = options.data_type->value(); + common_params.fully_connected.num_outputs = options.num_outputs->value(); + + common_params.verification.absolute_tolerance = options.absolute_tolerance->value(); + common_params.verification.relative_tolerance = options.relative_tolerance->value(); + common_params.verification.tolerance_number = options.tolerance_number->value(); + + return common_params; +} + +/** fully_connectedLayer Graph example validation accessor class */ +template +class FullyConnectedVerifyAccessor final : public graph::ITensorAccessor +{ +public: + using TBias = typename std::conditional::type, uint8_t>::value, int32_t, D>::type; + + /** Constructor + * + * @param[in] params fully_connected parameters + */ + explicit FullyConnectedVerifyAccessor(ExampleParams ¶ms) + : _params(params) + { + } + + // Inherited methods overridden: + bool access_tensor(ITensor &tensor) override + { + const RelativeTolerance rel_tolerance(relative_tolenace(_params.verification.relative_tolerance)); /**< Relative tolerance */ + const AbsoluteTolerance abs_tolerance(absolute_tolerance(_params.verification.absolute_tolerance)); /**< Absolute tolerance */ + const float tolerance_num(tolerance_number(_params.verification.tolerance_number)); /**< Tolerance number */ + + // 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.fully_connected.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 + SimpleTensor src{ input_descriptor.shape, _params.fully_connected.data_type, 1, input_descriptor.quant_info }; + SimpleTensor weights{ weights_descriptor.shape, _params.fully_connected.data_type, 1, weights_descriptor.quant_info }; + SimpleTensor bias{ TensorShape(tensor.info()->tensor_shape().x()), _params.fully_connected.data_type, 1, _params.input.quant_info }; + + //Fill the tensors with random values + fill_tensor(src, 0, static_cast(_params.input.range_low), static_cast(_params.input.range_high)); + fill_tensor(weights, 1, static_cast(_params.weights.range_low), static_cast(_params.weights.range_high)); + fill_tensor(bias, 2, static_cast(_params.input.range_low), static_cast(_params.input.range_high)); + + //Calculate reference + SimpleTensor output = reference::fully_connected_layer(src, weights, bias, output_desciptor.shape, _params.output.quant_info); + + arm_compute::test::validation::validate(Accessor(tensor), output, rel_tolerance, tolerance_num, abs_tolerance); + + return false; + } + +private: + /** Fill tensor with Random values. + * + * Validate the given tensor against the reference result. + * + * @param[out] tensor The tensor we want to file + * @param[in] seed seed for the randomization function + * @param[in] low lower bound for random values + * @param[in] high upper bound for random values + * + * @return None. + */ + template + void fill_tensor(arm_compute::test::SimpleTensor &tensor, std::random_device::result_type seed, T low, T high) + { + std::mt19937 gen(seed); + switch(tensor.data_type()) + { + case arm_compute::DataType::QASYMM8: + { + const uint8_t qasymm8_low = tensor.quantization_info().quantize(low, RoundingPolicy::TO_NEAREST_UP); + const uint8_t qasymm8_high = tensor.quantization_info().quantize(high, RoundingPolicy::TO_NEAREST_UP); + + std::uniform_int_distribution distribution(qasymm8_low, qasymm8_high); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = tensor.quantization_info().quantize(distribution(gen), RoundingPolicy::TO_NEAREST_UP); + } + + break; + } + case arm_compute::DataType::S32: + { + std::uniform_int_distribution distribution(static_cast(low), static_cast(high)); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = distribution(gen); + } + + break; + } + + case arm_compute::DataType::F16: + { + std::uniform_real_distribution distribution(static_cast(low), static_cast(high)); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = static_cast(distribution(gen)); + } + break; + } + case arm_compute::DataType::F32: + { + std::uniform_real_distribution distribution(static_cast(low), static_cast(high)); + + for(int i = 0; i < tensor.num_elements(); ++i) + { + tensor[i] = distribution(gen); + } + + break; + } + default: + ARM_COMPUTE_ERROR("NOT SUPPORTED!"); + } + } + /** Select relative tolerance. + * + * Select relative tolerance if not supplied by user. + * + * @param[in] user_value supplied relative tolerance. -1 designates no user input + * + * @return Appropriate relative tolerance. + */ + float relative_tolenace(float user_value) + { + const std::map> 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 } + } + } + }; + if(user_value == -1) + { + return relative_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type); + } + + return user_value; + } + + /** Select absolute tolerance. + * + * Select absolute tolerance if not supplied by user. + * + * @param[in] user_value supplied absolute tolerance. -1 designates no user input + * + * @return Appropriate absolute tolerance. + */ + float absolute_tolerance(float user_value) + { + const std::map> 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 } + } + } + }; + + if(user_value == -1) + { + return absolute_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type); + } + return user_value; + } + /** Select tolerance number. + * + * Select tolerance number if not supplied by user. + * + * @param[in] user_value supplied tolerance number. -1 designates no user input + * + * @return Appropriate tolerance number. + */ + float tolerance_number(float user_value) + { + const std::map> 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 } + } + } + }; + + if(user_value == -1) + { + return absolute_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type); + } + return user_value; + } + + ExampleParams _params; +}; + +/** Generates appropriate fully_connected verify accessor + * + * @param[in] params User supplied parameters for fully_connected. + * + * @return A fully_connected verify accessor for the requested datatype. + */ +inline std::unique_ptr get_fully_connected_verify_accessor(ExampleParams params) +{ + switch(params.fully_connected.data_type) + { + case DataType::QASYMM8: + { + return arm_compute::support::cpp14::make_unique>( + params); + } + case DataType::F16: + { + return arm_compute::support::cpp14::make_unique>( + params); + } + case DataType::F32: + { + return arm_compute::support::cpp14::make_unique>( + params); + } + default: + ARM_COMPUTE_ERROR("NOT SUPPORTED!"); + } +} + +} // namespace + +class Graphfully_connectedValidateExample final : public ValidateExample +{ +public: + Graphfully_connectedValidateExample() + : graph(0, "fully_connected Graph example") + { + } + bool do_setup(int argc, char **argv) override + { + CommandLineParser parser; + + FullyConnectedOptions Options(parser); + + parser.parse(argc, argv); + + ExampleParams params = consume_fully_connected_graph_parameters(Options); + + if(params.common_params.help) + { + parser.print_help(argv[0]); + return false; + } + + std::cout << params << std::endl; + + // Create input descriptor + 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.fully_connected.data_type, params.input.quant_info, params.fully_connected.data_layout); + + const PixelValue lower = PixelValue(params.input.range_low, params.fully_connected.data_type, params.input.quant_info); + const PixelValue upper = PixelValue(params.input.range_high, params.fully_connected.data_type, params.input.quant_info); + + const PixelValue weights_lower = PixelValue(params.weights.range_low, params.fully_connected.data_type, params.weights.quant_info); + const PixelValue weights_upper = PixelValue(params.weights.range_high, params.fully_connected.data_type, params.weights.quant_info); + + graph << params.common_params.target + << InputLayer(input_descriptor, get_random_accessor(lower, upper, 0)) + << 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) + << OutputLayer(get_fully_connected_verify_accessor(params)); + + GraphConfig config; + config.num_threads = params.common_params.threads; + + graph.finalize(params.common_params.target, config); + + return true; + } + + void do_run() override + { + graph.run(); + } + + void do_teardown() override + { + } + +private: + Stream graph; +}; + +/** 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(argc, argv); +} diff --git a/tests/validation/reference/FullyConnectedLayer.cpp b/tests/validation/reference/FullyConnectedLayer.cpp index d65d0caab0..07ddf6d308 100644 --- a/tests/validation/reference/FullyConnectedLayer.cpp +++ b/tests/validation/reference/FullyConnectedLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -105,10 +105,16 @@ void vector_matrix_multiply(const SimpleTensor &src, const SimpleTensor &w } // namespace template -SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape) +SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape, QuantizationInfo out_quant_info) { + // if no explicit quantization has been set you the same as src + if(out_quant_info == QuantizationInfo()) + { + out_quant_info = src.quantization_info(); + } + // Create reference - SimpleTensor dst{ TensorShape{ dst_shape }, src.data_type(), 1, src.quantization_info() }; + SimpleTensor dst{ TensorShape{ dst_shape }, src.data_type(), 1, out_quant_info }; // Sanity checks const int num_batch_dimensions = std::max(0, static_cast(dst_shape.num_dimensions()) - 1); @@ -145,9 +151,12 @@ SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTe return dst; } -template SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape); -template SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape); -template SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape); +template SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape, + QuantizationInfo out_quant_info); +template SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape, + QuantizationInfo out_quant_info); +template SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape, + QuantizationInfo out_quant_info); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/FullyConnectedLayer.h b/tests/validation/reference/FullyConnectedLayer.h index 1dfb496924..f474a1cfb8 100644 --- a/tests/validation/reference/FullyConnectedLayer.h +++ b/tests/validation/reference/FullyConnectedLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -36,7 +36,8 @@ namespace validation namespace reference { template -SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape); +SimpleTensor fully_connected_layer(const SimpleTensor &src, const SimpleTensor &weights, const SimpleTensor &bias, const TensorShape &dst_shape, + QuantizationInfo out_quant_info = QuantizationInfo()); } // namespace reference } // namespace validation } // namespace test -- cgit v1.2.1