diff options
Diffstat (limited to 'tests/validate_examples/graph_fully_connected.cpp')
| -rw-r--r-- | tests/validate_examples/graph_fully_connected.cpp | 499 |
1 files changed, 110 insertions, 389 deletions
diff --git a/tests/validate_examples/graph_fully_connected.cpp b/tests/validate_examples/graph_fully_connected.cpp index e4f51175f0..085518c865 100644 --- a/tests/validate_examples/graph_fully_connected.cpp +++ b/tests/validate_examples/graph_fully_connected.cpp @@ -35,6 +35,7 @@ #include "utils/Utils.h" #include "ValidateExample.h" +#include "graph_validate_utils.h" #include <utility> @@ -45,77 +46,10 @@ 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) +namespace { - 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 +/** 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. @@ -125,19 +59,13 @@ struct ExampleParams * CommonOptions options( parser ); * parser.parse(argc, argv); */ -class FullyConnectedOptions final +class FullyConnectedOptions final : public CommonGraphValidateOptions { public: explicit FullyConnectedOptions(CommandLineParser &parser) noexcept - : width(parser.add_option<SimpleOption<int>>("width", 3)), + : CommonGraphValidateOptions(parser), + width(parser.add_option<SimpleOption<int>>("width", 3)), batch(parser.add_option<SimpleOption<int>>("batch", 1)), - help(parser.add_option<ToggleOption>("help")), - threads(parser.add_option<SimpleOption<int>>("threads")), - target(), - data_type(), - absolute_tolerance(parser.add_option<SimpleOption<float>>("abs_tolerance", -1.0f)), - relative_tolerance(parser.add_option<SimpleOption<float>>("rel_tolerance", -1.0f)), - tolerance_number(parser.add_option<SimpleOption<float>>("tolerance_num", -1.0f)), 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)), @@ -150,31 +78,8 @@ public: weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")), weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high")) { - const std::set<arm_compute::graph::Target> supported_targets - { - Target::NEON, - Target::CL, - Target::GC, - }; - - const std::set<arm_compute::DataType> supported_data_types - { - DataType::F16, - DataType::F32, - DataType::QASYMM8, - }; - - target = parser.add_option<EnumOption<Target>>("target", supported_targets, Target::NEON); - data_type = parser.add_option<EnumOption<DataType>>("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"); @@ -188,6 +93,44 @@ public: 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.scale = input_scale->value(); + common_params.input.quant_info.offset = 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.scale = weights_scale->value(); + common_params.weights.quant_info.offset = 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.scale = output_scale->value(); + common_params.output.quant_info.offset = 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) */ @@ -197,95 +140,41 @@ public: /** Allow instances of this class to be moved */ FullyConnectedOptions &operator=(FullyConnectedOptions &&) noexcept(true) = default; /** Default destructor */ - ~FullyConnectedOptions() = default; - - SimpleOption<int> *width; /**< Input width */ - SimpleOption<int> *batch; /**< Input batch */ - ToggleOption *help; /**< show help message */ - SimpleOption<int> *threads; /**< Number of threads option */ - EnumOption<arm_compute::graph::Target> *target; /**< Graph execution target */ - EnumOption<arm_compute::DataType> *data_type; /**< Graph data type */ - SimpleOption<float> *absolute_tolerance; /**< Absolute tolerance used in verification */ - SimpleOption<float> *relative_tolerance; /**< Relative tolerance used in verification */ - SimpleOption<float> *tolerance_number; /**< Tolerance number used in verification */ - 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 */ + ~FullyConnectedOptions() override = default; + + 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 */ }; -/** 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 */ +/** Fully Connected Layer Graph example validation accessor class */ template <typename D> -class FullyConnectedVerifyAccessor final : public graph::ITensorAccessor +class FullyConnectedVerifyAccessor final : public VerifyAccessor<D> { -public: + 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; - /** Constructor - * - * @param[in] params fully_connected parameters - */ - explicit FullyConnectedVerifyAccessor(ExampleParams ¶ms) - : _params(params) - { - } - - // Inherited methods overridden: - bool access_tensor(ITensor &tensor) override + // 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 { - const RelativeTolerance<float> rel_tolerance(relative_tolenace(_params.verification.relative_tolerance)); /**< Relative tolerance */ - const AbsoluteTolerance<float> 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 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, @@ -293,101 +182,31 @@ public: const TensorDescriptor output_desciptor = FullyConnectedLayerNode::compute_output_descriptor(input_descriptor, _params.fully_connected.num_outputs, _params.output.quant_info); //Create Input tensors - SimpleTensor<D> src{ input_descriptor.shape, _params.fully_connected.data_type, 1, input_descriptor.quant_info }; - SimpleTensor<D> weights{ weights_descriptor.shape, _params.fully_connected.data_type, 1, weights_descriptor.quant_info }; - SimpleTensor<TBias> 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<D>(src, 0, static_cast<D>(_params.input.range_low), static_cast<D>(_params.input.range_high)); - fill_tensor<D>(weights, 1, static_cast<D>(_params.weights.range_low), static_cast<D>(_params.weights.range_high)); - fill_tensor<TBias>(bias, 2, static_cast<TBias>(_params.input.range_low), static_cast<TBias>(_params.input.range_high)); - - //Calculate reference - SimpleTensor<D> output = reference::fully_connected_layer<D>(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; + 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 }; } -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 <typename T> - void fill_tensor(arm_compute::test::SimpleTensor<T> &tensor, std::random_device::result_type seed, T low, T high) + TensorShape output_shape(ITensor &tensor) override { - 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); + ARM_COMPUTE_UNUSED(tensor); - std::uniform_int_distribution<uint8_t> 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<int32_t> distribution(static_cast<int32_t>(low), static_cast<uint32_t>(high)); - - for(int i = 0; i < tensor.num_elements(); ++i) - { - tensor[i] = distribution(gen); - } - - break; - } - - case arm_compute::DataType::F16: - { - std::uniform_real_distribution<float> distribution(static_cast<half>(low), static_cast<half>(high)); - - for(int i = 0; i < tensor.num_elements(); ++i) - { - tensor[i] = static_cast<half>(distribution(gen)); - } - break; - } - case arm_compute::DataType::F32: - { - std::uniform_real_distribution<float> distribution(static_cast<float>(low), static_cast<float>(high)); + 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); - for(int i = 0; i < tensor.num_elements(); ++i) - { - tensor[i] = distribution(gen); - } + return output_desciptor.shape; + } - break; - } - default: - ARM_COMPUTE_ERROR("NOT SUPPORTED!"); - } + 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); } - /** 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) + + float relative_tolerance() override { const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance { @@ -406,23 +225,11 @@ private: } } }; - if(user_value == -1) - { - return relative_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type); - } - return user_value; + return relative_tolerance.at(_params.common_params.target).at(_params.data_type); } - /** 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) + float absolute_tolerance() override { const std::map<Target, const std::map<DataType, float>> absolute_tolerance { @@ -442,21 +249,10 @@ private: } }; - if(user_value == -1) - { - return absolute_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type); - } - return user_value; + return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); } - /** 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) + + float tolerance_number() override { const std::map<Target, const std::map<DataType, float>> absolute_tolerance { @@ -476,110 +272,35 @@ private: } }; - if(user_value == -1) - { - return absolute_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type); - } - return user_value; + return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); } - - 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<graph::ITensorAccessor> get_fully_connected_verify_accessor(ExampleParams params) -{ - switch(params.fully_connected.data_type) - { - case DataType::QASYMM8: - { - return arm_compute::support::cpp14::make_unique<FullyConnectedVerifyAccessor<uint8_t>>( - params); - } - case DataType::F16: - { - return arm_compute::support::cpp14::make_unique<FullyConnectedVerifyAccessor<half>>( - params); - } - case DataType::F32: - { - return arm_compute::support::cpp14::make_unique<FullyConnectedVerifyAccessor<float>>( - params); - } - default: - ARM_COMPUTE_ERROR("NOT SUPPORTED!"); - } -} - } // namespace -class Graphfully_connectedValidateExample final : public ValidateExample +class GraphFullyConnectedValidateExample final : public GraphValidateExample<FullyConnectedLayer, FullyConnectedOptions, FullyConnectedVerifyAccessor> { + using GraphValidateExample::graph; + public: - Graphfully_connectedValidateExample() - : graph(0, "fully_connected Graph example") - { - } - bool do_setup(int argc, char **argv) override + GraphFullyConnectedValidateExample() + : GraphValidateExample("Fully_connected Graph example") { - 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 + FullyConnectedLayer GraphFunctionLayer(ExampleParams ¶ms) override { - graph.run(); - } + 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); - void do_teardown() override - { - } + 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); -private: - Stream graph; + 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 @@ -592,5 +313,5 @@ private: */ int main(int argc, char **argv) { - return arm_compute::utils::run_example<Graphfully_connectedValidateExample>(argc, argv); + return arm_compute::utils::run_example<GraphFullyConnectedValidateExample>(argc, argv); } |