diff options
Diffstat (limited to 'tests/validate_examples/graph_convolution.cpp')
| -rw-r--r-- | tests/validate_examples/graph_convolution.cpp | 668 |
1 files changed, 113 insertions, 555 deletions
diff --git a/tests/validate_examples/graph_convolution.cpp b/tests/validate_examples/graph_convolution.cpp index 4f5ab0dc08..acc1e69544 100644 --- a/tests/validate_examples/graph_convolution.cpp +++ b/tests/validate_examples/graph_convolution.cpp @@ -35,6 +35,7 @@ #include "utils/Utils.h" #include "ValidateExample.h" +#include "graph_validate_utils.h" #include <utility> @@ -45,161 +46,9 @@ using namespace arm_compute::graph; using namespace arm_compute; using namespace arm_compute::test; using namespace arm_compute::test::validation; -namespace -{ -/*Available Padding modes */ -enum class PaddingMode -{ - Valid, - Same, - Manual -}; -/** Stream Input operator for the PaddingMode type - * - * @param[in] stream Input stream. - * @param[out] Mode Convolution parameters to output - * - * @return input stream. - */ -inline ::std::istream &operator>>(::std::istream &stream, PaddingMode &Mode) -{ - static const std::map<std::string, PaddingMode> modes = - { - { "valid", PaddingMode::Valid }, - { "same", PaddingMode::Same }, - { "manual", PaddingMode::Manual } - }; - std::string value; - stream >> value; - try - { - Mode = modes.at(arm_compute::utility::tolower(value)); - } - catch(const std::out_of_range &) - { - throw std::invalid_argument(value); - } - - return stream; -} - -/** Formatted output of the PaddingMode type - * - * @param[out] os Output stream. - * @param[in] Mode PaddingMode to output - * - * @return Modified output stream. - */ -inline ::std::ostream &operator<<(::std::ostream &os, PaddingMode Mode) -{ - switch(Mode) - { - case PaddingMode::Valid: - os << "Valid"; - break; - case PaddingMode::Same: - os << "Same"; - break; - case PaddingMode::Manual: - os << "Manual"; - break; - default: - throw std::invalid_argument("Unsupported padding mode format"); - } - - return os; -} -/** Structure holding all the input tensor graph parameters */ -struct TensorParams -{ - int width{ 0 }; - int height{ 0 }; - int fm{ 0 }; - int batch{ 0 }; - QuantizationInfo quant_info{ 1.0f, 0 }; - std::string npy{}; - 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 Convolution layer graph parameters */ -struct ConvolutionParams -{ - arm_compute::DataType data_type{ DataType::F32 }; - arm_compute::DataLayout data_layout{ DataLayout::NCHW }; - arm_compute::graph::ConvolutionMethod convolution_method{ arm_compute::graph::ConvolutionMethod::Default }; - - /** Padding graph parameters */ - int padding_top{ 0 }; - int padding_bottom{ 0 }; - int padding_left{ 0 }; - int padding_right{ 0 }; - int padding_stride_x{ 0 }; - int padding_stride_y{ 0 }; - PaddingMode padding_mode{ PaddingMode::Valid }; - struct - { - struct - { - int X{ 0 }; - int Y{ 0 }; - } stride{}; - PaddingMode mode{ PaddingMode::Valid }; - } padding{}; -}; - -/** Structure holding all the graph Example parameters */ -struct ExampleParams -{ - FrameworkParams common_params{}; - TensorParams input{}; - TensorParams weights{}; - TensorParams bias{}; - TensorParams output{}; - VerificationParams verification{}; - ConvolutionParams convolution{}; -}; - -/** Formatted output of the ConvolutionParams type - * - * @param[out] os Output stream. - * @param[in] common_params Convolution parameters to output - * - * @return Modified output stream. - */ -::std::ostream &operator<<(::std::ostream &os, const ExampleParams &common_params) +namespace { - os << "Threads : " << common_params.common_params.threads << std::endl; - os << "Target : " << common_params.common_params.target << std::endl; - os << "Data type : " << common_params.convolution.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 << "Weight dimensions(X,Y, Channels(same as input), OFM) : (" << common_params.weights.width << "," << common_params.weights.height << "," << common_params.input.fm << "," << - common_params.weights.fm << ")" << std::endl; - os << "Padding(top, bottom, left, right) (stride x, stride y) : (" << common_params.convolution.padding_top << "," << common_params.convolution.padding_bottom << "," << - common_params.convolution.padding_left << "," << common_params.convolution.padding_right << ") (" << common_params.convolution.padding_stride_x << "," << common_params.convolution.padding_stride_y << - ")" << std::endl; - os << "Padding Mode: " << common_params.convolution.padding_mode << std::endl; - os << "Convolution Method: " << common_params.convolution.convolution_method << std::endl; - return os; -} - /** Convolution command line options used to configure the graph examples * * (Similar to common options) @@ -210,11 +59,12 @@ struct ExampleParams * CommonOptions options( parser ); * parser.parse(argc, argv); */ -class ConvolutionOptions final +class ConvolutionOptions final : public CommonGraphValidateOptions { public: explicit ConvolutionOptions(CommandLineParser &parser) noexcept - : width(parser.add_option<SimpleOption<int>>("width", 9)), + : CommonGraphValidateOptions(parser), + width(parser.add_option<SimpleOption<int>>("width", 9)), height(parser.add_option<SimpleOption<int>>("height", 9)), channels(parser.add_option<SimpleOption<int>>("channels", 1)), batch(parser.add_option<SimpleOption<int>>("batch", 1)), @@ -227,16 +77,9 @@ public: padding_right(parser.add_option<SimpleOption<int>>("padding_right", 0)), stride_x(parser.add_option<SimpleOption<int>>("stride_x", 1)), stride_y(parser.add_option<SimpleOption<int>>("stride_y", 1)), - help(parser.add_option<ToggleOption>("help")), - threads(parser.add_option<SimpleOption<int>>("threads")), - target(), - data_type(), padding_mode(), conv_mode(), data_layout(), - 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)), scale(parser.add_option<SimpleOption<float>>("scale", 1.0f)), offset(parser.add_option<SimpleOption<int>>("offset", 0)), weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)), @@ -252,24 +95,10 @@ public: weights_npy(parser.add_option<SimpleOption<std::string>>("weights_npy")), bias_npy(parser.add_option<SimpleOption<std::string>>("bias_image")) { - const std::set<PaddingMode> available_padding_modes - { - PaddingMode::Valid, - PaddingMode::Same - }; - - const std::set<arm_compute::graph::Target> supported_targets + const std::set<ConvolutionPaddingMode> available_padding_modes { - Target::NEON, - Target::CL, - Target::GC, - }; - - const std::set<arm_compute::DataType> supported_data_types - { - DataType::F16, - DataType::F32, - DataType::QASYMM8, + ConvolutionPaddingMode::Valid, + ConvolutionPaddingMode::Same }; const std::set<arm_compute::graph::ConvolutionMethod> supported_convolution_methods @@ -286,14 +115,10 @@ public: DataLayout::NCHW, }; - padding_mode = parser.add_option<EnumOption<PaddingMode>>("padding_mode", available_padding_modes, PaddingMode::Valid); - target = parser.add_option<EnumOption<Target>>("target", supported_targets, Target::NEON); - data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32); + padding_mode = parser.add_option<EnumOption<ConvolutionPaddingMode>>("padding_mode", available_padding_modes, ConvolutionPaddingMode::Valid); conv_mode = parser.add_option<EnumOption<arm_compute::graph::ConvolutionMethod>>("convolution_method", supported_convolution_methods, arm_compute::graph::ConvolutionMethod::Default); data_layout = parser.add_option<EnumOption<DataLayout>>("layout", supported_data_layouts, DataLayout::NHWC); - target->set_help("Target to execute on"); - data_type->set_help("Data type to use"); padding_mode->set_help("Set padding mode"); help->set_help("Show this help message"); width->set_help("Set Input dimension width"); @@ -310,10 +135,6 @@ public: stride_x->set_help("Set padding stride x"); stride_y->set_help("Set padding stride y"); conv_mode->set_help("Set convolution method"); - data_layout->set_help("Data layout to use"); - 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"); scale->set_help("Quantization scale from QASYMM8"); offset->set_help("Quantization offset from QASYMM8"); weights_scale->set_help("Quantization scale from QASYMM8"); @@ -328,6 +149,69 @@ 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.height = height->value(); + common_params.input.fm = channels->value(); + common_params.input.batch = batch->value(); + common_params.input.quant_info.scale = scale->value(); + common_params.input.quant_info.offset = offset->value(); + common_params.input.npy = input_npy->value(); + common_params.input.range_low = input_range_low->value(); + common_params.input.range_high = input_range_high->value(); + + common_params.weights.width = weights_width->value(); + common_params.weights.height = weights_height->value(); + common_params.weights.fm = OFM->value(); + common_params.weights.npy = weights_npy->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.bias.npy = bias_npy->value(); + + common_params.output.quant_info.scale = output_scale->value(); + common_params.output.quant_info.offset = output_offset->value(); + common_params.output.npy = output_npy->value(); + + common_params.convolution.padding_mode = padding_mode->value(); + common_params.convolution.padding_top = padding_top->value(); + common_params.convolution.padding_bottom = padding_bottom->value(); + common_params.convolution.padding_left = padding_left->value(); + common_params.convolution.padding_right = padding_right->value(); + common_params.convolution.padding_stride_x = stride_x->value(); + common_params.convolution.padding_stride_y = stride_y->value(); + + common_params.data_type = data_type->value(); + common_params.data_layout = data_layout->value(); + common_params.convolution_method = conv_mode->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 << "Weight dimensions(X,Y, Channels(same as input), OFM) : (" << common_params.weights.width << "," << common_params.weights.height << "," << common_params.input.fm << "," << + common_params.weights.fm << ")" << std::endl; + os << "Padding(top, bottom, left, right) (stride x, stride y) : (" << common_params.convolution.padding_top << "," << common_params.convolution.padding_bottom << "," << + common_params.convolution.padding_left << "," << common_params.convolution.padding_right << ") (" << common_params.convolution.padding_stride_x << "," << common_params.convolution.padding_stride_y << + ")" << std::endl; + os << "Padding Mode: " << common_params.convolution.padding_mode << std::endl; + os << "Convolution Method: " << common_params.convolution_method << std::endl; + } + /** Prevent instances of this class from being copied (As this class contains pointers) */ ConvolutionOptions(const ConvolutionOptions &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ @@ -337,7 +221,7 @@ public: /** Allow instances of this class to be moved */ ConvolutionOptions &operator=(ConvolutionOptions &&) noexcept(true) = default; /** Default destructor */ - ~ConvolutionOptions() = default; + ~ConvolutionOptions() override = default; SimpleOption<int> *width; /**< Input width */ SimpleOption<int> *height; /**< Input height */ @@ -352,16 +236,9 @@ public: SimpleOption<int> *padding_right; /**< Padding right */ SimpleOption<int> *stride_x; /**< Padding stride x */ SimpleOption<int> *stride_y; /**< Padding stride y */ - 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 */ - EnumOption<PaddingMode> *padding_mode; /**< Padding mode */ + EnumOption<ConvolutionPaddingMode> *padding_mode; /**< Padding mode */ EnumOption<arm_compute::graph::ConvolutionMethod> *conv_mode; /**< Convolution method */ EnumOption<arm_compute::DataLayout> *data_layout; /**< Graph data layout */ - 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> *scale; /**< Input Quantization scale from QASYMM8 */ SimpleOption<int> *offset; /**< Input Quantization offset from QASYMM8 */ SimpleOption<float> *weights_scale; /**< Weights Quantization scale from QASYMM8 */ @@ -379,227 +256,26 @@ public: SimpleOption<std::string> *bias_npy; /**< Use bias .npy image */ }; -/** Consumes the convolution graph options and creates a structure containing any information - * - * @param[in] options Options to consume - * - * @return Convolutionparams structure containing the common graph parameters - */ -ExampleParams consume_covolution_graph_parameters(ConvolutionOptions &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.height = options.height->value(); - common_params.input.fm = options.channels->value(); - common_params.input.batch = options.batch->value(); - common_params.input.quant_info.scale = options.scale->value(); - common_params.input.quant_info.offset = options.offset->value(); - common_params.input.npy = options.input_npy->value(); - common_params.input.range_low = options.input_range_low->value(); - common_params.input.range_high = options.input_range_high->value(); - - common_params.weights.width = options.weights_width->value(); - common_params.weights.height = options.weights_height->value(); - common_params.weights.fm = options.OFM->value(); - common_params.weights.npy = options.weights_npy->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.bias.npy = options.bias_npy->value(); - - common_params.output.quant_info.scale = options.output_scale->value(); - common_params.output.quant_info.offset = options.output_offset->value(); - common_params.output.npy = options.output_npy->value(); - - common_params.convolution.padding_mode = options.padding_mode->value(); - common_params.convolution.padding_top = options.padding_top->value(); - common_params.convolution.padding_bottom = options.padding_bottom->value(); - common_params.convolution.padding_left = options.padding_left->value(); - common_params.convolution.padding_right = options.padding_right->value(); - common_params.convolution.padding_stride_x = options.stride_x->value(); - common_params.convolution.padding_stride_y = options.stride_y->value(); - common_params.convolution.convolution_method = options.conv_mode->value(); - common_params.convolution.data_type = options.data_type->value(); - common_params.convolution.data_layout = options.data_layout->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; -} - -/** Calculate stride information. - * - * Depending on the selected padding mode create the desired PadStrideInfo - * - * @param[in] params Convolution parameters supplied by the user. - * - * @return PadStrideInfo with the correct padding mode. - */ -inline PadStrideInfo calculate_convolution_padding(ExampleParams params) -{ - switch(params.convolution.padding_mode) - { - case PaddingMode::Manual: - { - return PadStrideInfo(params.convolution.padding_stride_x, params.convolution.padding_stride_y, params.convolution.padding_left, params.convolution.padding_right, params.convolution.padding_top, - params.convolution.padding_bottom, DimensionRoundingType::FLOOR); - } - case PaddingMode::Valid: - { - return PadStrideInfo(); - } - case PaddingMode::Same: - { - return arm_compute::calculate_same_pad(TensorShape(params.input.width, params.input.height), TensorShape(params.weights.width, params.weights.height), - PadStrideInfo(params.convolution.padding_stride_x, - params.convolution.padding_stride_y)); - } - default: - ARM_COMPUTE_ERROR("NOT SUPPORTED!"); - } -} - /** ConvolutionLayer Graph example validation accessor class */ template <typename D> -class ConvolutionVerifyAccessor final : public graph::ITensorAccessor +class ConvolutionVerifyAccessor 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 Convolution parameters - */ - explicit ConvolutionVerifyAccessor(ExampleParams ¶ms) - : _params(std::move(params)) + SimpleTensor<D> reference(SimpleTensor<D> &src, SimpleTensor<D> &weights, SimpleTensor<TBias> &bias, const TensorShape &output_shape) override { - } + // Calculate padding information + const PadStrideInfo padding_info = calculate_convolution_padding(_params); - // Inherited methods overriden: - bool access_tensor(ITensor &tensor) override - { - if(_params.output.npy.empty()) - { - 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 */ - - //Create Input tensors - SimpleTensor<D> src{ TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch), _params.convolution.data_type, 1, _params.input.quant_info }; - SimpleTensor<D> weights{ TensorShape(_params.weights.width, _params.weights.height, _params.weights.fm), _params.convolution.data_type, 1, _params.weights.quant_info }; - SimpleTensor<TBias> bias{ TensorShape(_params.input.height), _params.convolution.data_type, 1, _params.input.quant_info }; - - //Fill the tenors 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 padding information - const PadStrideInfo padding_info = calculate_convolution_padding(_params); - - //Calculate reference - SimpleTensor<D> output = reference::convolution_layer<D>(src, weights, bias, permute_shape(tensor.info()->tensor_shape(), _params.convolution.data_layout, DataLayout::NCHW), padding_info, Size2D(1, - 1), - 1, - _params.output.quant_info); - - arm_compute::test::validation::validate(Accessor(tensor), output, rel_tolerance, tolerance_num, abs_tolerance); - } - else - { - //The user provided a reference file use an npy accessor to validate - NumPyAccessor(_params.output.npy, tensor.info()->tensor_shape(), tensor.info()->data_type()).access_tensor(tensor); - } - return false; + //Calculate reference + return reference::convolution_layer<D>(src, weights, bias, output_shape, padding_info, Size2D(1, 1), + 1, _params.output.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) - { - std::mt19937 gen(seed); - switch(tensor.data_type()) - { - case arm_compute::DataType::QASYMM8: - { - uint8_t qasymm8_low = tensor.quantization_info().quantize(low, RoundingPolicy::TO_NEAREST_UP); - uint8_t qasymm8_high = tensor.quantization_info().quantize(high, RoundingPolicy::TO_NEAREST_UP); - - 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)); - - 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) + float relative_tolerance() override { const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance { @@ -618,32 +294,20 @@ private: } } }; - if(user_value == -1) + + if(_params.convolution_method == arm_compute::graph::ConvolutionMethod::Winograd + && _params.data_type == DataType::F32 + && _params.common_params.target == arm_compute::graph::Target::NEON) { - if(_params.convolution.convolution_method == arm_compute::graph::ConvolutionMethod::Winograd - && _params.convolution.data_type == DataType::F32 - && _params.common_params.target == arm_compute::graph::Target::NEON) - { - return 0.05f; - } - else - { - return relative_tolerance.at(_params.common_params.target).at(_params.convolution.data_type); - } + return 0.05f; + } + else + { + return relative_tolerance.at(_params.common_params.target).at(_params.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) + float absolute_tolerance() override { const std::map<Target, const std::map<DataType, float>> absolute_tolerance { @@ -663,21 +327,10 @@ private: } }; - if(user_value == -1) - { - return absolute_tolerance.at(_params.common_params.target).at(_params.convolution.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 { @@ -697,133 +350,38 @@ private: } }; - if(user_value == -1) - { - return absolute_tolerance.at(_params.common_params.target).at(_params.convolution.data_type); - } - return user_value; + return absolute_tolerance.at(_params.common_params.target).at(_params.data_type); } - - ExampleParams _params; }; -/** Generates appropriate convolution verify accessor - * - * @param[in] params User supplied parameters for convolution. - * - * @return A convolution verify accessor for the requested datatype. - */ -inline std::unique_ptr<graph::ITensorAccessor> get_convolution_verify_accessor(ExampleParams params) -{ - switch(params.convolution.data_type) - { - case DataType::QASYMM8: - { - return arm_compute::support::cpp14::make_unique<ConvolutionVerifyAccessor<uint8_t>>( - params); - } - case DataType::F16: - { - return arm_compute::support::cpp14::make_unique<ConvolutionVerifyAccessor<half>>( - params); - } - case DataType::F32: - { - return arm_compute::support::cpp14::make_unique<ConvolutionVerifyAccessor<float>>( - params); - } - default: - ARM_COMPUTE_ERROR("NOT SUPPORTED!"); - } -} -/** Generates appropriate accessor according to the specified graph parameters - * - * @param[in] graph_parameters Graph parameters - * @param[in] lower Lower random values bound - * @param[in] upper Upper random values bound - * @param[in] seed Random generator seed - * - * @return An appropriate tensor accessor - */ -inline std::unique_ptr<graph::ITensorAccessor> get_accessor(const TensorParams &tensor, PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0) -{ - if(!tensor.npy.empty()) - { - return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(tensor.npy); - } - else - { - return arm_compute::support::cpp14::make_unique<RandomAccessor>(lower, upper, seed); - } -} } // namespace -class GraphConvolutionValidateExample final : public ValidateExample +class GraphConvolutionValidateExample final : public GraphValidateExample<ConvolutionLayer, ConvolutionOptions, ConvolutionVerifyAccessor> { + using GraphValidateExample::graph; + public: GraphConvolutionValidateExample() - : graph(0, "Convolution Graph example") + : GraphValidateExample("Convolution Graph example") { } - bool do_setup(int argc, char **argv) override - { - CommandLineParser parser; - - ConvolutionOptions Options(parser); - parser.parse(argc, argv); - - ExampleParams params = consume_covolution_graph_parameters(Options); - - if(params.common_params.help) - { - parser.print_help(argv[0]); - return false; - } + ConvolutionLayer 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); - std::cout << params << std::endl; + 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); // Calculate padding information const PadStrideInfo padding_info = calculate_convolution_padding(params); - // Create input descriptor - const TensorShape input_shape = permute_shape(TensorShape(params.input.width, params.input.height, params.input.fm, params.input.batch), DataLayout::NCHW, params.convolution.data_layout); - TensorDescriptor input_descriptor = TensorDescriptor(input_shape, params.convolution.data_type, params.input.quant_info, params.convolution.data_layout); - - const PixelValue lower = PixelValue(params.input.range_low, params.convolution.data_type, params.input.quant_info); - const PixelValue upper = PixelValue(params.input.range_high, params.convolution.data_type, params.input.quant_info); - - const PixelValue weights_lower = PixelValue(params.weights.range_low, params.convolution.data_type, params.weights.quant_info); - const PixelValue weights_upper = PixelValue(params.weights.range_high, params.convolution.data_type, params.weights.quant_info); - - graph << params.common_params.target - << params.convolution.convolution_method - << InputLayer(input_descriptor, get_accessor(params.input, lower, upper, 0)) - << ConvolutionLayer(params.weights.width, params.weights.height, params.weights.fm, - get_accessor(params.weights, weights_lower, weights_upper, 1), - get_accessor(params.bias, lower, upper, 2), - padding_info, 1, params.weights.quant_info, params.output.quant_info) - << OutputLayer(get_convolution_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 - { + return ConvolutionLayer(params.weights.width, params.weights.height, params.weights.fm, + get_accessor(params.weights, weights_lower, weights_upper, 1), + get_accessor(params.bias, lower, upper, 2), + padding_info, 1, params.weights.quant_info, params.output.quant_info); } - -private: - Stream graph; }; /** Main program for Graph Convolution test |