From 4a6d9e85a9cb2e199d20b06e5450036c3b83b91d Mon Sep 17 00:00:00 2001 From: ramelg01 Date: Sat, 2 Oct 2021 14:34:36 +0100 Subject: Provide logging for configure functions in all CPP functions - Moving impl of CPPSplit template to src/runtime/CPP to allow including of Log.h from src/common. - Fix logging of vector to print contained tensor's info not their ptrs. Partially-Resovles: COMPMID-4718 Signed-off-by: Ramy Elgammal Change-Id: Idec81665b2a7c0cfae5248803109c6e2edc520a1 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6362 Comments-Addressed: Arm Jenkins Reviewed-by: Pablo Marquez Tello Tested-by: Arm Jenkins --- Android.bp | 1 + arm_compute/runtime/CPP/functions/CPPSplit.h | 135 +-------------- src/common/utils/Log.h | 6 +- .../CL/functions/CLBatchNormalizationLayer.cpp | 3 +- .../CPPBoxWithNonMaximaSuppressionLimit.cpp | 10 +- .../CPP/functions/CPPDetectionOutputLayer.cpp | 9 +- .../CPP/functions/CPPDetectionPostProcessLayer.cpp | 12 +- .../CPP/functions/CPPNonMaximumSuppression.cpp | 6 +- src/runtime/CPP/functions/CPPPermute.cpp | 6 +- src/runtime/CPP/functions/CPPSplit.cpp | 186 +++++++++++++++++++++ src/runtime/CPP/functions/CPPTopKV.cpp | 6 +- src/runtime/CPP/functions/CPPUpsample.cpp | 6 +- src/runtime/NEON/functions/NEUnstack.cpp | 2 +- utils/TypePrinter.h | 167 +++++++++++++----- 14 files changed, 363 insertions(+), 192 deletions(-) create mode 100644 src/runtime/CPP/functions/CPPSplit.cpp diff --git a/Android.bp b/Android.bp index 9b6808eb9a..00e0b39175 100644 --- a/Android.bp +++ b/Android.bp @@ -710,6 +710,7 @@ cc_library_static { "src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp", "src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp", "src/runtime/CPP/functions/CPPPermute.cpp", + "src/runtime/CPP/functions/CPPSplit.cpp", "src/runtime/CPP/functions/CPPTopKV.cpp", "src/runtime/CPP/functions/CPPUpsample.cpp", "src/runtime/IScheduler.cpp", diff --git a/arm_compute/runtime/CPP/functions/CPPSplit.h b/arm_compute/runtime/CPP/functions/CPPSplit.h index b2b4d07c86..b797b26960 100644 --- a/arm_compute/runtime/CPP/functions/CPPSplit.h +++ b/arm_compute/runtime/CPP/functions/CPPSplit.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2020 Arm Limited. + * Copyright (c) 2020-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -41,10 +41,8 @@ template class CPPSplit : public IFunction { public: - CPPSplit() - : _outputs_vector(), _slice_functions(), _num_outputs(0) - { - } + CPPSplit(); + /** Static function to check if given info will lead to a valid configuration of @ref CPPSplit * * @param[in] input The input tensor info. Data types supported: All. @@ -55,72 +53,7 @@ public: * * @return a status */ - static Status validate(const ITensorInfo *input, const std::vector &outputs, unsigned int axis) - { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); - ARM_COMPUTE_RETURN_ERROR_ON(axis >= input->num_dimensions()); - ARM_COMPUTE_RETURN_ERROR_ON(outputs.size() < 2); - - // Get output shape - TensorShape output_shape{}; - unsigned int total_output_shape_size = 0; - - // Sum the output sizes and fall back to evenly-sized splits if any are zero - const bool using_split_shapes = std::none_of(outputs.begin(), outputs.end(), [&total_output_shape_size](ITensorInfo * info) - { - unsigned int output_shape_size = info->tensor_shape().total_size(); - total_output_shape_size += output_shape_size; - return output_shape_size == 0; - }); - - if(using_split_shapes) - { - ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().total_size() != total_output_shape_size); - } - else - { - output_shape = arm_compute::misc::shape_calculator::compute_split_shape(input, axis, outputs.size()); - ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0); - } - - // Validate output tensors - unsigned int axis_offset = 0; - for(const auto &output : outputs) - { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); - if(using_split_shapes) - { - output_shape = output->tensor_shape(); - ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0); - } - - const size_t axis_split_step = output_shape[axis]; - - // Start/End coordinates - Coordinates start_coords; - Coordinates end_coords; - for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d) - { - end_coords.set(d, -1); - } - - // Output auto inizialitation if not yet initialized - TensorInfo tmp_output_info = *output->clone(); - if(tmp_output_info.tensor_shape().total_size() == 0) - { - tmp_output_info = input->clone()->set_is_resizable(true).set_tensor_shape(output_shape); - } - - // Update coordinate on axis - start_coords.set(axis, axis_offset); - end_coords.set(axis, axis_offset + axis_split_step); - - ARM_COMPUTE_RETURN_ON_ERROR(SliceType::validate(input, output, start_coords, end_coords)); - axis_offset += axis_split_step; - } - - return Status{}; - } + static Status validate(const ITensorInfo *input, const std::vector &outputs, unsigned int axis); /** Initialise the kernel's input and outputs. * @@ -130,65 +63,7 @@ public: * from the split dimension. * @param[in] axis Axis on which to split the input. */ - void configure(const TensorInterfaceType *input, const std::vector &outputs, unsigned int axis) - { - // Create Slice functions - _num_outputs = outputs.size(); - _slice_functions.resize(_num_outputs); - - // Extract output tensor info - std::vector outputs_info; - for(auto &output : outputs) - { - ARM_COMPUTE_ERROR_ON_NULLPTR(output); - outputs_info.emplace_back(output->info()); - } - - // If any of the outputs have a zero size, fall-back to using evenly-sized output splits - const bool outputs_have_sizes = std::none_of(outputs_info.begin(), outputs_info.end(), [](ITensorInfo * info) - { - return info->tensor_shape().total_size() == 0; - }); - - // Validate - ARM_COMPUTE_ERROR_THROW_ON(CPPSplit::validate(input->info(), outputs_info, axis)); - - unsigned int axis_offset = 0; - unsigned int i = 0; - - for(const auto &output_info : outputs_info) - { - // Get output shape - TensorShape output_shape = (outputs_have_sizes ? - output_info->tensor_shape() : - arm_compute::misc::shape_calculator::compute_split_shape(input->info(), axis, _num_outputs)); - - const size_t axis_split_step = output_shape[axis]; - - // Start/End coordinates - Coordinates start_coords; - Coordinates end_coords; - - for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d) - { - end_coords.set(d, -1); - } - - // Update coordinate on axis - start_coords.set(axis, axis_offset); - end_coords.set(axis, axis_offset + axis_split_step); - - // Configure slice function - _slice_functions[i].configure(input, outputs[i], start_coords, end_coords); - - // Set valid region from shape - outputs[i]->info()->set_valid_region(ValidRegion(Coordinates(), output_shape)); - - // Update axis offset - axis_offset += axis_split_step; - ++i; - } - } + void configure(const TensorInterfaceType *input, const std::vector &outputs, unsigned int axis); protected: std::vector _outputs_vector; diff --git a/src/common/utils/Log.h b/src/common/utils/Log.h index 5b049d0de6..f3ae38a57c 100644 --- a/src/common/utils/Log.h +++ b/src/common/utils/Log.h @@ -134,9 +134,9 @@ logParamsImpl(std::vector &data_registry, const std::tuple & /** Function Template with variable number of inputs to collect all the passed parameters from * the logging macro ARM_COMPUTE_LOG_PARAMS(...) * - * @param[in] ...ins The input parameters in the variadic template, taken by reference, (not by value) to avoid - * detecting T as an abstract data type when passing any of these parameters as L-value reference - * to an abstract type. + * @param[in] ...ins The input parameters in the variadic template, taken by universal references Ts.. &&, (not by value) + * to avoid detecting T as an abstract data type when passing any of these parameters as an L-value + * reference to an abstract type. * * @return Vector of the parameters' data in a string format */ diff --git a/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp b/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp index 234a0df2aa..e8affc0853 100644 --- a/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp +++ b/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp @@ -29,10 +29,11 @@ #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "src/common/utils/Log.h" #include "src/core/CL/kernels/CLBatchNormalizationLayerKernel.h" +#include "src/common/utils/Log.h" + namespace arm_compute { CLBatchNormalizationLayer::CLBatchNormalizationLayer() diff --git a/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp b/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp index b6803d0d37..dccbe4045d 100644 --- a/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp +++ b/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020 Arm Limited. + * Copyright (c) 2018-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -26,6 +26,8 @@ #include "arm_compute/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.h" #include "arm_compute/runtime/Scheduler.h" +#include "src/common/utils/Log.h" + namespace arm_compute { namespace @@ -130,10 +132,12 @@ CPPBoxWithNonMaximaSuppressionLimit::CPPBoxWithNonMaximaSuppressionLimit(std::sh { } -void CPPBoxWithNonMaximaSuppressionLimit::configure(const ITensor *scores_in, const ITensor *boxes_in, const ITensor *batch_splits_in, ITensor *scores_out, ITensor *boxes_out, ITensor *classes, - ITensor *batch_splits_out, ITensor *keeps, ITensor *keeps_size, const BoxNMSLimitInfo info) +void CPPBoxWithNonMaximaSuppressionLimit::configure(const ITensor *scores_in, const ITensor *boxes_in, const ITensor *batch_splits_in, + ITensor *scores_out, ITensor *boxes_out, ITensor *classes, ITensor *batch_splits_out, + ITensor *keeps, ITensor *keeps_size, const BoxNMSLimitInfo info) { ARM_COMPUTE_ERROR_ON_NULLPTR(scores_in, boxes_in, scores_out, boxes_out, classes); + ARM_COMPUTE_LOG_PARAMS(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes, batch_splits_out, keeps, keeps_size, info); _is_qasymm8 = scores_in->info()->data_type() == DataType::QASYMM8 || scores_in->info()->data_type() == DataType::QASYMM8_SIGNED; diff --git a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp index fdb4c9f0f6..41d875eb97 100644 --- a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020 Arm Limited. + * Copyright (c) 2018-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -28,6 +28,8 @@ #include "arm_compute/core/Validate.h" #include "src/core/helpers/AutoConfiguration.h" +#include "src/common/utils/Log.h" + #include namespace arm_compute @@ -388,9 +390,12 @@ CPPDetectionOutputLayer::CPPDetectionOutputLayer() { } -void CPPDetectionOutputLayer::configure(const ITensor *input_loc, const ITensor *input_conf, const ITensor *input_priorbox, ITensor *output, DetectionOutputLayerInfo info) +void CPPDetectionOutputLayer::configure(const ITensor *input_loc, const ITensor *input_conf, const ITensor *input_priorbox, + ITensor *output, DetectionOutputLayerInfo info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input_loc, input_conf, input_priorbox, output); + ARM_COMPUTE_LOG_PARAMS(input_loc, input_conf, input_priorbox, output, info); + // Output auto initialization if not yet initialized // Since the number of bboxes to kept is unknown before nms, the shape is set to the maximum // The maximum is keep_top_k * input_loc_size[1] diff --git a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp index 31f1fafd69..ecbc49b3c1 100644 --- a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -28,6 +28,8 @@ #include "arm_compute/core/Validate.h" #include "src/core/helpers/AutoConfiguration.h" +#include "src/common/utils/Log.h" + #include #include #include @@ -213,10 +215,14 @@ CPPDetectionPostProcessLayer::CPPDetectionPostProcessLayer(std::shared_ptrinfo(), TensorInfo(TensorShape(_kNumCoordBox, _num_max_detected_boxes, _kBatchSize), 1, DataType::F32)); diff --git a/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp b/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp index d0d0b1e98b..6d01b127c0 100644 --- a/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp +++ b/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -25,12 +25,16 @@ #include "arm_compute/core/CPP/kernels/CPPNonMaximumSuppressionKernel.h" +#include "src/common/utils/Log.h" + namespace arm_compute { void CPPNonMaximumSuppression::configure( const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, const float score_threshold, const float nms_threshold) { + ARM_COMPUTE_LOG_PARAMS(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold); + auto k = std::make_unique(); k->configure(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold); _kernel = std::move(k); diff --git a/src/runtime/CPP/functions/CPPPermute.cpp b/src/runtime/CPP/functions/CPPPermute.cpp index 76fa09f12b..83941f1dc1 100644 --- a/src/runtime/CPP/functions/CPPPermute.cpp +++ b/src/runtime/CPP/functions/CPPPermute.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -25,10 +25,14 @@ #include "arm_compute/core/CPP/kernels/CPPPermuteKernel.h" +#include "src/common/utils/Log.h" + using namespace arm_compute; void CPPPermute::configure(const ITensor *input, ITensor *output, const PermutationVector &perm) { + ARM_COMPUTE_LOG_PARAMS(input, output, perm); + auto k = std::make_unique(); k->configure(input, output, perm); _kernel = std::move(k); diff --git a/src/runtime/CPP/functions/CPPSplit.cpp b/src/runtime/CPP/functions/CPPSplit.cpp new file mode 100644 index 0000000000..98af8ad971 --- /dev/null +++ b/src/runtime/CPP/functions/CPPSplit.cpp @@ -0,0 +1,186 @@ +/* + * Copyright (c) 2021 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/runtime/CPP/functions/CPPSplit.h" + +#ifdef ARM_COMPUTE_CPU_ENABLED // NEON Build is activated +#include "arm_compute/runtime/NEON/functions/NESlice.h" +#endif /* ARM_COMPUTE_CPU_ENABLED */ + +#ifdef ARM_COMPUTE_OPENCL_ENABLED // OPENCL build is activated +#include "arm_compute/runtime/CL/functions/CLSlice.h" +#endif /* ARM_COMPUTE_OPENCL_ENABLED */ + +#include "src/common/utils/Log.h" + +namespace arm_compute +{ +/** Basic function to split a tensor along a given axis */ + +template +CPPSplit::CPPSplit() + : _outputs_vector(), _slice_functions(), _num_outputs(0) +{ +} + +template +Status CPPSplit::validate(const ITensorInfo *input, const std::vector &outputs, unsigned int axis) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); + ARM_COMPUTE_RETURN_ERROR_ON(axis >= input->num_dimensions()); + ARM_COMPUTE_RETURN_ERROR_ON(outputs.size() < 2); + + // Get output shape + TensorShape output_shape{}; + unsigned int total_output_shape_size = 0; + + // Sum the output sizes and fall back to evenly-sized splits if any are zero + const bool using_split_shapes = std::none_of(outputs.begin(), outputs.end(), [&total_output_shape_size](ITensorInfo * info) + { + unsigned int output_shape_size = info->tensor_shape().total_size(); + total_output_shape_size += output_shape_size; + return output_shape_size == 0; + }); + + if(using_split_shapes) + { + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().total_size() != total_output_shape_size); + } + else + { + output_shape = arm_compute::misc::shape_calculator::compute_split_shape(input, axis, outputs.size()); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0); + } + + // Validate output tensors + unsigned int axis_offset = 0; + for(const auto &output : outputs) + { + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); + if(using_split_shapes) + { + output_shape = output->tensor_shape(); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0); + } + + const size_t axis_split_step = output_shape[axis]; + + // Start/End coordinates + Coordinates start_coords; + Coordinates end_coords; + for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d) + { + end_coords.set(d, -1); + } + + // Output auto inizialitation if not yet initialized + TensorInfo tmp_output_info = *output->clone(); + if(tmp_output_info.tensor_shape().total_size() == 0) + { + tmp_output_info = input->clone()->set_is_resizable(true).set_tensor_shape(output_shape); + } + + // Update coordinate on axis + start_coords.set(axis, axis_offset); + end_coords.set(axis, axis_offset + axis_split_step); + + ARM_COMPUTE_RETURN_ON_ERROR(SliceType::validate(input, output, start_coords, end_coords)); + axis_offset += axis_split_step; + } + + return Status{}; +} + +template +void CPPSplit::configure(const TensorInterfaceType *input, const std::vector &outputs, unsigned int axis) +{ + // (TensorInterfaceType*) + ARM_COMPUTE_LOG_PARAMS(input, outputs, axis); + + // Create Slice functions + _num_outputs = outputs.size(); + _slice_functions.resize(_num_outputs); + + // Extract output tensor info + std::vector outputs_info; + for(auto &output : outputs) + { + ARM_COMPUTE_ERROR_ON_NULLPTR(output); + outputs_info.emplace_back(output->info()); + } + + // If any of the outputs have a zero size, fall-back to using evenly-sized output splits + const bool outputs_have_sizes = std::none_of(outputs_info.begin(), outputs_info.end(), [](ITensorInfo * info) + { + return info->tensor_shape().total_size() == 0; + }); + + // Validate + ARM_COMPUTE_ERROR_THROW_ON(CPPSplit::validate(input->info(), outputs_info, axis)); + + unsigned int axis_offset = 0; + unsigned int i = 0; + + for(const auto &output_info : outputs_info) + { + // Get output shape + TensorShape output_shape = (outputs_have_sizes ? + output_info->tensor_shape() : + arm_compute::misc::shape_calculator::compute_split_shape(input->info(), axis, _num_outputs)); + + const size_t axis_split_step = output_shape[axis]; + + // Start/End coordinates + Coordinates start_coords; + Coordinates end_coords; + + for(unsigned int d = 0; d < output_shape.num_dimensions(); ++d) + { + end_coords.set(d, -1); + } + + // Update coordinate on axis + start_coords.set(axis, axis_offset); + end_coords.set(axis, axis_offset + axis_split_step); + + // Configure slice function + _slice_functions[i].configure(input, outputs[i], start_coords, end_coords); + + // Set valid region from shape + outputs[i]->info()->set_valid_region(ValidRegion(Coordinates(), output_shape)); + + // Update axis offset + axis_offset += axis_split_step; + ++i; + } +} + +// Instantiate CPPSplit for NESlice and CLSlice types to enable linking to the above templated CPPSplit's methods +#ifdef ARM_COMPUTE_CPU_ENABLED // NEON Build is activated +template class CPPSplit; +#endif /* ARM_COMPUTE_CPU_ENABLED */ + +#ifdef ARM_COMPUTE_OPENCL_ENABLED // OPENCL build is activated +template class CPPSplit; +#endif /* ARM_COMPUTE_OPENCL_ENABLED */ +} // namespace arm_compute diff --git a/src/runtime/CPP/functions/CPPTopKV.cpp b/src/runtime/CPP/functions/CPPTopKV.cpp index 2547e56a1d..62a74735a2 100644 --- a/src/runtime/CPP/functions/CPPTopKV.cpp +++ b/src/runtime/CPP/functions/CPPTopKV.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020 Arm Limited. + * Copyright (c) 2019-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -25,10 +25,14 @@ #include "arm_compute/core/CPP/kernels/CPPTopKVKernel.h" +#include "src/common/utils/Log.h" + namespace arm_compute { void CPPTopKV::configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k) { + ARM_COMPUTE_LOG_PARAMS(predictions, targets, output, k); + auto kernel = std::make_unique(); kernel->configure(predictions, targets, output, k); _kernel = std::move(kernel); diff --git a/src/runtime/CPP/functions/CPPUpsample.cpp b/src/runtime/CPP/functions/CPPUpsample.cpp index 3b4ba2ba42..8f72473aeb 100644 --- a/src/runtime/CPP/functions/CPPUpsample.cpp +++ b/src/runtime/CPP/functions/CPPUpsample.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -25,10 +25,14 @@ #include "arm_compute/core/CPP/kernels/CPPUpsampleKernel.h" +#include "src/common/utils/Log.h" + using namespace arm_compute; void CPPUpsample::configure(const ITensor *input, ITensor *output, const PadStrideInfo &info) { + ARM_COMPUTE_LOG_PARAMS(input, output, info); + auto k = std::make_unique(); k->configure(input, output, info); _kernel = std::move(k); diff --git a/src/runtime/NEON/functions/NEUnstack.cpp b/src/runtime/NEON/functions/NEUnstack.cpp index 176b17f1f5..0ffab5e92a 100644 --- a/src/runtime/NEON/functions/NEUnstack.cpp +++ b/src/runtime/NEON/functions/NEUnstack.cpp @@ -71,7 +71,7 @@ void NEUnstack::configure(const ITensor *input, const std::vector &ou ARM_COMPUTE_ERROR_ON_NULLPTR(input); ARM_COMPUTE_ERROR_THROW_ON(NEUnstack::validate(input->info(), outputs_vector_info, axis)); - ARM_COMPUTE_LOG_PARAMS(input, output_vector, outputs_vector_info, axis); + ARM_COMPUTE_LOG_PARAMS(input, output_vector, axis); // Wrap around negative values const unsigned int axis_u = wrap_axis(axis, input->info()); diff --git a/utils/TypePrinter.h b/utils/TypePrinter.h index 23df2dc20c..5fa92e6360 100644 --- a/utils/TypePrinter.h +++ b/utils/TypePrinter.h @@ -67,7 +67,22 @@ std::string to_string_if_not_null(T *arg) } } +/** Fallback method: try to use std::to_string: + * + * @param[in] val Value to convert to string + * + * @return String representing val. + */ +template +inline std::string to_string(const T &val) +{ + return support::cpp11::to_string(val); +} + /** Formatted output of a vector of objects. + * + * @note: Using the overloaded to_string() instead of overloaded operator<<(), because to_string() functions are + * overloaded for all types, where two or more of them can use the same operator<<(), ITensor is an example. * * @param[out] os Output stream * @param[in] args Vector of objects to print @@ -75,7 +90,7 @@ std::string to_string_if_not_null(T *arg) * @return Modified output stream. */ template -inline ::std::ostream &operator<<(::std::ostream &os, const std::vector &args) +::std::ostream &operator<<(::std::ostream &os, const std::vector &args) { const size_t max_print_size = 5U; @@ -96,7 +111,7 @@ inline ::std::ostream &operator<<(::std::ostream &os, const std::vector &args { os << ", "; } - os << args[i]; + os << to_string(args[i]); } if(i < args.size()) { @@ -106,6 +121,20 @@ inline ::std::ostream &operator<<(::std::ostream &os, const std::vector &args return os; } +/** Formatted output of a vector of objects. + * + * @param[in] args Vector of objects to print + * + * @return String representing args. + */ +template +std::string to_string(const std::vector &args) +{ + std::stringstream str; + str << args; + return str.str(); +} + /** Formatted output of the Dimensions type. * * @param[out] os Output stream. @@ -1072,7 +1101,7 @@ inline ::std::ostream &operator<<(std::ostream &os, const ITensorInfo *info) os << "Shape=" << info->tensor_shape() << "," << "DataLayout=" << string_from_data_layout(data_layout) << "," - << "DataType=" << string_from_data_type(data_type) << ","; + << "DataType=" << string_from_data_type(data_type); if(is_data_type_quantized(data_type)) { @@ -1080,7 +1109,7 @@ inline ::std::ostream &operator<<(std::ostream &os, const ITensorInfo *info) const auto scales = qinfo.scale(); const auto offsets = qinfo.offset(); - os << "QuantizationInfo={" + os << ", QuantizationInfo={" << "scales.size=" << scales.size() << ", scale(s)=" << scales << ", "; @@ -2241,20 +2270,6 @@ inline ::std::ostream &operator<<(::std::ostream &os, const PriorBoxLayerInfo &i return os; } -/** Formatted output of a vector of objects. - * - * @param[in] args Vector of objects to print - * - * @return String representing args. - */ -template -std::string to_string(const std::vector &args) -{ - std::stringstream str; - str << args; - return str.str(); -} - /** Formatted output of the WinogradInfo type. */ inline ::std::ostream &operator<<(::std::ostream &os, const WinogradInfo &info) { @@ -2273,18 +2288,6 @@ inline std::string to_string(const WinogradInfo &type) return str.str(); } -/** Fallback method: try to use std::to_string: - * - * @param[in] val Value to convert to string - * - * @return String representing val. - */ -template -inline std::string to_string(const T &val) -{ - return support::cpp11::to_string(val); -} - /** Convert a CLTunerMode value to a string * * @param val CLTunerMode value to be converted @@ -2782,20 +2785,20 @@ inline std::string to_string(const SoftmaxKernelInfo &info) * @return Modified output stream. */ template -inline ::std::ostream &operator<<(::std::ostream &os, const LSTMParams &lstm_params) -{ - os << "{input_to_input_weights=" << lstm_params.input_to_input_weights() << ", " - << "recurrent_to_input_weights=" << lstm_params.recurrent_to_input_weights() << ", " - << "cell_to_input_weights=" << lstm_params.cell_to_input_weights() << ", " - << "input_gate_bias=" << lstm_params.input_gate_bias() << ", " - << "cell_to_forget_weights=" << lstm_params.cell_to_forget_weights() << ", " - << "cell_to_output_weights=" << lstm_params.cell_to_output_weights() << ", " - << "projection_weights=" << lstm_params.projection_weights() << ", " - << "projection_bias=" << lstm_params.projection_bias() << ", " - << "input_layer_norm_weights=" << lstm_params.input_layer_norm_weights() << ", " - << "forget_layer_norm_weights=" << lstm_params.forget_layer_norm_weights() << ", " - << "cell_layer_norm_weights=" << lstm_params.cell_layer_norm_weights() << ", " - << "output_layer_norm_weights=" << lstm_params.output_layer_norm_weights() << ", " +::std::ostream &operator<<(::std::ostream &os, const LSTMParams &lstm_params) +{ + os << "{input_to_input_weights=" << to_string(lstm_params.input_to_input_weights()) << ", " + << "recurrent_to_input_weights=" << to_string(lstm_params.recurrent_to_input_weights()) << ", " + << "cell_to_input_weights=" << to_string(lstm_params.cell_to_input_weights()) << ", " + << "input_gate_bias=" << to_string(lstm_params.input_gate_bias()) << ", " + << "cell_to_forget_weights=" << to_string(lstm_params.cell_to_forget_weights()) << ", " + << "cell_to_output_weights=" << to_string(lstm_params.cell_to_output_weights()) << ", " + << "projection_weights=" << to_string(lstm_params.projection_weights()) << ", " + << "projection_bias=" << to_string(lstm_params.projection_bias()) << ", " + << "input_layer_norm_weights=" << to_string(lstm_params.input_layer_norm_weights()) << ", " + << "forget_layer_norm_weights=" << to_string(lstm_params.forget_layer_norm_weights()) << ", " + << "cell_layer_norm_weights=" << to_string(lstm_params.cell_layer_norm_weights()) << ", " + << "output_layer_norm_weights=" << to_string(lstm_params.output_layer_norm_weights()) << ", " << "cell_clip=" << lstm_params.cell_clip() << ", " << "projection_clip=" << lstm_params.projection_clip() << ", " << "input_intermediate_scale=" << lstm_params.input_intermediate_scale() << ", " @@ -2817,7 +2820,7 @@ inline ::std::ostream &operator<<(::std::ostream &os, const LSTMParams &lstm_ * @return String representing the corresponding LSTMParams */ template -inline std::string to_string(const LSTMParams &lstm_params) +std::string to_string(const LSTMParams &lstm_params) { std::stringstream str; str << lstm_params; @@ -2836,6 +2839,80 @@ inline std::string to_string(const uint8_t num) return ::std::to_string(static_cast(num)); } +/** Available non maxima suppression types */ +/** Formatted output of the NMSType type. + * + * @param[out] os Output stream. + * @param[in] nms_type NMSType to output. + * + * @return Modified output stream. + */ +inline ::std::ostream &operator<<(::std::ostream &os, const NMSType &nms_type) +{ + switch(nms_type) + { + case NMSType::LINEAR: + os << "LINEAR"; + break; + case NMSType::GAUSSIAN: + os << "GAUSSIAN"; + break; + case NMSType::ORIGINAL: + os << "ORIGINAL"; + break; + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); + } + return os; +} + +/** Converts a @ref NMSType to string + * + * @param[in] nms_type NMSType value to be converted + * + * @return String representing the corresponding NMSType + */ +inline std::string to_string(const NMSType nms_type) +{ + std::stringstream str; + str << nms_type; + return str.str(); +} + +/** Formatted output of the BoxNMSLimitInfo type. + * + * @param[out] os Output stream. + * @param[in] info BoxNMSLimitInfo to output. + * + * @return Modified output stream. + */ +inline ::std::ostream &operator<<(::std::ostream &os, const BoxNMSLimitInfo &info) +{ + os << "{score_thresh = " << info.score_thresh() << ", " + << "nms = " << info.nms() << ", " + << "detections_per_im = " << info.detections_per_im() << ", " + << "soft_nms_enabled = " << info.soft_nms_enabled() << ", " + << "soft_nms_min_score_thres = " << info.soft_nms_min_score_thres() << ", " + << "suppress_size = " << info.suppress_size() << ", " + << "min_size = " << info.min_size() << ", " + << "im_width = " << info.im_width() << ", " + << "im_height = " << info.im_height() << "}"; + return os; +} + +/** Converts a @ref BoxNMSLimitInfo to string + * + * @param[in] info BoxNMSLimitInfo value to be converted + * + * @return String representing the corresponding BoxNMSLimitInfo + */ +inline std::string to_string(const BoxNMSLimitInfo &info) +{ + std::stringstream str; + str << info; + return str.str(); +} + } // namespace arm_compute #endif /* __ARM_COMPUTE_TYPE_PRINTER_H__ */ -- cgit v1.2.1