diff options
author | Georgios Pinitas <georgios.pinitas@arm.com> | 2018-04-03 13:44:29 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:16 +0000 |
commit | d9eb27597eabe5b7c17520f4f9b3f8a282d72573 (patch) | |
tree | 9b2b7d74b0ef83623b18d6d4279a564e5b63d641 /src/graph2/backends | |
parent | a8ca2b0cfe052c9a28b691317a674f28f495c139 (diff) | |
download | ComputeLibrary-d9eb27597eabe5b7c17520f4f9b3f8a282d72573.tar.gz |
COMPMID-797: Switch to new graph.
- Cleaned up build system
Change-Id: If2faa27ee5b31fa8b972836960ab3ef671059c8d
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/126435
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Diffstat (limited to 'src/graph2/backends')
-rw-r--r-- | src/graph2/backends/BackendRegistry.cpp | 63 | ||||
-rw-r--r-- | src/graph2/backends/CL/CLDeviceBackend.cpp | 175 | ||||
-rw-r--r-- | src/graph2/backends/CL/CLFunctionsFactory.cpp | 590 | ||||
-rw-r--r-- | src/graph2/backends/CL/CLNodeValidator.cpp | 64 | ||||
-rw-r--r-- | src/graph2/backends/CL/CLSubTensorHandle.cpp | 78 | ||||
-rw-r--r-- | src/graph2/backends/CL/CLTensorHandle.cpp | 78 | ||||
-rw-r--r-- | src/graph2/backends/GLES/GCDeviceBackend.cpp | 133 | ||||
-rw-r--r-- | src/graph2/backends/GLES/GCFunctionsFactory.cpp | 507 | ||||
-rw-r--r-- | src/graph2/backends/GLES/GCNodeValidator.cpp | 122 | ||||
-rw-r--r-- | src/graph2/backends/GLES/GCTensorHandle.cpp | 78 | ||||
-rw-r--r-- | src/graph2/backends/NEON/NEDeviceBackend.cpp | 141 | ||||
-rw-r--r-- | src/graph2/backends/NEON/NEFunctionFactory.cpp | 563 | ||||
-rw-r--r-- | src/graph2/backends/NEON/NENodeValidator.cpp | 65 | ||||
-rw-r--r-- | src/graph2/backends/NEON/NESubTensorHandle.cpp | 75 | ||||
-rw-r--r-- | src/graph2/backends/NEON/NETensorHandle.cpp | 77 |
15 files changed, 0 insertions, 2809 deletions
diff --git a/src/graph2/backends/BackendRegistry.cpp b/src/graph2/backends/BackendRegistry.cpp deleted file mode 100644 index 5f1218f335..0000000000 --- a/src/graph2/backends/BackendRegistry.cpp +++ /dev/null @@ -1,63 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/BackendRegistry.h" - -using namespace arm_compute::graph2::backends; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -BackendRegistry::BackendRegistry() - : _registered_backends() -{ -} - -BackendRegistry &BackendRegistry::get() -{ - static BackendRegistry instance; - return instance; -} - -IDeviceBackend *BackendRegistry::find_backend(Target target) -{ - ARM_COMPUTE_ERROR_ON(!contains(target)); - return _registered_backends[target].get(); -} - -bool BackendRegistry::contains(Target target) const -{ - auto it = _registered_backends.find(target); - return (it != _registered_backends.end()); -} - -const std::map<Target, std::unique_ptr<IDeviceBackend>> &BackendRegistry::backends() const -{ - return _registered_backends; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute diff --git a/src/graph2/backends/CL/CLDeviceBackend.cpp b/src/graph2/backends/CL/CLDeviceBackend.cpp deleted file mode 100644 index 71566d2f1f..0000000000 --- a/src/graph2/backends/CL/CLDeviceBackend.cpp +++ /dev/null @@ -1,175 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/CL/CLDeviceBackend.h" - -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/GraphContext.h" -#include "arm_compute/graph2/INode.h" -#include "arm_compute/graph2/Logger.h" -#include "arm_compute/graph2/Tensor.h" -#include "arm_compute/graph2/backends/BackendRegistrar.h" -#include "arm_compute/graph2/backends/CL/CLFunctionFactory.h" -#include "arm_compute/graph2/backends/CL/CLNodeValidator.h" -#include "arm_compute/graph2/backends/CL/CLSubTensorHandle.h" -#include "arm_compute/graph2/backends/CL/CLTensorHandle.h" - -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/runtime/BlobLifetimeManager.h" -#include "arm_compute/runtime/CL/CLBufferAllocator.h" -#include "arm_compute/runtime/CL/CLScheduler.h" -#include "arm_compute/runtime/MemoryManagerOnDemand.h" -#include "arm_compute/runtime/PoolManager.h" - -#include "support/ToolchainSupport.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -namespace -{ -bool file_exists(const std::string &filename) -{ - std::ifstream file(filename); - return file.good(); -} -} // namespace - -/** Register CL backend */ -static detail::BackendRegistrar<CLDeviceBackend> CLDeviceBackend_registrar(Target::CL); - -/** Tuner export file */ -static const std::string tuner_data_filename = "acl_tuner.csv"; - -CLDeviceBackend::CLDeviceBackend() - : _tuner(), _allocator(cl::Context::getDefault()) -{ -} - -CLDeviceBackend::~CLDeviceBackend() -{ - // TODO (geopin01) : Shouldn't call non exception safe stuff here - if(_tuner.tune_new_kernels() && !_tuner.lws_table().empty()) - { - _tuner.save_to_file(tuner_data_filename); - } -} - -void CLDeviceBackend::set_kernel_tuning(bool enable_tuning) -{ - _tuner.set_tune_new_kernels(enable_tuning); -} - -void CLDeviceBackend::initialize_backend() -{ - // Load tuner data if available - if(_tuner.lws_table().empty() && file_exists(tuner_data_filename)) - { - _tuner.load_from_file(tuner_data_filename); - } - - // Setup Scheduler - CLScheduler::get().default_init(&_tuner); - - // Create allocator with new context - _allocator = CLBufferAllocator(); -} - -void CLDeviceBackend::setup_backend_context(GraphContext &ctx) -{ - // Setup tuner - set_kernel_tuning(ctx.config().use_tuner); - - // Setup a management backend - if(ctx.memory_management_ctx(Target::CL) == nullptr) - { - MemoryManagerContext mm_ctx; - mm_ctx.target = Target::CL; - mm_ctx.mm = create_memory_manager(MemoryManagerAffinity::Buffer); - - ctx.insert_memory_management_ctx(std::move(mm_ctx)); - } -} - -std::unique_ptr<ITensorHandle> CLDeviceBackend::create_tensor(const Tensor &tensor) -{ - // Get tensor descriptor - const TensorDescriptor &tensor_desc = tensor.desc(); - ARM_COMPUTE_ERROR_ON(tensor_desc.target != Target::CL); - - // Create backend tensor handle - TensorInfo info(tensor_desc.shape, 1, tensor_desc.data_type); - auto backend_tensor_handle = support::cpp14::make_unique<CLTensorHandle>(info); - - return std::move(backend_tensor_handle); -} - -std::unique_ptr<ITensorHandle> CLDeviceBackend::create_subtensor(ITensorHandle *parent, TensorShape shape, Coordinates coords, bool extend_parent) -{ - if(parent == nullptr) - { - return nullptr; - } - - return support::cpp14::make_unique<CLSubTensorHandle>(parent, shape, coords, extend_parent); -} - -std::unique_ptr<arm_compute::IFunction> CLDeviceBackend::configure_node(INode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Configuring CL node with ID : " << node.id() << std::endl); - ARM_COMPUTE_ERROR_ON(node.assigned_target() != Target::CL); - - // Configure node - return CLFunctionFactory::create(&node, ctx); -} - -arm_compute::Status CLDeviceBackend::validate_node(INode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating CL node with ID : " << node.id() << std::endl); - ARM_COMPUTE_ERROR_ON(node.assigned_target() != Target::CL); - - return CLNodeValidator::validate(&node); -} - -std::shared_ptr<arm_compute::IMemoryManager> CLDeviceBackend::create_memory_manager(MemoryManagerAffinity affinity) -{ - if(affinity == MemoryManagerAffinity::Offset) - { - ARM_COMPUTE_LOG_GRAPH_WARNING("CL Backend does not support offset affinity memory management!"); - return nullptr; - } - - auto lifetime_mgr = std::make_shared<BlobLifetimeManager>(); - auto pool_mgr = std::make_shared<PoolManager>(); - auto mm = std::make_shared<MemoryManagerOnDemand>(lifetime_mgr, pool_mgr); - - mm->set_allocator(&_allocator); - - return mm; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/CL/CLFunctionsFactory.cpp b/src/graph2/backends/CL/CLFunctionsFactory.cpp deleted file mode 100644 index 5a51b19e18..0000000000 --- a/src/graph2/backends/CL/CLFunctionsFactory.cpp +++ /dev/null @@ -1,590 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/CL/CLFunctionFactory.h" - -#include "arm_compute/core/utils/misc/Cast.h" -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/GraphContext.h" -#include "arm_compute/graph2/Logger.h" -#include "arm_compute/graph2/TypePrinter.h" -#include "arm_compute/graph2/Types.h" -#include "arm_compute/graph2/backends/Utils.h" -#include "arm_compute/graph2/nodes/Nodes.h" -#include "arm_compute/runtime/CL/CLFunctions.h" - -#include "support/ToolchainSupport.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -namespace -{ -/** Returns backing tensor of a given tensor - * - * @param[in] tensor Tensor to extract the backing tensor from - * - * @return Backing tensor if present else nullptr - */ -arm_compute::ICLTensor *get_backing_tensor(arm_compute::graph2::Tensor *tensor) -{ - arm_compute::ICLTensor *backing_tensor = nullptr; - if(tensor != nullptr) - { - ARM_COMPUTE_ERROR_ON(tensor->desc().target != arm_compute::graph2::Target::CL); - // Get backing tensor handle - ITensorHandle *tensor_handle = tensor->handle(); - // Get backing tensor - backing_tensor = (tensor_handle != nullptr) ? polymorphic_cast<ICLTensor *>(&tensor_handle->tensor()) : nullptr; - } - - return backing_tensor; -} - -/** Create a backend activation layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend activation layer function - */ -std::unique_ptr<IFunction> create_activation_layer(ActivationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL ActivationLayerNode node with ID : " << node.id() << " and Name: " << node.name() - << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const ActivationLayerInfo act_info = node.activation_info(); - - // Create function - auto func = support::cpp14::make_unique<CLActivationLayer>(); - func->configure(input, output, act_info); - - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLActivationLayer" - << " Data Type: " << input->info()->data_type() - << " Shape: " << input->info()->tensor_shape() - << " Activation function: " << act_info.activation() - << " a: " << act_info.a() - << " b: " << act_info.b() - << " InPlace : " << is_in_place_operation(input, output) - << std::endl); - - return std::move(func); -} - -/** Create a backend batch normalization layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend batch normalization layer function - */ -std::unique_ptr<IFunction> create_batch_normalization_layer(BatchNormalizationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating CL BatchNormalization node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - - // TODO (geopin01) : Var and mean are compulsory, switch function to accept nullptr as beta and/or gamma - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 5); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *mean = get_backing_tensor(node.input(1)); - ICLTensor *var = get_backing_tensor(node.input(2)); - ICLTensor *beta = get_backing_tensor(node.input(3)); - ICLTensor *gamma = get_backing_tensor(node.input(4)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const float epsilon = node.epsilon(); - const ActivationLayerInfo fused_act = node.fused_activation(); - - // Create and configure function - auto func = support::cpp14::make_unique<CLBatchNormalizationLayer>(); - func->configure(input, output, mean, var, beta, gamma, epsilon, fused_act); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLBatchNormalizationLayer" - << " Data Type: " << input->info()->data_type() - << " Shape: " << input->info()->tensor_shape() - << " Epsilon: " << epsilon << " " - << (fused_act.enabled() ? to_string(fused_act.activation()) : "") - << " InPlace : " << is_in_place_operation(input, output) - << std::endl); - - return std::move(func); -} - -/** Create a backend convolution layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend convolution layer function - */ -std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating CL ConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *weights = get_backing_tensor(node.input(1)); - ICLTensor *biases = get_backing_tensor(node.input(2)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const PadStrideInfo conv_info = node.convolution_info(); - const ConvolutionMethod conv_algorithm = node.convolution_method(); - - // Create and configure function (we assume that functions have been validated before creation) - std::shared_ptr<IMemoryManager> mm = get_memory_manager(ctx, Target::CL); - std::unique_ptr<IFunction> func; - std::string func_name; - - if(conv_algorithm == ConvolutionMethod::WINOGRAD) - { - std::tie(func, func_name) = create_named_function<CLWinogradConvolutionLayer>( - std::string("CLWinogradConvolutionLayer"), input, weights, biases, output, conv_info); - } - else if(conv_algorithm == ConvolutionMethod::DIRECT) - { - std::tie(func, func_name) = create_named_function<CLDirectConvolutionLayer>( - std::string("CLDirectConvolutionLayer"), input, weights, biases, output, conv_info); - } - else if(conv_algorithm == ConvolutionMethod::GEMM) - { - std::tie(func, func_name) = create_named_memory_managed_function<CLGEMMConvolutionLayer>(std::string("CLGEMMConvolutionLayer"), mm, - input, weights, biases, output, conv_info); - } - else - { - std::tie(func, func_name) = create_named_memory_managed_function<CLConvolutionLayer>(std::string("CLConvolutionLayer"), mm, - input, weights, biases, output, conv_info); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - return func; -} - -/** Create a backend layer depth concatenate function - * - * @param[in] node Node to create the backend function for - * - * @return Backend depth concatenate layer function - */ -std::unique_ptr<arm_compute::IFunction> create_depth_concatenate_layer(DepthConcatenateLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating CL DepthConcatenate node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Return nullptr if depth concatenate is switched off - if(!node.is_enabled()) - { - return nullptr; - } - - // Extract IO and info - std::vector<arm_compute::ICLTensor *> inputs; - for(unsigned int i = 0; i < node.num_inputs(); ++i) - { - inputs.push_back(get_backing_tensor(node.input(i))); - } - ICLTensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<CLDepthConcatenateLayer>(); - func->configure(inputs, output); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLDepthConcatenateLayer" - << " Data Type: " << output->info()->data_type() - << " Shape: " << output->info()->tensor_shape() - << " Num Inputs: " << inputs.size() - << std::endl); - - return std::move(func); -} - -/** Create a backend layer depth-wise convolution function - * - * @param[in] node Node to create the backend function for - * - * @return Backend depth-wise convolution layer function - */ -std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvolutionLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL DepthwiseConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() - << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *weights = get_backing_tensor(node.input(1)); - ICLTensor *biases = get_backing_tensor(node.input(2)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const PadStrideInfo conv_info = node.convolution_info(); - const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); - - // Create and configure function (we assume that functions have been validated before creation) - std::unique_ptr<IFunction> func; - std::string func_name; - if(dwc_algorithm == DepthwiseConvolutionMethod::OPTIMIZED_3x3) - { - std::tie(func, func_name) = create_named_function<CLDepthwiseConvolutionLayer3x3>( - std::string("CLDepthwiseConvolutionLayer3x3"), input, weights, biases, output, conv_info); - } - else - { - std::tie(func, func_name) = create_named_function<CLDepthwiseConvolutionLayer>( - std::string("CLDepthwiseConvolutionLayer"), input, weights, biases, output, conv_info); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - return func; -} - -/** Create a backend element-wise operation layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend element-wise operation layer function - */ -std::unique_ptr<IFunction> create_eltwise_layer(EltwiseLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL EltwiseLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 2); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input1 = get_backing_tensor(node.input(0)); - ICLTensor *input2 = get_backing_tensor(node.input(1)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const EltwiseOperation eltwise_op = node.eltwise_operation(); - ARM_COMPUTE_ERROR_ON(input1 == nullptr); - ARM_COMPUTE_ERROR_ON(input2 == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - std::unique_ptr<IFunction> func = nullptr; - std::string func_name; - if(eltwise_op == EltwiseOperation::ADD) - { - std::tie(func, func_name) = create_named_function<CLArithmeticAddition>(std::string("CLArithmeticAddition"), - input1, input2, output, - ConvertPolicy::SATURATE); - } - else if(eltwise_op == EltwiseOperation::SUB) - { - std::tie(func, func_name) = create_named_function<CLArithmeticSubtraction>( - std::string("CLArithmeticSubtraction"), input1, input2, output, ConvertPolicy::SATURATE); - } - else if(eltwise_op == EltwiseOperation::MUL) - { - std::tie(func, func_name) = create_named_function<CLPixelWiseMultiplication>( - std::string("CLPixelWiseMultiplication"), input1, input2, output, 1.f, ConvertPolicy::SATURATE, - RoundingPolicy::TO_NEAREST_EVEN); - } - else - { - ARM_COMPUTE_ERROR("Unsupported element-wise operation!"); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input1->info()->data_type() - << " Shape : " << input1->info()->tensor_shape() - << std::endl); - - return func; -} - -/** Create a backend flatten layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend flatten layer function - */ -std::unique_ptr<IFunction> create_flatten_layer(FlattenLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL FlattenLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<CLFlattenLayer>(); - func->configure(input, output); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLFlattenLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend fully connected layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend fully connected layer function - */ -std::unique_ptr<IFunction> create_fully_connected_layer(FullyConnectedLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL FullyConnectedLayer node with ID : " << node.id() << " and Name: " << node.name() - << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *weights = get_backing_tensor(node.input(1)); - ICLTensor *biases = get_backing_tensor(node.input(2)); - ICLTensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<CLFullyConnectedLayer>(get_memory_manager(ctx, Target::CL)); - func->configure(input, weights, biases, output); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(weights == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLFullyConnectedLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Biases Shape: " << biases->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend normalization layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend normalization layer function - */ -std::unique_ptr<IFunction> create_normalization_layer(NormalizationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL NormalizationLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const NormalizationLayerInfo norm_info = node.normalization_info(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<CLNormalizationLayer>(); - func->configure(input, output, norm_info); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLNormalizationLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Normalization info: " << norm_info.type() - << std::endl); - - return std::move(func); -} - -/** Create a backend pooling layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend pooling layer function - */ -std::unique_ptr<IFunction> create_pooling_layer(PoolingLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL PoolingLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const PoolingLayerInfo pool_info = node.pooling_info(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<CLPoolingLayer>(); - func->configure(input, output, pool_info); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLPoolingLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Pooling info: " << pool_info.pool_type() - << std::endl); - - return std::move(func); -} - -/** Create a backend reshape layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend reshape layer function - */ -std::unique_ptr<IFunction> create_reshape_layer(ReshapeLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL ReshapeLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *output = get_backing_tensor(node.output(0)); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<CLReshapeLayer>(); - func->configure(input, output); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLReshapeLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend softmax layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend softmax layer function - */ -std::unique_ptr<IFunction> create_softmax_layer(SoftmaxLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating CL SoftmaxLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ICLTensor *input = get_backing_tensor(node.input(0)); - ICLTensor *output = get_backing_tensor(node.output(0)); - const float beta = node.beta(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<CLSoftmaxLayer>(get_memory_manager(ctx, Target::CL)); - func->configure(input, output, beta); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated CLSoftmaxLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} -} // namespace - -std::unique_ptr<IFunction> CLFunctionFactory::create(INode *node, GraphContext &ctx) -{ - if(node == nullptr) - { - return nullptr; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ActivationLayer: - return create_activation_layer(*polymorphic_downcast<ActivationLayerNode *>(node)); - case NodeType::BatchNormalizationLayer: - return create_batch_normalization_layer(*polymorphic_downcast<BatchNormalizationLayerNode *>(node)); - case NodeType::ConvolutionLayer: - return create_convolution_layer(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx); - case NodeType::DepthConcatenateLayer: - return create_depth_concatenate_layer(*polymorphic_downcast<DepthConcatenateLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return create_depthwise_convolution_layer(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - case NodeType::EltwiseLayer: - return create_eltwise_layer(*polymorphic_downcast<EltwiseLayerNode *>(node)); - case NodeType::FlattenLayer: - return create_flatten_layer(*polymorphic_downcast<FlattenLayerNode *>(node)); - case NodeType::FullyConnectedLayer: - return create_fully_connected_layer(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx); - case NodeType::NormalizationLayer: - return create_normalization_layer(*polymorphic_downcast<NormalizationLayerNode *>(node)); - case NodeType::PoolingLayer: - return create_pooling_layer(*polymorphic_downcast<PoolingLayerNode *>(node)); - case NodeType::ReshapeLayer: - return create_reshape_layer(*polymorphic_downcast<ReshapeLayerNode *>(node)); - case NodeType::SoftmaxLayer: - return create_softmax_layer(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx); - default: - return nullptr; - } -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/CL/CLNodeValidator.cpp b/src/graph2/backends/CL/CLNodeValidator.cpp deleted file mode 100644 index 851285630e..0000000000 --- a/src/graph2/backends/CL/CLNodeValidator.cpp +++ /dev/null @@ -1,64 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/CL/CLNodeValidator.h" - -#include "arm_compute/graph2/backends/ValidateHelpers.h" -#include "arm_compute/graph2/nodes/Nodes.h" - -#include "arm_compute/core/utils/misc/Cast.h" -#include "arm_compute/runtime/CL/CLFunctions.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -Status CLNodeValidator::validate(INode *node) -{ - if(node == nullptr) - { - return Status{}; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ConvolutionLayer: - return detail::validate_convolution_layer<CLConvolutionLayer, - CLDirectConvolutionLayer, - CLGEMMConvolutionLayer, - CLWinogradConvolutionLayer>(*polymorphic_downcast<ConvolutionLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return detail::validate_depthwise_convolution_layer<CLDepthwiseConvolutionLayer, - CLDepthwiseConvolutionLayer3x3>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - default: - return Status{}; - } -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/CL/CLSubTensorHandle.cpp b/src/graph2/backends/CL/CLSubTensorHandle.cpp deleted file mode 100644 index 65a1ba4d5f..0000000000 --- a/src/graph2/backends/CL/CLSubTensorHandle.cpp +++ /dev/null @@ -1,78 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/CL/CLSubTensorHandle.h" - -#include "arm_compute/core/utils/misc/Cast.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -CLSubTensorHandle::CLSubTensorHandle(ITensorHandle *parent_handle, const TensorShape &shape, const Coordinates &coords, bool extend_parent) - : _sub_tensor() -{ - ARM_COMPUTE_ERROR_ON(!parent_handle); - auto parent_tensor = arm_compute::utils::cast::polymorphic_downcast<ICLTensor *>(&parent_handle->tensor()); - _sub_tensor = arm_compute::CLSubTensor(parent_tensor, shape, coords, extend_parent); -} - -void CLSubTensorHandle::allocate() -{ - // noop -} - -const arm_compute::ITensor &CLSubTensorHandle::tensor() const -{ - return _sub_tensor; -} - -arm_compute::ITensor &CLSubTensorHandle::tensor() -{ - return _sub_tensor; -} - -void CLSubTensorHandle::map(bool blocking) -{ - _sub_tensor.map(blocking); -} - -void CLSubTensorHandle::unmap() -{ - _sub_tensor.unmap(); -} - -void CLSubTensorHandle::release_if_unused() -{ - // noop -} - -bool CLSubTensorHandle::is_subtensor() const -{ - return true; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/CL/CLTensorHandle.cpp b/src/graph2/backends/CL/CLTensorHandle.cpp deleted file mode 100644 index 89678fb280..0000000000 --- a/src/graph2/backends/CL/CLTensorHandle.cpp +++ /dev/null @@ -1,78 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/CL/CLTensorHandle.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -CLTensorHandle::CLTensorHandle(const ITensorInfo &info) - : _tensor() -{ - _tensor.allocator()->init(info); -} - -void CLTensorHandle::allocate() -{ - _tensor.allocator()->allocate(); -} - -const arm_compute::ITensor &CLTensorHandle::tensor() const -{ - return _tensor; -} - -arm_compute::ITensor &CLTensorHandle::tensor() -{ - return _tensor; -} - -void CLTensorHandle::map(bool blocking) -{ - _tensor.map(blocking); -} - -void CLTensorHandle::unmap() -{ - _tensor.unmap(); -} - -void CLTensorHandle::release_if_unused() -{ - // TODO (geopin01): Release tensor only if all sub-tensors are marked as not used - if(!_tensor.is_used()) - { - _tensor.allocator()->free(); - } -} - -bool CLTensorHandle::is_subtensor() const -{ - return false; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/GLES/GCDeviceBackend.cpp b/src/graph2/backends/GLES/GCDeviceBackend.cpp deleted file mode 100644 index 7dab422a82..0000000000 --- a/src/graph2/backends/GLES/GCDeviceBackend.cpp +++ /dev/null @@ -1,133 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/GLES/GCDeviceBackend.h" - -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/GraphContext.h" -#include "arm_compute/graph2/INode.h" -#include "arm_compute/graph2/Logger.h" -#include "arm_compute/graph2/Tensor.h" -#include "arm_compute/graph2/backends/BackendRegistrar.h" -#include "arm_compute/graph2/backends/GLES/GCFunctionFactory.h" -#include "arm_compute/graph2/backends/GLES/GCNodeValidator.h" -#include "arm_compute/graph2/backends/GLES/GCTensorHandle.h" - -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/runtime/BlobLifetimeManager.h" -#include "arm_compute/runtime/GLES_COMPUTE/GCBufferAllocator.h" -#include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" -#include "arm_compute/runtime/MemoryManagerOnDemand.h" -#include "arm_compute/runtime/PoolManager.h" - -#include "support/ToolchainSupport.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -/** Register GLES backend */ -static detail::BackendRegistrar<GCDeviceBackend> GCDeviceBackend_registrar(Target::GC); - -GCDeviceBackend::GCDeviceBackend() - : _allocator() -{ -} - -void GCDeviceBackend::initialize_backend() -{ - // Setup Scheduler - GCScheduler::get().default_init(); -} - -void GCDeviceBackend::setup_backend_context(GraphContext &ctx) -{ - // Setup a management backend - if(ctx.memory_management_ctx(Target::GC) == nullptr) - { - MemoryManagerContext mm_ctx; - mm_ctx.target = Target::GC; - mm_ctx.mm = create_memory_manager(MemoryManagerAffinity::Buffer); - - ctx.insert_memory_management_ctx(std::move(mm_ctx)); - } -} - -std::unique_ptr<ITensorHandle> GCDeviceBackend::create_tensor(const Tensor &tensor) -{ - // Get tensor descriptor - const TensorDescriptor &tensor_desc = tensor.desc(); - ARM_COMPUTE_ERROR_ON(tensor_desc.target != Target::GC); - - // Create backend tensor handle - TensorInfo info(tensor_desc.shape, 1, tensor_desc.data_type); - auto backend_tensor_handle = support::cpp14::make_unique<GCTensorHandle>(info); - - return std::move(backend_tensor_handle); -} - -std::unique_ptr<ITensorHandle> GCDeviceBackend::create_subtensor(ITensorHandle *parent, TensorShape shape, Coordinates coords, bool extend_parent) -{ - ARM_COMPUTE_UNUSED(parent, shape, coords, extend_parent); - ARM_COMPUTE_ERROR("GLES backend has no sub-tensor support!"); - return nullptr; -} - -std::unique_ptr<arm_compute::IFunction> GCDeviceBackend::configure_node(INode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Configuring GC node with ID : " << node.id() << std::endl); - ARM_COMPUTE_ERROR_ON(node.assigned_target() != Target::GC); - - // Configure node - return GCFunctionFactory::create(&node, ctx); -} - -arm_compute::Status GCDeviceBackend::validate_node(INode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating GC node with ID : " << node.id() << std::endl); - ARM_COMPUTE_ERROR_ON(node.assigned_target() != Target::GC); - - return GCNodeValidator::validate(&node); -} - -std::shared_ptr<arm_compute::IMemoryManager> GCDeviceBackend::create_memory_manager(MemoryManagerAffinity affinity) -{ - if(affinity == MemoryManagerAffinity::Offset) - { - ARM_COMPUTE_LOG_GRAPH_WARNING("GC Backend does not support offset affinity memory management!"); - return nullptr; - } - - auto lifetime_mgr = std::make_shared<BlobLifetimeManager>(); - auto pool_mgr = std::make_shared<PoolManager>(); - auto mm = std::make_shared<MemoryManagerOnDemand>(lifetime_mgr, pool_mgr); - - mm->set_allocator(&_allocator); - - return mm; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/GLES/GCFunctionsFactory.cpp b/src/graph2/backends/GLES/GCFunctionsFactory.cpp deleted file mode 100644 index 24ab2bce37..0000000000 --- a/src/graph2/backends/GLES/GCFunctionsFactory.cpp +++ /dev/null @@ -1,507 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/GLES/GCFunctionFactory.h" - -#include "arm_compute/core/utils/misc/Cast.h" -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/GraphContext.h" -#include "arm_compute/graph2/Logger.h" -#include "arm_compute/graph2/TypePrinter.h" -#include "arm_compute/graph2/Types.h" -#include "arm_compute/graph2/backends/Utils.h" -#include "arm_compute/graph2/nodes/Nodes.h" -#include "arm_compute/runtime/GLES_COMPUTE/GCFunctions.h" - -#include "support/ToolchainSupport.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -namespace -{ -/** Returns backing tensor of a given tensor - * - * @param[in] tensor Tensor to extract the backing tensor from - * - * @return Backing tensor if present else nullptr - */ -arm_compute::IGCTensor *get_backing_tensor(arm_compute::graph2::Tensor *tensor) -{ - arm_compute::IGCTensor *backing_tensor = nullptr; - if(tensor != nullptr) - { - ARM_COMPUTE_ERROR_ON(tensor->desc().target != arm_compute::graph2::Target::GC); - // Get backing tensor handle - ITensorHandle *tensor_handle = tensor->handle(); - // Get backing tensor - backing_tensor = (tensor_handle != nullptr) ? polymorphic_cast<IGCTensor *>(&tensor_handle->tensor()) : nullptr; - } - - return backing_tensor; -} - -/** Create a backend activation layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend activation layer function - */ -std::unique_ptr<IFunction> create_activation_layer(ActivationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC ActivationLayerNode node with ID : " << node.id() << " and Name: " << node.name() - << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const ActivationLayerInfo act_info = node.activation_info(); - - // Create function - auto func = support::cpp14::make_unique<GCActivationLayer>(); - func->configure(input, output, act_info); - - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCActivationLayer" - << " Data Type: " << input->info()->data_type() - << " Shape: " << input->info()->tensor_shape() - << " Activation function: " << act_info.activation() - << " a: " << act_info.a() - << " b: " << act_info.b() - << " InPlace : " << is_in_place_operation(input, output) - << std::endl); - - return std::move(func); -} - -/** Create a backend batch normalization layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend batch normalization layer function - */ -std::unique_ptr<IFunction> create_batch_normalization_layer(BatchNormalizationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating GC BatchNormalization node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - - // TODO (geopin01) : Var and mean are compulsory, switch function to accept nullptr as beta and/or gamma - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 5); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *mean = get_backing_tensor(node.input(1)); - IGCTensor *var = get_backing_tensor(node.input(2)); - IGCTensor *beta = get_backing_tensor(node.input(3)); - IGCTensor *gamma = get_backing_tensor(node.input(4)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const float epsilon = node.epsilon(); - const ActivationLayerInfo fused_act = node.fused_activation(); - - // Create and configure function - auto func = support::cpp14::make_unique<GCBatchNormalizationLayer>(); - func->configure(input, output, mean, var, beta, gamma, epsilon, fused_act); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCBatchNormalizationLayer" - << " Data Type: " << input->info()->data_type() - << " Shape: " << input->info()->tensor_shape() - << " Epsilon: " << epsilon << " " - << (fused_act.enabled() ? to_string(fused_act.activation()) : "") - << " InPlace : " << is_in_place_operation(input, output) - << std::endl); - - return std::move(func); -} - -/** Create a backend convolution layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend convolution layer function - */ -std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating GC ConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *weights = get_backing_tensor(node.input(1)); - IGCTensor *biases = get_backing_tensor(node.input(2)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const PadStrideInfo conv_info = node.convolution_info(); - const ConvolutionMethod conv_algorithm = node.convolution_method(); - - // Create and configure function (we assume that functions have been validated before creation) - std::shared_ptr<IMemoryManager> mm = get_memory_manager(ctx, Target::GC); - std::unique_ptr<IFunction> func; - std::string func_name; - - if(conv_algorithm == ConvolutionMethod::DIRECT) - { - std::tie(func, func_name) = create_named_function<GCDirectConvolutionLayer>( - std::string("GCDirectConvolutionLayer"), input, weights, biases, output, conv_info); - } - else - { - std::tie(func, func_name) = create_named_memory_managed_function<GCConvolutionLayer>(std::string("GCConvolutionLayer"), mm, - input, weights, biases, output, conv_info); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - return func; -} - -/** Create a backend layer depth concatenate function - * - * @param[in] node Node to create the backend function for - * - * @return Backend depth concatenate layer function - */ -std::unique_ptr<arm_compute::IFunction> create_depth_concatenate_layer(DepthConcatenateLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating GC DepthConcatenate node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Return nullptr if depth concatenate is switched off - if(!node.is_enabled()) - { - return nullptr; - } - - // Extract IO and info - std::vector<arm_compute::IGCTensor *> inputs; - for(unsigned int i = 0; i < node.num_inputs(); ++i) - { - inputs.push_back(get_backing_tensor(node.input(i))); - } - IGCTensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<GCDepthConcatenateLayer>(); - func->configure(inputs, output); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCDepthConcatenateLayer" - << " Data Type: " << output->info()->data_type() - << " Shape: " << output->info()->tensor_shape() - << " Num Inputs: " << inputs.size() - << std::endl); - - return std::move(func); -} - -/** Create a backend layer depth-wise convolution function - * - * @param[in] node Node to create the backend function for - * - * @return Backend depth-wise convolution layer function - */ -std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvolutionLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC DepthwiseConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() - << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *weights = get_backing_tensor(node.input(1)); - IGCTensor *biases = get_backing_tensor(node.input(2)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const PadStrideInfo conv_info = node.convolution_info(); - const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); - - // Create and configure function (we assume that functions have been validated before creation) - std::unique_ptr<IFunction> func; - std::string func_name; - if(dwc_algorithm == DepthwiseConvolutionMethod::OPTIMIZED_3x3) - { - std::tie(func, func_name) = create_named_function<GCDepthwiseConvolutionLayer3x3>( - std::string("GCDepthwiseConvolutionLayer3x3"), input, weights, biases, output, conv_info); - } - else - { - ARM_COMPUTE_ERROR("Generic DepthwiseConvolutionLayer is not supported in GLES backend"); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - return func; -} - -/** Create a backend element-wise operation layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend element-wise operation layer function - */ -std::unique_ptr<IFunction> create_eltwise_layer(EltwiseLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC EltwiseLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 2); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input1 = get_backing_tensor(node.input(0)); - IGCTensor *input2 = get_backing_tensor(node.input(1)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const EltwiseOperation eltwise_op = node.eltwise_operation(); - ARM_COMPUTE_ERROR_ON(input1 == nullptr); - ARM_COMPUTE_ERROR_ON(input2 == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - std::unique_ptr<IFunction> func = nullptr; - std::string func_name; - if(eltwise_op == EltwiseOperation::ADD) - { - std::tie(func, func_name) = create_named_function<GCArithmeticAddition>(std::string("GCArithmeticAddition"), - input1, input2, output, - ConvertPolicy::SATURATE); - } - else if(eltwise_op == EltwiseOperation::SUB) - { - ARM_COMPUTE_ERROR("Arithmetic subtraction is not supported in GLES backend"); - } - else if(eltwise_op == EltwiseOperation::MUL) - { - std::tie(func, func_name) = create_named_function<GCPixelWiseMultiplication>( - std::string("GCPixelWiseMultiplication"), input1, input2, output, 1.f); - } - else - { - ARM_COMPUTE_ERROR("Unsupported element-wise operation!"); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input1->info()->data_type() - << " Shape : " << input1->info()->tensor_shape() - << std::endl); - - return func; -} - -/** Create a backend fully connected layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend fully connected layer function - */ -std::unique_ptr<IFunction> create_fully_connected_layer(FullyConnectedLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC FullyConnectedLayer node with ID : " << node.id() << " and Name: " << node.name() - << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *weights = get_backing_tensor(node.input(1)); - IGCTensor *biases = get_backing_tensor(node.input(2)); - IGCTensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<GCFullyConnectedLayer>(get_memory_manager(ctx, Target::GC)); - func->configure(input, weights, biases, output); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(weights == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCFullyConnectedLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Biases Shape: " << biases->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend normalization layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend normalization layer function - */ -std::unique_ptr<IFunction> create_normalization_layer(NormalizationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC NormalizationLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const NormalizationLayerInfo norm_info = node.normalization_info(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<GCNormalizationLayer>(); - func->configure(input, output, norm_info); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCNormalizationLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Normalization info: " << norm_info.type() - << std::endl); - - return std::move(func); -} - -/** Create a backend pooling layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend pooling layer function - */ -std::unique_ptr<IFunction> create_pooling_layer(PoolingLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC PoolingLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const PoolingLayerInfo pool_info = node.pooling_info(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<GCPoolingLayer>(); - func->configure(input, output, pool_info); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCPoolingLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Pooling info: " << pool_info.pool_type() - << std::endl); - - return std::move(func); -} - -/** Create a backend softmax layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend softmax layer function - */ -std::unique_ptr<IFunction> create_softmax_layer(SoftmaxLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC SoftmaxLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - IGCTensor *input = get_backing_tensor(node.input(0)); - IGCTensor *output = get_backing_tensor(node.output(0)); - const float beta = node.beta(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<GCSoftmaxLayer>(get_memory_manager(ctx, Target::CL)); - func->configure(input, output, beta); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated GCSoftmaxLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} -} // namespace - -std::unique_ptr<IFunction> GCFunctionFactory::create(INode *node, GraphContext &ctx) -{ - if(node == nullptr) - { - return nullptr; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ActivationLayer: - return create_activation_layer(*polymorphic_downcast<ActivationLayerNode *>(node)); - case NodeType::BatchNormalizationLayer: - return create_batch_normalization_layer(*polymorphic_downcast<BatchNormalizationLayerNode *>(node)); - case NodeType::ConvolutionLayer: - return create_convolution_layer(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx); - case NodeType::DepthConcatenateLayer: - return create_depth_concatenate_layer(*polymorphic_downcast<DepthConcatenateLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return create_depthwise_convolution_layer(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - case NodeType::EltwiseLayer: - return create_eltwise_layer(*polymorphic_downcast<EltwiseLayerNode *>(node)); - case NodeType::FullyConnectedLayer: - return create_fully_connected_layer(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx); - case NodeType::NormalizationLayer: - return create_normalization_layer(*polymorphic_downcast<NormalizationLayerNode *>(node)); - case NodeType::PoolingLayer: - return create_pooling_layer(*polymorphic_downcast<PoolingLayerNode *>(node)); - case NodeType::SoftmaxLayer: - return create_softmax_layer(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx); - default: - return nullptr; - } -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/GLES/GCNodeValidator.cpp b/src/graph2/backends/GLES/GCNodeValidator.cpp deleted file mode 100644 index b8daae566d..0000000000 --- a/src/graph2/backends/GLES/GCNodeValidator.cpp +++ /dev/null @@ -1,122 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/GLES/GCNodeValidator.h" - -#include "arm_compute/graph2/backends/ValidateHelpers.h" -#include "arm_compute/graph2/nodes/Nodes.h" - -#include "arm_compute/core/utils/misc/Cast.h" -#include "arm_compute/runtime/GLES_COMPUTE/GCFunctions.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -namespace -{ -/** Validates a Depthwise Convolution layer node - * - * @param[in] node Node to validate - * - * @return Status - */ -Status validate_depthwise_convolution_layer(DepthwiseConvolutionLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating GCDepthwiseConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - arm_compute::ITensorInfo *weights = detail::get_backing_tensor_info(node.input(1)); - ARM_COMPUTE_ERROR_ON(weights == nullptr); - - // TODO (geopin01) : Switch when validation is implemented - // Validate function - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->tensor_shape().x() != 3 && weights->tensor_shape().y() != 3, "Unsupported depthwise convolution"); - node.set_depthwise_convolution_method(DepthwiseConvolutionMethod::OPTIMIZED_3x3); - - return Status{}; -} -/** Validates a Convolution layer node - * - * @param[in] node Node to validate - * - * @return Status - */ -Status validate_convolution_layer(ConvolutionLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating ConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - arm_compute::ITensorInfo *weights = detail::get_backing_tensor_info(node.input(1)); - const PadStrideInfo conv_info = node.convolution_info(); - const ConvolutionMethod conv_algorithm = node.convolution_method(); - - // Validate function - if(conv_algorithm == ConvolutionMethod::DIRECT) - { - bool is_square = weights->tensor_shape().x() == weights->tensor_shape().y(); - bool is_direct = (weights->tensor_shape().x() == 1) || (weights->tensor_shape().x() == 3) || (weights->tensor_shape().x() == 5); - bool is_correct_stride = (conv_info.stride().first) <= 2 && (conv_info.stride().second <= 2); - if(!(is_square && is_direct && is_correct_stride)) - { - node.set_convolution_method(ConvolutionMethod::DEFAULT); - } - } - - return Status{}; -} -} // namespace - -Status GCNodeValidator::validate(INode *node) -{ - if(node == nullptr) - { - return Status{}; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ConvolutionLayer: - return validate_convolution_layer(*polymorphic_downcast<ConvolutionLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return validate_depthwise_convolution_layer(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - case NodeType::FlattenLayer: - return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation"); - case NodeType::ReshapeLayer: - return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation"); - default: - return Status{}; - } -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/GLES/GCTensorHandle.cpp b/src/graph2/backends/GLES/GCTensorHandle.cpp deleted file mode 100644 index 2165cd2de6..0000000000 --- a/src/graph2/backends/GLES/GCTensorHandle.cpp +++ /dev/null @@ -1,78 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/GLES/GCTensorHandle.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -GCTensorHandle::GCTensorHandle(const ITensorInfo &info) - : _tensor() -{ - _tensor.allocator()->init(info); -} - -void GCTensorHandle::allocate() -{ - _tensor.allocator()->allocate(); -} - -const arm_compute::ITensor &GCTensorHandle::tensor() const -{ - return _tensor; -} - -arm_compute::ITensor &GCTensorHandle::tensor() -{ - return _tensor; -} - -void GCTensorHandle::map(bool blocking) -{ - _tensor.map(blocking); -} - -void GCTensorHandle::unmap() -{ - _tensor.unmap(); -} - -void GCTensorHandle::release_if_unused() -{ - // TODO (geopin01): Release tensor only if all sub-tensors are marked as not used - if(!_tensor.is_used()) - { - _tensor.allocator()->free(); - } -} - -bool GCTensorHandle::is_subtensor() const -{ - return false; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/NEON/NEDeviceBackend.cpp b/src/graph2/backends/NEON/NEDeviceBackend.cpp deleted file mode 100644 index 6cb507b4f1..0000000000 --- a/src/graph2/backends/NEON/NEDeviceBackend.cpp +++ /dev/null @@ -1,141 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/NEON/NEDeviceBackend.h" - -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/GraphContext.h" -#include "arm_compute/graph2/INode.h" -#include "arm_compute/graph2/Logger.h" -#include "arm_compute/graph2/Tensor.h" -#include "arm_compute/graph2/backends/BackendRegistrar.h" -#include "arm_compute/graph2/backends/NEON/NEFunctionFactory.h" -#include "arm_compute/graph2/backends/NEON/NENodeValidator.h" -#include "arm_compute/graph2/backends/NEON/NESubTensorHandle.h" -#include "arm_compute/graph2/backends/NEON/NETensorHandle.h" - -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/runtime/Allocator.h" -#include "arm_compute/runtime/BlobLifetimeManager.h" -#include "arm_compute/runtime/MemoryManagerOnDemand.h" -#include "arm_compute/runtime/OffsetLifetimeManager.h" -#include "arm_compute/runtime/PoolManager.h" -#include "arm_compute/runtime/Scheduler.h" - -#include "support/ToolchainSupport.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -/** Register NEON backend */ -static detail::BackendRegistrar<NEDeviceBackend> NEDeviceBackend_registrar(Target::NEON); - -NEDeviceBackend::NEDeviceBackend() - : _allocator() -{ -} - -void NEDeviceBackend::initialize_backend() -{ -} - -void NEDeviceBackend::setup_backend_context(GraphContext &ctx) -{ - // Set number of threads - Scheduler::get().set_num_threads(ctx.config().num_threads); - - // Create function level memory manager - if(ctx.memory_management_ctx(Target::NEON) == nullptr) - { - MemoryManagerContext mm_ctx; - mm_ctx.target = Target::NEON; - mm_ctx.mm = create_memory_manager(MemoryManagerAffinity::Buffer); - - ctx.insert_memory_management_ctx(std::move(mm_ctx)); - } -} - -std::unique_ptr<ITensorHandle> NEDeviceBackend::create_tensor(const Tensor &tensor) -{ - // Get tensor descriptor - const TensorDescriptor &tensor_desc = tensor.desc(); - ARM_COMPUTE_ERROR_ON(tensor_desc.target != Target::NEON); - - // Create backend tensor handle - TensorInfo info(tensor_desc.shape, 1, tensor_desc.data_type); - auto backend_tensor_handle = support::cpp14::make_unique<NETensorHandle>(info); - - return std::move(backend_tensor_handle); -} - -std::unique_ptr<ITensorHandle> NEDeviceBackend::create_subtensor(ITensorHandle *parent, TensorShape shape, Coordinates coords, bool extend_parent) -{ - if(parent == nullptr) - { - return nullptr; - } - - return support::cpp14::make_unique<NESubTensorHandle>(parent, shape, coords, extend_parent); -} - -std::unique_ptr<arm_compute::IFunction> NEDeviceBackend::configure_node(INode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Configuring NEON node with ID : " << node.id() << std::endl); - ARM_COMPUTE_ERROR_ON(node.assigned_target() != Target::NEON); - - // Configure node - return NEFunctionFactory::create(&node, ctx); -} - -arm_compute::Status NEDeviceBackend::validate_node(INode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating NEON node with ID : " << node.id() << std::endl); - ARM_COMPUTE_ERROR_ON(node.assigned_target() != Target::NEON); - - return NENodeValidator::validate(&node); -} - -std::shared_ptr<arm_compute::IMemoryManager> NEDeviceBackend::create_memory_manager(MemoryManagerAffinity affinity) -{ - std::shared_ptr<ILifetimeManager> lifetime_mgr = nullptr; - if(affinity == MemoryManagerAffinity::Buffer) - { - lifetime_mgr = std::make_shared<BlobLifetimeManager>(); - } - else - { - lifetime_mgr = std::make_shared<OffsetLifetimeManager>(); - } - auto pool_mgr = std::make_shared<PoolManager>(); - auto mm = std::make_shared<MemoryManagerOnDemand>(lifetime_mgr, pool_mgr); - - mm->set_allocator(&_allocator); - - return mm; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/NEON/NEFunctionFactory.cpp b/src/graph2/backends/NEON/NEFunctionFactory.cpp deleted file mode 100644 index 933210377d..0000000000 --- a/src/graph2/backends/NEON/NEFunctionFactory.cpp +++ /dev/null @@ -1,563 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/NEON/NEFunctionFactory.h" - -#include "arm_compute/core/utils/misc/Cast.h" -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/GraphContext.h" -#include "arm_compute/graph2/Logger.h" -#include "arm_compute/graph2/TypePrinter.h" -#include "arm_compute/graph2/backends/Utils.h" -#include "arm_compute/graph2/nodes/Nodes.h" -#include "arm_compute/runtime/NEON/NEFunctions.h" -#include "support/ToolchainSupport.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -namespace -{ -/** Returns backing tensor of a given tensor - * - * @param[in] tensor Tensor to extract the backing tensor from - * - * @return Backing tensor if present else nullptr - */ -arm_compute::ITensor *get_backing_tensor(arm_compute::graph2::Tensor *tensor) -{ - return ((tensor == nullptr) || (tensor->handle() == nullptr)) ? nullptr : &tensor->handle()->tensor(); -} - -/** Create a backend activation layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend activation layer function - */ -std::unique_ptr<IFunction> create_activation_layer(ActivationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON ActivationLayerNode node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *output = get_backing_tensor(node.output(0)); - const ActivationLayerInfo act_info = node.activation_info(); - - // Create function - auto func = support::cpp14::make_unique<NEActivationLayer>(); - func->configure(input, output, act_info); - - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEActivationLayer" - << " Data Type: " << input->info()->data_type() - << " Shape: " << input->info()->tensor_shape() - << " Activation function: " << act_info.activation() - << " a: " << act_info.a() - << " b: " << act_info.b() - << " InPlace : " << is_in_place_operation(input, output) - << std::endl); - - return std::move(func); -} - -/** Create a backend batch normalization layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend batch normalization layer function - */ -std::unique_ptr<IFunction> create_batch_normalization_layer(BatchNormalizationLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON BatchNormalization node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - - // TODO (geopin01) : Var and mean are compulsory, switch function to accept nullptr as beta and/or gamma - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 5); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *mean = get_backing_tensor(node.input(1)); - ITensor *var = get_backing_tensor(node.input(2)); - ITensor *beta = get_backing_tensor(node.input(3)); - ITensor *gamma = get_backing_tensor(node.input(4)); - ITensor *output = get_backing_tensor(node.output(0)); - const float epsilon = node.epsilon(); - const ActivationLayerInfo fused_act = node.fused_activation(); - - // Create and configure function - auto func = support::cpp14::make_unique<NEBatchNormalizationLayer>(); - func->configure(input, output, mean, var, beta, gamma, epsilon, fused_act); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEBatchNormalizationLayer" - << " Data Type: " << input->info()->data_type() - << " Shape: " << input->info()->tensor_shape() - << " Epsilon: " << epsilon << " " - << (fused_act.enabled() ? to_string(fused_act.activation()) : "") - << " InPlace : " << is_in_place_operation(input, output) - << std::endl); - - return std::move(func); -} - -/** Create a backend convolution layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend convolution layer function - */ -std::unique_ptr<IFunction> create_convolution_layer(ConvolutionLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON ConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *weights = get_backing_tensor(node.input(1)); - ITensor *biases = get_backing_tensor(node.input(2)); - ITensor *output = get_backing_tensor(node.output(0)); - const PadStrideInfo conv_info = node.convolution_info(); - const ConvolutionMethod conv_algorithm = node.convolution_method(); - - // Create and configure function (we assume that functions have been validated before creation) - std::shared_ptr<IMemoryManager> mm = get_memory_manager(ctx, Target::NEON); - std::unique_ptr<IFunction> func; - std::string func_name; - if(conv_algorithm == ConvolutionMethod::DIRECT) - { - std::tie(func, func_name) = create_named_memory_managed_function<NEDirectConvolutionLayer>(std::string("NEDirectConvolutionLayer"), mm, - input, weights, biases, output, conv_info); - } - else if(conv_algorithm == ConvolutionMethod::GEMM) - { - std::tie(func, func_name) = create_named_memory_managed_function<NEGEMMConvolutionLayer>(std::string("NEGEMMConvolutionLayer"), mm, - input, weights, biases, output, conv_info); - } - else if(conv_algorithm == ConvolutionMethod::WINOGRAD) - { - std::tie(func, func_name) = create_named_memory_managed_function<NEWinogradLayer>(std::string("NEWinogradLayer"), mm, - input, weights, biases, output, conv_info); - } - else - { - std::tie(func, func_name) = create_named_memory_managed_function<NEConvolutionLayer>(std::string("NEConvolutionLayer"), mm, - input, weights, biases, output, conv_info); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - return func; -} - -/** Create a backend layer depth concatenate function - * - * @param[in] node Node to create the backend function for - * - * @return Backend depth concatenate layer function - */ -std::unique_ptr<arm_compute::IFunction> create_depth_concatenate_layer(DepthConcatenateLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON DepthConcatenate node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Return nullptr if depth concatenate is switched off - if(!node.is_enabled()) - { - return nullptr; - } - - // Extract IO and info - std::vector<arm_compute::ITensor *> inputs; - for(unsigned int i = 0; i < node.num_inputs(); ++i) - { - inputs.push_back(get_backing_tensor(node.input(i))); - } - ITensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<NEDepthConcatenateLayer>(); - func->configure(inputs, output); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEDepthConcatenateLayer" - << " Data Type: " << output->info()->data_type() - << " Shape: " << output->info()->tensor_shape() - << " Num Inputs: " << inputs.size() - << std::endl); - - return std::move(func); -} - -/** Create a backend layer depth-wise convolution function - * - * @param[in] node Node to create the backend function for - * - * @return Backend depth-wise convolution layer function - */ -std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvolutionLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON DepthwiseConvolutionLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *weights = get_backing_tensor(node.input(1)); - ITensor *biases = get_backing_tensor(node.input(2)); - ITensor *output = get_backing_tensor(node.output(0)); - const PadStrideInfo conv_info = node.convolution_info(); - const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); - - // Create and configure function (we assume that functions have been validated before creation) - std::unique_ptr<IFunction> func; - std::string func_name; - if(dwc_algorithm == DepthwiseConvolutionMethod::OPTIMIZED_3x3) - { - std::tie(func, func_name) = create_named_function<NEDepthwiseConvolutionLayer3x3>(std::string("NEDepthwiseConvolutionLayer3x3"), - input, weights, biases, output, conv_info); - } - else - { - std::tie(func, func_name) = create_named_function<NEDepthwiseConvolutionLayer>(std::string("NEDepthwiseConvolutionLayer"), - input, weights, biases, output, conv_info); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - return func; -} - -/** Create a backend element-wise operation layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend element-wise operation layer function - */ -std::unique_ptr<IFunction> create_eltwise_layer(EltwiseLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON EltwiseLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 2); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input1 = get_backing_tensor(node.input(0)); - ITensor *input2 = get_backing_tensor(node.input(1)); - ITensor *output = get_backing_tensor(node.output(0)); - const EltwiseOperation eltwise_op = node.eltwise_operation(); - ARM_COMPUTE_ERROR_ON(input1 == nullptr); - ARM_COMPUTE_ERROR_ON(input2 == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - std::unique_ptr<IFunction> func = nullptr; - std::string func_name; - if(eltwise_op == EltwiseOperation::ADD) - { - std::tie(func, func_name) = create_named_function<NEArithmeticAddition>(std::string("NEArithmeticAddition"), - input1, input2, output, ConvertPolicy::SATURATE); - } - else if(eltwise_op == EltwiseOperation::SUB) - { - std::tie(func, func_name) = create_named_function<NEArithmeticSubtraction>(std::string("NEArithmeticSubtraction"), - input1, input2, output, ConvertPolicy::SATURATE); - } - else if(eltwise_op == EltwiseOperation::MUL) - { - std::tie(func, func_name) = create_named_function<NEPixelWiseMultiplication>(std::string("NEPixelWiseMultiplication"), - input1, input2, output, 1.f, - ConvertPolicy::SATURATE, RoundingPolicy::TO_NEAREST_EVEN); - } - else - { - ARM_COMPUTE_ERROR("Unsupported element-wise operation!"); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << func_name - << " Data Type: " << input1->info()->data_type() - << " Shape : " << input1->info()->tensor_shape() - << std::endl); - - return func; -} - -/** Create a backend flatten layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend flatten layer function - */ -std::unique_ptr<IFunction> create_flatten_layer(FlattenLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON FlattenLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<NEFlattenLayer>(); - func->configure(input, output); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEFlattenLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend fully connected layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend fully connected layer function - */ -std::unique_ptr<IFunction> create_fully_connected_layer(FullyConnectedLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON FullyConnectedLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 3); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *weights = get_backing_tensor(node.input(1)); - ITensor *biases = get_backing_tensor(node.input(2)); - ITensor *output = get_backing_tensor(node.output(0)); - - // Create and configure function - auto func = support::cpp14::make_unique<NEFullyConnectedLayer>(get_memory_manager(ctx, Target::NEON)); - func->configure(input, weights, biases, output); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(weights == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEFullyConnectedLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend normalization layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend normalization layer function - */ -std::unique_ptr<IFunction> create_normalization_layer(NormalizationLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON NormalizationLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *output = get_backing_tensor(node.output(0)); - const NormalizationLayerInfo norm_info = node.normalization_info(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<NENormalizationLayer>(get_memory_manager(ctx, Target::NEON)); - func->configure(input, output, norm_info); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NENormalizationLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Normalization info: " << norm_info.type() - << std::endl); - - return std::move(func); -} - -/** Create a backend pooling layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend pooling layer function - */ -std::unique_ptr<IFunction> create_pooling_layer(PoolingLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON PoolingLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *output = get_backing_tensor(node.output(0)); - const PoolingLayerInfo pool_info = node.pooling_info(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<NEPoolingLayer>(); - func->configure(input, output, pool_info); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEPoolingLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Pooling info: " << pool_info.pool_type() - << std::endl); - - return std::move(func); -} - -/** Create a backend reshape layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend reshape layer function - */ -std::unique_ptr<IFunction> create_reshape_layer(ReshapeLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON ReshapeLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *output = get_backing_tensor(node.output(0)); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<NEReshapeLayer>(); - func->configure(input, output); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NEReshapeLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} - -/** Create a backend softmax layer function - * - * @param[in] node Node to create the backend function for - * - * @return Backend softmax layer function - */ -std::unique_ptr<IFunction> create_softmax_layer(SoftmaxLayerNode &node, GraphContext &ctx) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Creating NEON SoftmaxLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 1); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - ITensor *input = get_backing_tensor(node.input(0)); - ITensor *output = get_backing_tensor(node.output(0)); - const float beta = node.beta(); - ARM_COMPUTE_ERROR_ON(input == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - // Create and configure function - auto func = support::cpp14::make_unique<NESoftmaxLayer>(get_memory_manager(ctx, Target::NEON)); - func->configure(input, output, beta); - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated NESoftmaxLayer" - << " Data Type: " << input->info()->data_type() - << " Input shape: " << input->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << std::endl); - - return std::move(func); -} -} // namespace - -std::unique_ptr<IFunction> NEFunctionFactory::create(INode *node, GraphContext &ctx) -{ - if(node == nullptr) - { - return nullptr; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ActivationLayer: - return create_activation_layer(*polymorphic_downcast<ActivationLayerNode *>(node)); - case NodeType::BatchNormalizationLayer: - return create_batch_normalization_layer(*polymorphic_downcast<BatchNormalizationLayerNode *>(node)); - case NodeType::ConvolutionLayer: - return create_convolution_layer(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx); - case NodeType::DepthConcatenateLayer: - return create_depth_concatenate_layer(*polymorphic_downcast<DepthConcatenateLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return create_depthwise_convolution_layer(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - case NodeType::EltwiseLayer: - return create_eltwise_layer(*polymorphic_downcast<EltwiseLayerNode *>(node)); - case NodeType::FlattenLayer: - return create_flatten_layer(*polymorphic_downcast<FlattenLayerNode *>(node)); - case NodeType::FullyConnectedLayer: - return create_fully_connected_layer(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx); - case NodeType::NormalizationLayer: - return create_normalization_layer(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx); - case NodeType::PoolingLayer: - return create_pooling_layer(*polymorphic_downcast<PoolingLayerNode *>(node)); - case NodeType::ReshapeLayer: - return create_reshape_layer(*polymorphic_downcast<ReshapeLayerNode *>(node)); - case NodeType::SoftmaxLayer: - return create_softmax_layer(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx); - default: - return nullptr; - } -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/NEON/NENodeValidator.cpp b/src/graph2/backends/NEON/NENodeValidator.cpp deleted file mode 100644 index 4620f4cd87..0000000000 --- a/src/graph2/backends/NEON/NENodeValidator.cpp +++ /dev/null @@ -1,65 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/NEON/NENodeValidator.h" - -#include "arm_compute/graph2/backends/ValidateHelpers.h" -#include "arm_compute/graph2/nodes/Nodes.h" - -#include "arm_compute/core/utils/misc/Cast.h" -#include "arm_compute/runtime/NEON/NEFunctions.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -Status NENodeValidator::validate(INode *node) -{ - if(node == nullptr) - { - return Status{}; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ConvolutionLayer: - return detail::validate_convolution_layer<NEConvolutionLayer, - NEDirectConvolutionLayer, - NEGEMMConvolutionLayer, - NEWinogradLayer>(*polymorphic_downcast<ConvolutionLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return detail::validate_depthwise_convolution_layer<NEDepthwiseConvolutionLayer, - NEDepthwiseConvolutionLayer3x3>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - - default: - return Status{}; - } -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/NEON/NESubTensorHandle.cpp b/src/graph2/backends/NEON/NESubTensorHandle.cpp deleted file mode 100644 index 1cd15be29c..0000000000 --- a/src/graph2/backends/NEON/NESubTensorHandle.cpp +++ /dev/null @@ -1,75 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/NEON/NESubTensorHandle.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -NESubTensorHandle::NESubTensorHandle(ITensorHandle *parent_handle, const TensorShape &shape, const Coordinates &coords, bool extend_parent) - : _sub_tensor() -{ - ARM_COMPUTE_ERROR_ON(!parent_handle); - _sub_tensor = arm_compute::SubTensor(&parent_handle->tensor(), shape, coords, extend_parent); -} - -void NESubTensorHandle::allocate() -{ - // noop -} - -const arm_compute::ITensor &NESubTensorHandle::tensor() const -{ - return _sub_tensor; -} - -arm_compute::ITensor &NESubTensorHandle::tensor() -{ - return _sub_tensor; -} - -void NESubTensorHandle::map(bool blocking) -{ - ARM_COMPUTE_UNUSED(blocking); -} - -void NESubTensorHandle::unmap() -{ - // noop -} - -void NESubTensorHandle::release_if_unused() -{ - // noop -} - -bool NESubTensorHandle::is_subtensor() const -{ - return true; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file diff --git a/src/graph2/backends/NEON/NETensorHandle.cpp b/src/graph2/backends/NEON/NETensorHandle.cpp deleted file mode 100644 index 0b901c3497..0000000000 --- a/src/graph2/backends/NEON/NETensorHandle.cpp +++ /dev/null @@ -1,77 +0,0 @@ -/* - * Copyright (c) 2018 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/graph2/backends/NEON/NETensorHandle.h" - -namespace arm_compute -{ -namespace graph2 -{ -namespace backends -{ -NETensorHandle::NETensorHandle(const ITensorInfo &info) - : _tensor() -{ - _tensor.allocator()->init(info); -} - -void NETensorHandle::allocate() -{ - _tensor.allocator()->allocate(); -} - -const arm_compute::ITensor &NETensorHandle::tensor() const -{ - return _tensor; -} - -arm_compute::ITensor &NETensorHandle::tensor() -{ - return _tensor; -} - -void NETensorHandle::map(bool blocking) -{ - ARM_COMPUTE_UNUSED(blocking); -} - -void NETensorHandle::unmap() -{ -} - -void NETensorHandle::release_if_unused() -{ - // TODO (geopin01): Release tensor only if all sub-tensors are marked as not used - if(!_tensor.is_used()) - { - _tensor.allocator()->free(); - } -} - -bool NETensorHandle::is_subtensor() const -{ - return false; -} -} // namespace backends -} // namespace graph2 -} // namespace arm_compute
\ No newline at end of file |