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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2017-11-23 15:59:55 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:41:58 +0000 |
commit | 236bfe7033a313ab98ff436d85f38a58b0738ed1 (patch) | |
tree | a07d0b122fa93fb26a24067de6341eaded1a52f7 /src | |
parent | 9c450cc0e0b2e7060fa0a74a5196906bc28d0625 (diff) | |
download | ComputeLibrary-236bfe7033a313ab98ff436d85f38a58b0738ed1.tar.gz |
COMPIMID-553: MobileNet use case.
Change-Id: I1181abbd5785065f3d57e91844376a4b110938a9
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110701
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'src')
-rw-r--r-- | src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp | 6 | ||||
-rw-r--r-- | src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp | 44 | ||||
-rw-r--r-- | src/graph/nodes/ConvolutionLayer.cpp | 9 | ||||
-rw-r--r-- | src/graph/nodes/DepthwiseConvolutionLayer.cpp | 7 | ||||
-rw-r--r-- | src/graph/nodes/ReshapeLayer.cpp | 4 | ||||
-rw-r--r-- | src/graph/operations/CLSimpleOperations.cpp | 2 | ||||
-rw-r--r-- | src/graph/operations/NESimpleOperations.cpp | 2 | ||||
-rw-r--r-- | src/runtime/CL/functions/CLDepthwiseConvolution.cpp | 3 |
8 files changed, 55 insertions, 22 deletions
diff --git a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp index 38e367dfb7..e8882b9daf 100644 --- a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp +++ b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp @@ -130,7 +130,8 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts)); // Set kernel static arguments - unsigned int idx = 2 * num_arguments_per_3D_tensor() + 4 * num_arguments_per_1D_tensor(); // Skip the input and output parameters + unsigned int include_output = (output != nullptr) ? 1 : 0; + unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor() + 4 * num_arguments_per_1D_tensor(); // Skip the input and output parameters _kernel.setArg<cl_float>(idx++, _epsilon); // Configure kernel window @@ -160,7 +161,8 @@ void CLBatchNormalizationLayerKernel::run(const Window &window, cl::CommandQueue Window vector_slice = window.first_slice_window_1D(); vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); - unsigned int idx = 2 * num_arguments_per_3D_tensor(); + unsigned int include_output = (_output != nullptr) ? 1 : 0; + unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor(); add_1D_tensor_argument(idx, _mean, vector_slice); add_1D_tensor_argument(idx, _var, vector_slice); add_1D_tensor_argument(idx, _beta, vector_slice); diff --git a/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp index be8fae2885..e86c55fbc0 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp @@ -37,6 +37,29 @@ using namespace arm_compute; +namespace +{ +/** Calculates expected output shape dimension + * + * @param[in] Input shape + * + * @return Expected output shape + */ +TensorShape get_output_shape(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info) +{ + unsigned int output_width = 0; + unsigned int output_height = 0; + + std::tie(output_width, output_height) = scaled_dimensions(input_shape.x(), input_shape.y(), weights_shape.x(), weights_shape.y(), conv_info); + + TensorShape output_shape = input_shape; + output_shape.set(0, output_width); + output_shape.set(1, output_height); + + return output_shape; +} +} // namespace + CLDepthwiseConvolution3x3Kernel::CLDepthwiseConvolution3x3Kernel() : _border_size(0), _input(), _output(), _weights(), _biases(), _conv_stride_x(0), _conv_stride_y(0), _conv_pad_left(0), _conv_pad_top(0) { @@ -50,9 +73,7 @@ BorderSize CLDepthwiseConvolution3x3Kernel::border_size() const void CLDepthwiseConvolution3x3Kernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QASYMM8, DataType::F32); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != 3 || weights->info()->dimension(1) != 3); if(biases != nullptr) @@ -69,13 +90,18 @@ void CLDepthwiseConvolution3x3Kernel::configure(const ICLTensor *input, const IC ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1); } - std::pair<unsigned int, unsigned int> expected_output = scaled_dimensions(input->info()->tensor_shape().x(), input->info()->tensor_shape().y(), - weights->info()->tensor_shape().x(), weights->info()->tensor_shape().y(), - conv_info); + // Get convolved dimensions + TensorShape output_shape = get_output_shape(input->info()->tensor_shape(), weights->info()->tensor_shape(), conv_info); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), + output_shape, + 1, + input->info()->data_type(), + input->info()->fixed_point_position(), + input->info()->quantization_info()); - ARM_COMPUTE_UNUSED(expected_output); - ARM_COMPUTE_ERROR_ON(expected_output.first != output->info()->tensor_shape().x()); - ARM_COMPUTE_ERROR_ON(expected_output.second != output->info()->tensor_shape().y()); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); _input = input; _output = output; diff --git a/src/graph/nodes/ConvolutionLayer.cpp b/src/graph/nodes/ConvolutionLayer.cpp index a7236fc78a..ae4a8d7e6b 100644 --- a/src/graph/nodes/ConvolutionLayer.cpp +++ b/src/graph/nodes/ConvolutionLayer.cpp @@ -189,7 +189,7 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph in->info()->data_type(), in->info()->fixed_point_position())); } - if(_biases.tensor() == nullptr) + if(_biases.has_accessor() && _biases.tensor() == nullptr) { _biases.set_info(TensorInfo(TensorShape(_ofm), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); } @@ -200,11 +200,14 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph // Check if the weights and biases are loaded bool weights_are_loaded = _weights.tensor() != nullptr; - bool biases_are_loaded = _weights.tensor() != nullptr; + bool biases_are_loaded = _biases.has_accessor() ? _biases.tensor() != nullptr : true; // Set bias and weights target _weights.set_target(_target_hint); - _biases.set_target(_target_hint); + if(_biases.has_accessor()) + { + _biases.set_target(_target_hint); + } // Calculate output shape TensorShape output_shape = calculate_convolution_layer_output_shape(in->info()->tensor_shape(), _weights.info().tensor_shape(), _conv_info); diff --git a/src/graph/nodes/DepthwiseConvolutionLayer.cpp b/src/graph/nodes/DepthwiseConvolutionLayer.cpp index 1c006d61db..ceac2a2def 100644 --- a/src/graph/nodes/DepthwiseConvolutionLayer.cpp +++ b/src/graph/nodes/DepthwiseConvolutionLayer.cpp @@ -51,10 +51,13 @@ std::unique_ptr<arm_compute::IFunction> DepthwiseConvolutionLayer::instantiate_n } bool weights_is_loaded = _weights.tensor() != nullptr; - bool biases_is_loaded = _biases.has_accessor() ? _biases.tensor() != nullptr : false; + bool biases_is_loaded = _biases.has_accessor() ? _biases.tensor() != nullptr : true; _weights.set_target(_target_hint); - _biases.set_target(_target_hint); + if(_biases.has_accessor()) + { + _biases.set_target(_target_hint); + } // Create node context NodeContext node_ctx(OperationType::DepthwiseConvolutionLayer); diff --git a/src/graph/nodes/ReshapeLayer.cpp b/src/graph/nodes/ReshapeLayer.cpp index 4967534879..bbe0739e64 100644 --- a/src/graph/nodes/ReshapeLayer.cpp +++ b/src/graph/nodes/ReshapeLayer.cpp @@ -47,11 +47,11 @@ std::unique_ptr<arm_compute::IFunction> ReshapeLayer::instantiate_node(GraphCont arm_compute::auto_init_if_empty(*out->info(), _shape, 1, in->info()->data_type(), in->info()->fixed_point_position()); // Create node context - NodeContext node_ctx(OperationType::QuantizationLayer); + NodeContext node_ctx(OperationType::ReshapeLayer); node_ctx.set_target(_target_hint); node_ctx.add_input(in); node_ctx.add_output(out); // Get function - return OperationRegistry::get().find_operation(OperationType::QuantizationLayer, _target_hint)->configure(node_ctx); + return OperationRegistry::get().find_operation(OperationType::ReshapeLayer, _target_hint)->configure(node_ctx); } diff --git a/src/graph/operations/CLSimpleOperations.cpp b/src/graph/operations/CLSimpleOperations.cpp index 881f4910ad..647f88f0e2 100644 --- a/src/graph/operations/CLSimpleOperations.cpp +++ b/src/graph/operations/CLSimpleOperations.cpp @@ -138,7 +138,7 @@ REGISTER_SIMPLE_OPERATION(CLDepthConvertLayerOperation, OPENCL, OperationType::D /* DepthwiseConvolutionLayer Layer */ REGISTER_SIMPLE_OPERATION(CLDepthwiseConvolutionOperation, OPENCL, OperationType::DepthwiseConvolutionLayer) { - ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 2 || ctx.num_inputs() != 3); + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 2 && ctx.num_inputs() != 3); ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0)) == nullptr); ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr); diff --git a/src/graph/operations/NESimpleOperations.cpp b/src/graph/operations/NESimpleOperations.cpp index c77aeeca11..f234341cec 100644 --- a/src/graph/operations/NESimpleOperations.cpp +++ b/src/graph/operations/NESimpleOperations.cpp @@ -138,7 +138,7 @@ REGISTER_SIMPLE_OPERATION(NEDepthConvertLayerOperation, NEON, OperationType::Dep /* DepthwiseConvolutionLayer Layer */ REGISTER_SIMPLE_OPERATION(NEDepthwiseConvolutionOperation, NEON, OperationType::DepthwiseConvolutionLayer) { - ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 2 || ctx.num_inputs() != 3); + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 2 && ctx.num_inputs() != 3); ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); diff --git a/src/runtime/CL/functions/CLDepthwiseConvolution.cpp b/src/runtime/CL/functions/CLDepthwiseConvolution.cpp index a701391c44..81149508dd 100644 --- a/src/runtime/CL/functions/CLDepthwiseConvolution.cpp +++ b/src/runtime/CL/functions/CLDepthwiseConvolution.cpp @@ -38,8 +38,7 @@ CLDepthwiseConvolution3x3::CLDepthwiseConvolution3x3() void CLDepthwiseConvolution3x3::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::F32); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); _kernel.set_target(CLScheduler::get().target()); _kernel.configure(input, weights, biases, output, conv_info); |