diff options
Diffstat (limited to 'src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp')
| -rw-r--r-- | src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp | 268 |
1 files changed, 100 insertions, 168 deletions
diff --git a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp index f01b58a8b3..d9c21150df 100644 --- a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp @@ -246,28 +246,44 @@ void CLDepthwiseConvolutionLayer3x3::prepare() } } -CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayer() - : _im2col_kernel(), _weights_reshape_kernel(), _v2mm_kernel(), _vector_to_tensor_kernel(), _output_stage_kernel(), _activationlayer_function(), _v2mm_input_fill_border(), _v2mm_weights_fill_border(), - _input_reshaped(), _weights_reshaped(), _v2mm_output(), _output_reshaped(), _is_prepared(false), _is_quantized(false), _is_activationlayer_enabled(false), _original_weights(nullptr), - _optimised_function(nullptr) +CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager) + : _memory_group(std::move(memory_manager)), + _optimised_function(nullptr), + _dwc_native_kernel(), + _permute_input_to_nhwc(), + _permute_weights_to_nhwc(), + _permute_output_to_nchw(), + _permuted_input(), + _permuted_weights(), + _permuted_output(), + _original_weights(), + _needs_permute(false), + _is_prepared(false) { } void CLDepthwiseConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + ARM_COMPUTE_ERROR_THROW_ON(CLDepthwiseConvolutionLayer::validate(input->info(), + weights->info(), + biases != nullptr ? biases->info() : nullptr, + output->info(), + conv_info, + depth_multiplier, + act_info, + dilation)); const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH); const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); - ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_w) + (weights->info()->dimension(idx_w) - 1) * (dilation.x() - 1) > input->info()->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); - ARM_COMPUTE_ERROR_ON(weights->info()->dimension(idx_h) + (weights->info()->dimension(idx_h) - 1) * (dilation.y() - 1) > input->info()->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); - const bool can_run_optimised_3x3_kernel = (weights->info()->dimension(idx_w) == 3) && (weights->info()->dimension(idx_h) == 3); + _needs_permute = false; + _is_prepared = false; + _original_weights = weights; + if(bool(can_run_optimised_3x3_kernel)) { auto f = arm_compute::support::cpp14::make_unique<CLDepthwiseConvolutionLayer3x3>(); @@ -276,103 +292,46 @@ void CLDepthwiseConvolutionLayer::configure(ICLTensor *input, const ICLTensor *w } else { - const size_t idx_c = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::CHANNEL); - - const size_t weights_w = weights->info()->dimension(idx_w); - const size_t weights_h = weights->info()->dimension(idx_h); - const size_t weights_z = weights->info()->dimension(idx_c); - - _is_prepared = false; - _original_weights = weights; - _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); - - bool append_bias = (biases != nullptr) && !_is_quantized; - const GPUTarget gpu_target = CLScheduler::get().target(); - - // Calculate output shape - TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info, depth_multiplier, dilation); - - // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); - - // Output width and height - const unsigned int conv_w = output_shape[idx_w]; - const unsigned int conv_h = output_shape[idx_h]; - - // Set up intermediate tensors - const size_t patch_size = weights_w * weights_h + ((append_bias) ? 1 : 0); - const size_t conv_size = conv_w * conv_h; - - const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform(); - - // Im2Col configuration - TensorShape shape_im2col = input->info()->tensor_shape(); - shape_im2col.set(0, patch_size); - shape_im2col.set(1, conv_size); - shape_im2col.set(2, weights_z); - _input_reshaped.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col)); - _im2col_kernel.set_target(gpu_target); - _im2col_kernel.configure(input, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier, dilation); - CLScheduler::get().tune_kernel_static(_im2col_kernel); - - // Weights reshape configuration - const TensorShape shape_weights_reshape(patch_size, weights_z); - _weights_reshaped.allocator()->init(weights->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_weights_reshape)); - _weights_reshape_kernel.configure(weights, &_weights_reshaped, append_bias ? biases : nullptr); - - // GEMV configuration - DataType v2mm_dt = (input->info()->data_type() == DataType::QASYMM8) ? DataType::S32 : input->info()->data_type(); - TensorShape shape_v2mm_out = input->info()->tensor_shape(); - shape_v2mm_out.set(0, conv_size * weights_z); - shape_v2mm_out.set(1, 1); - shape_v2mm_out.set(2, 1); - _v2mm_output.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_data_type(v2mm_dt).set_tensor_shape(shape_v2mm_out)); - _v2mm_kernel.set_target(gpu_target); - _v2mm_kernel.configure(&_input_reshaped, &_weights_reshaped, &_v2mm_output); - CLScheduler::get().tune_kernel_static(_v2mm_kernel); - _output_reshaped.allocator()->init(_v2mm_output.info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(output_shape)); - _vector_to_tensor_kernel.configure(&_v2mm_output, (_is_quantized) ? &_output_reshaped : output, conv_w, conv_h); - - // Output staged configuration - if(_is_quantized) - { - const UniformQuantizationInfo output_quant_info = (output->info()->total_size() == 0) ? iq_info : oq_info; - - int output_multiplier = 0; - int output_shift = 0; - const float multiplier = iq_info.scale * wq_info.scale / output_quant_info.scale; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - _output_stage_kernel.configure(&_output_reshaped, biases, output, output_multiplier, output_shift, output_quant_info.offset); - _output_reshaped.allocator()->allocate(); - } + _needs_permute = input->info()->data_layout() == DataLayout::NCHW; - // Fill borders on inputs - PixelValue zero_in(static_cast<int32_t>(0)); - PixelValue zero_w(static_cast<int32_t>(0)); - if(_is_quantized) + ICLTensor *input_to_use = input; + const ICLTensor *weights_to_use = weights; + ICLTensor *output_to_use = output; + if(_needs_permute) { - zero_in = PixelValue(static_cast<int32_t>(iq_info.offset)); - zero_w = PixelValue(static_cast<int32_t>(wq_info.offset)); - } - BorderSize border_size = _v2mm_kernel.border_size(); - _v2mm_input_fill_border.configure(&_input_reshaped, border_size, BorderMode::CONSTANT, zero_in); + _memory_group.manage(&_permuted_input); + _memory_group.manage(&_permuted_output); - border_size.bottom = 0; - _v2mm_weights_fill_border.configure(&_weights_reshaped, border_size, BorderMode::CONSTANT, zero_w); + // Configure the function to transform the input tensor from NCHW -> NHWC + _permute_input_to_nhwc.configure(input, &_permuted_input, PermutationVector(2U, 0U, 1U)); + _permuted_input.info()->set_data_layout(DataLayout::NHWC); - // Allocate intermediate tensors - _input_reshaped.allocator()->allocate(); - _v2mm_output.allocator()->allocate(); + // Configure the function to transform the weights tensor from IHW -> HWI + _permute_weights_to_nhwc.configure(weights, &_permuted_weights, PermutationVector(2U, 0U, 1U)); + _permuted_weights.info()->set_data_layout(DataLayout::NHWC); + + // Set output quantization info before dwc kernel configure + _permuted_output.info()->set_quantization_info(output->info()->quantization_info()); + + input_to_use = &_permuted_input; + weights_to_use = &_permuted_weights; + output_to_use = &_permuted_output; + } - //Configure Activation Layer - _is_activationlayer_enabled = act_info.enabled(); + DWCWeightsKernelInfo dwc_weights_info; + dwc_weights_info.n0 = (depth_multiplier == 1) ? 8 : 1; + DWCKernelInfo dwc_info; + dwc_info.activation_info = act_info; + _dwc_native_kernel.configure(input_to_use, weights_to_use, biases, output_to_use, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation); - if(_is_activationlayer_enabled) + if(_needs_permute) { - _activationlayer_function.configure(output, nullptr, act_info); + _permuted_input.allocator()->allocate(); + + // Configure the function to transform the convoluted output to NCHW format + _permuted_output.info()->set_data_layout(DataLayout::NCHW); + _permute_output_to_nchw.configure(&_permuted_output, output, PermutationVector(1U, 2U, 0U)); + _permuted_output.allocator()->allocate(); } } } @@ -380,6 +339,8 @@ void CLDepthwiseConvolutionLayer::configure(ICLTensor *input, const ICLTensor *w Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); + const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); @@ -390,60 +351,36 @@ Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe if(!can_run_optimised_3x3_kernel) { - const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL); - - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(idx_c) * depth_multiplier) != weights->dimension(idx_c)); - - const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); - const bool append_bias = (biases != nullptr) && !is_quantized; - const TensorShape output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); - const size_t weights_w = weights->dimension(idx_w); - const size_t weights_h = weights->dimension(idx_h); - const size_t weights_z = weights->dimension(idx_c); - const unsigned int conv_w = output_shape[idx_w]; - const unsigned int conv_h = output_shape[idx_h]; - const size_t patch_size = weights_w * weights_h + ((append_bias) ? 1 : 0); - const size_t conv_size = conv_w * conv_h; - - TensorShape shape_im2col = input->tensor_shape(); - shape_im2col.set(0, patch_size); - shape_im2col.set(1, conv_size); - shape_im2col.set(2, weights_z); - TensorInfo input_reshaped(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col)); - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseIm2ColKernel::validate(input, &input_reshaped, Size2D(weights_w, weights_h), conv_info, append_bias, depth_multiplier, dilation)); - - const TensorShape shape_weights_reshape(patch_size, weights_z); - TensorInfo weights_reshaped(weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_weights_reshape)); - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerReshapeWeightsGenericKernel::validate(weights, &weights_reshaped, append_bias ? biases : nullptr)); - - DataType v2mm_dt = (input->data_type() == DataType::QASYMM8) ? DataType::S32 : input->data_type(); - TensorShape shape_v2mm_out = input->tensor_shape(); - shape_v2mm_out.set(0, conv_size * weights_z); - shape_v2mm_out.set(1, 1); - shape_v2mm_out.set(2, 1); - TensorInfo v2mm_output(input->clone()->set_is_resizable(true).reset_padding().set_data_type(v2mm_dt).set_tensor_shape(shape_v2mm_out)); - ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMMatrixVectorMultiplyKernel::validate(&input_reshaped, &weights_reshaped, &v2mm_output)); - - TensorInfo output_reshaped(v2mm_output.clone()->set_is_resizable(true).reset_padding().set_tensor_shape(output_shape)); - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseVectorToTensorKernel::validate(&v2mm_output, (is_quantized) ? &output_reshaped : output, conv_w, conv_h)); - - if(is_quantized) + DWCWeightsKernelInfo dwc_weights_info; + dwc_weights_info.n0 = (depth_multiplier == 1) ? 8 : 1; + DWCKernelInfo dwc_info; + dwc_info.activation_info = act_info; + + const bool needs_permute = input->data_layout() == DataLayout::NCHW; + + if(needs_permute) { - const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = (output->total_size() == 0) ? iq_info : output->quantization_info().uniform(); - - const float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - ARM_COMPUTE_UNUSED(multiplier); - ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); - ARM_COMPUTE_RETURN_ON_ERROR(CLDirectConvolutionLayerOutputStageKernel::validate(&output_reshaped, biases, output)); + TensorShape permuted_input_shape = input->tensor_shape(); + TensorShape permuted_weights_shape = weights->tensor_shape(); + TensorShape permuted_output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); + + permute(permuted_input_shape, PermutationVector(2U, 0U, 1U)); + permute(permuted_weights_shape, PermutationVector(2U, 0U, 1U)); + permute(permuted_output_shape, PermutationVector(2U, 0U, 1U)); + + const TensorInfo permuted_input = input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(DataLayout::NHWC); + const TensorInfo permuted_weights = weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(DataLayout::NHWC); + const TensorInfo permuted_output = output->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(DataLayout::NHWC); + + ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(input, &permuted_input, PermutationVector(2U, 0U, 1U))); + ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(weights, &permuted_weights, PermutationVector(2U, 0U, 1U))); + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(&permuted_input, &permuted_weights, biases, &permuted_output, dwc_weights_info, + dwc_info, conv_info, depth_multiplier, dilation)); + ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(&permuted_output, output, PermutationVector(1U, 2U, 0U))); } - - // Validate Activation Layer - if(act_info.enabled()) + else { - ARM_COMPUTE_RETURN_ON_ERROR(CLActivationLayer::validate(output, nullptr, act_info)); + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation)); } } else @@ -457,23 +394,22 @@ void CLDepthwiseConvolutionLayer::run() { prepare(); + MemoryGroupResourceScope scope_mg(_memory_group); + if(_optimised_function != nullptr) { _optimised_function->run(); } else { - CLScheduler::get().enqueue(_im2col_kernel); - CLScheduler::get().enqueue(_v2mm_input_fill_border); - CLScheduler::get().enqueue(_v2mm_kernel); - CLScheduler::get().enqueue(_vector_to_tensor_kernel); - if(_is_quantized) + if(_needs_permute) { - CLScheduler::get().enqueue(_output_stage_kernel); + _permute_input_to_nhwc.run(); } - if(_is_activationlayer_enabled) + CLScheduler::get().enqueue(_dwc_native_kernel); + if(_needs_permute) { - _activationlayer_function.run(); + _permute_output_to_nchw.run(); } } } @@ -484,21 +420,17 @@ void CLDepthwiseConvolutionLayer::prepare() { _optimised_function->prepare(); } - else + else if(!_is_prepared) { - if(!_is_prepared) + if(_needs_permute) { ARM_COMPUTE_ERROR_ON(!_original_weights->is_used()); - // Run weights reshaping and mark original weights tensor as unused - _weights_reshaped.allocator()->allocate(); - CLScheduler::get().enqueue(_weights_reshape_kernel); - CLScheduler::get().enqueue(_v2mm_weights_fill_border); + _permuted_weights.allocator()->allocate(); + _permute_weights_to_nhwc.run(); _original_weights->mark_as_unused(); - - CLScheduler::get().queue().finish(); - _is_prepared = true; } + _is_prepared = true; } } } // namespace arm_compute |