| /* |
| * Copyright (c) 2021-2022 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. |
| */ |
| |
| #pragma once |
| |
| #include "depthwise_depthfirst.hpp" |
| #include "interleaves/generic_quantized_dot_product.hpp" |
| |
| #ifdef CYCLE_PROFILING |
| #include "profiler.hpp" |
| #endif |
| |
| #include <limits> |
| |
| namespace arm_conv { |
| namespace depthwise { |
| |
| template <typename TInput, typename TWeight, typename TOutput, typename TAccum> |
| class DepthfirstMultiplierStrategy : public DepthwiseDepthfirstStrategyCommon<TInput, TWeight, TOutput, TAccum, Nothing> |
| { |
| using Parent = DepthwiseDepthfirstStrategyCommon<TInput, TWeight, TOutput, TAccum, Nothing>; |
| |
| protected: |
| virtual interleaves::PackingArguments get_packing_args(const DepthwiseArgs &args) const |
| { |
| return interleaves::PackingArguments( |
| args.kernel_rows, args.kernel_cols, sizeof(TWeight), |
| true, sizeof(TAccum), |
| this->get_vl_type(), |
| sizeof(TAccum), 1, |
| [args] (unsigned int pos, unsigned int &x, unsigned int &y) -> bool |
| { |
| if (pos < args.kernel_rows * args.kernel_cols) |
| { |
| y = pos % args.kernel_cols; |
| x = pos / args.kernel_cols; |
| return true; |
| } |
| return false; |
| } |
| ); |
| } |
| |
| public: |
| using Parent::Parent; |
| |
| size_t get_storage_size(const DepthwiseArgs &args) const override |
| { |
| return interleaves::get_storage_size_generic(this->get_packing_args(args), args); |
| } |
| |
| void pack_parameters(const DepthwiseArgs &args, void *buffer, const void *biases, const Nothing &, const void *weights, size_t ld_weight_col, size_t ld_weight_row) const override |
| { |
| interleaves::pack_parameters_generic( |
| this->get_packing_args(args), args, |
| buffer, biases, weights, ld_weight_col, ld_weight_row |
| ); |
| } |
| |
| using KernelType = std::function<void( |
| const TInput *const *, // Input pointers |
| TOutput *const *, // Output pointers |
| const void *, // Ravelled bias, weights, and quantization parameters |
| unsigned int, // # output channels |
| TAccum, TAccum // Min and max activation clamps |
| )>; |
| virtual KernelType get_kernel(void) const = 0; |
| }; |
| |
| |
| template <typename TInput, typename TWeight, typename TOutput> |
| class DepthfirstMultiplierStrategy<TInput, TWeight, TOutput, int32_t> : public DepthwiseDepthfirstStrategyCommon<TInput, TWeight, TOutput, int32_t, arm_gemm::Requantize32> |
| { |
| using Parent = DepthwiseDepthfirstStrategyCommon<TInput, TWeight, TOutput, int32_t, arm_gemm::Requantize32>; |
| |
| public: |
| using Parent::Parent; |
| |
| size_t get_storage_size(const DepthwiseArgs &args) const override |
| { |
| return interleaves::quantized::get_storage_size(args, this->get_vl_type(), this->get_accumulator_depth_vl()); |
| } |
| |
| void pack_parameters(const DepthwiseArgs &args, void *buffer, const void *biases, const arm_gemm::Requantize32 &qp, const void *weights, size_t ld_weight_col, size_t ld_weight_row) const override |
| { |
| interleaves::quantized::pack_parameters<TWeight>( |
| buffer, reinterpret_cast<const int32_t *>(biases), |
| reinterpret_cast<const TWeight *>(weights), ld_weight_col, ld_weight_row, |
| args, qp, this->get_vl_type(), this->get_accumulator_depth_vl() |
| ); |
| } |
| |
| using KernelType = std::function<void( |
| const TInput *const *, // Input pointers |
| TOutput *const *, // Output pointers |
| const void *, // Ravelled bias, weights, and quantization parameters |
| unsigned int, // # output channels |
| const arm_gemm::Requantize32 & |
| )>; |
| virtual KernelType get_kernel(void) const = 0; |
| }; |
| |
| |
| template <typename TInput, typename TWeight, typename TOutput, typename TAccum> |
| class GenericDepthfirstMultiplierKernelStrategy |
| { |
| const arm_gemm::VLType m_vl_type; |
| const unsigned int m_output_rows, m_output_cols; |
| |
| public: |
| GenericDepthfirstMultiplierKernelStrategy(unsigned int output_rows, unsigned int output_cols, arm_gemm::VLType vl_type) |
| : m_vl_type(vl_type), m_output_rows(output_rows), m_output_cols(output_cols) |
| { |
| } |
| |
| virtual ~GenericDepthfirstMultiplierKernelStrategy() = default; |
| |
| arm_gemm::VLType get_vl_type(void) const { return m_vl_type; } |
| unsigned int get_output_rows(void) const { return m_output_rows; } |
| unsigned int get_output_cols(void) const { return m_output_cols; } |
| |
| using KernelType = std::function<void( |
| const TInput *const *, // Input pointers |
| TOutput *const *, // Output pointers |
| const TWeight *, // Ravelled weight parameters |
| const TAccum *, // Bias, |
| unsigned int, unsigned int, // Number of kernel points, number of output channels |
| TAccum, TAccum // Activation minimum and maximum |
| )>; |
| virtual KernelType get_kernel(void) const = 0; |
| }; |
| |
| template <typename TInput, typename TWeight, typename TOutput> |
| class GenericDepthfirstMultiplierKernelStrategy<TInput, TWeight, TOutput, int32_t> |
| { |
| const arm_gemm::VLType m_vl_type; |
| const unsigned int m_output_rows, m_output_cols; |
| |
| public: |
| GenericDepthfirstMultiplierKernelStrategy(unsigned int output_rows, unsigned int output_cols, arm_gemm::VLType vl_type) |
| : m_vl_type(vl_type), m_output_rows(output_rows), m_output_cols(output_cols) |
| { |
| } |
| |
| virtual ~GenericDepthfirstMultiplierKernelStrategy() = default; |
| |
| arm_gemm::VLType get_vl_type(void) const { return m_vl_type; } |
| unsigned int get_output_rows(void) const { return m_output_rows; } |
| unsigned int get_output_cols(void) const { return m_output_cols; } |
| |
| using KernelType = std::function<void( |
| const TInput *const *, // Input pointers |
| TOutput *const *, // Output pointers |
| const TWeight *, // Ravelled weight parameters |
| const int32_t *, // Bias, |
| unsigned int, unsigned int, // Number of kernel points, number of output channels |
| const int32_t *, const int32_t *, const int32_t *, // Per-channel left-shifts, multipliers, right-shifts (need to account for start channel) |
| const arm_gemm::Requantize32 & |
| )>; |
| virtual KernelType get_kernel(void) const = 0; |
| }; |
| |
| template <typename TInput, |
| typename TWeight=TInput, |
| typename TOutput=TInput, |
| typename TAccum=typename DefaultTAccum<TInput>::Type, |
| typename OutputStage=typename DefaultOutputStage<TOutput>::Type> |
| class GenericDepthfirstMultiplierStrategy : public DepthwiseDepthfirstStrategyCommon<TInput, TWeight, TOutput, TAccum, OutputStage> |
| { |
| using KernelStrategyType = GenericDepthfirstMultiplierKernelStrategy<TInput, TWeight, TOutput, TAccum>; |
| std::unique_ptr<KernelStrategyType> m_kern; |
| |
| protected: |
| virtual interleaves::PackingArguments get_packing_args(const DepthwiseArgs &args) const |
| { |
| return interleaves::PackingArguments( |
| args.kernel_rows, args.kernel_cols, sizeof(TWeight), |
| false, sizeof(TAccum), |
| this->get_vl_type(), |
| sizeof(TAccum), 1, |
| [args] (unsigned int pos, unsigned int &x, unsigned int &y) -> bool |
| { |
| if (pos < args.kernel_rows * args.kernel_cols) |
| { |
| y = pos % args.kernel_cols; |
| x = pos / args.kernel_cols; |
| return true; |
| } |
| return false; |
| } |
| ); |
| } |
| |
| public: |
| GenericDepthfirstMultiplierStrategy(KernelStrategyType *kern, const DepthwiseArgs &args) |
| : DepthwiseDepthfirstStrategyCommon<TInput, TWeight, TOutput, TAccum, OutputStage>( |
| kern->get_output_rows(), kern->get_output_cols(), |
| args.kernel_rows, args.kernel_cols, |
| args.stride_rows, args.stride_cols |
| ), |
| m_kern(kern) |
| { |
| }; |
| |
| arm_gemm::VLType get_vl_type(void) const override { return m_kern->get_vl_type(); } |
| const typename KernelStrategyType::KernelType get_kernel(void) const { return m_kern->get_kernel(); } |
| |
| size_t get_storage_size(const DepthwiseArgs &args) const override |
| { |
| return interleaves::get_storage_size_generic(this->get_packing_args(args), args); |
| } |
| |
| void pack_parameters(const DepthwiseArgs &args, void *buffer, const void *biases, const OutputStage &, const void *weights, size_t ld_weight_col, size_t ld_weight_row) const override |
| { |
| interleaves::pack_parameters_generic( |
| this->get_packing_args(args), args, |
| buffer, biases, weights, ld_weight_col, ld_weight_row |
| ); |
| } |
| }; |
| |
| // Specialise elements of the wrapper based on the type of kernel. |
| namespace depthfirst_multiplier { |
| |
| /* Working space element which contains a pointer for each row of input, a row |
| * of padding, and a space which can be used to construct an NCHW-ordered patch |
| * of input. |
| */ |
| template <typename T, bool IsGeneric=false, typename OutputStage=Nothing> |
| class InputPatchElement |
| { |
| public: |
| struct Workspace |
| { |
| constexpr static bool InputPatchIsGeneric = IsGeneric; |
| const T **input_rows; |
| T *input_padding; |
| T *input_patch; |
| }; |
| |
| static size_t get_element_size(const WorkspaceArgs<IDepthfirstStrategy, OutputStage> &args) |
| { |
| return sizeof_input_rows(args) + sizeof_input_padding(args) + sizeof_input_patch(args); |
| } |
| |
| template <class WorkspaceType> |
| static void *initialise(WorkspaceType *ws, void *buffer, const WorkspaceArgs<IDepthfirstStrategy, OutputStage> &args) |
| { |
| auto buffer_bytes = reinterpret_cast<char *>(buffer); |
| |
| ws->input_rows = reinterpret_cast<const T **>(buffer_bytes); |
| buffer_bytes += sizeof_input_rows(args); |
| |
| ws->input_padding = reinterpret_cast<T*>(buffer_bytes); |
| buffer_bytes += sizeof_input_padding(args); |
| |
| ws->input_patch = reinterpret_cast<T*>(buffer_bytes); |
| buffer_bytes += sizeof_input_patch(args); |
| |
| // Initialise the padding |
| memset(ws->input_padding, |
| get_input_buffer_fill_value(args.output_stage), |
| sizeof_input_padding(args)); |
| |
| return buffer_bytes; |
| } |
| |
| protected: |
| static size_t sizeof_input_rows(const WorkspaceArgs<IDepthfirstStrategy, OutputStage> &args) |
| { |
| if (IsGeneric) |
| { |
| return sizeof(T *) * args.strategy->get_output_rows() * args.depthwise_args.kernel_rows * args.depthwise_args.kernel_cols; |
| } |
| else |
| { |
| return sizeof(T *) * args.strategy->get_input_rows(); |
| } |
| } |
| |
| static size_t sizeof_input_padding(const WorkspaceArgs<IDepthfirstStrategy, OutputStage> &args) |
| { |
| // Round-up the number of columns to be a whole number of QUADS |
| auto input_cols = arm_gemm::roundup<size_t>(args.strategy->get_input_cols(), 16 / sizeof(T)); |
| return sizeof(T) * input_cols; |
| } |
| |
| static size_t sizeof_input_patch(const WorkspaceArgs<IDepthfirstStrategy, OutputStage> &args) |
| { |
| if (IsGeneric) |
| { |
| // Round-up the number of columns to be a whole number of QUADS |
| auto output_cols = arm_gemm::roundup<size_t>(args.strategy->get_output_cols(), 16 / sizeof(T)); |
| const auto kernel_points = args.depthwise_args.kernel_rows * args.depthwise_args.kernel_cols; |
| return sizeof(T) * kernel_points * args.strategy->get_output_rows() * output_cols; |
| } |
| else |
| { |
| // Round-up the number of columns to be a whole number of QUADS |
| auto input_cols = arm_gemm::roundup<size_t>(args.strategy->get_input_cols(), 16 / sizeof(T)); |
| return sizeof(T) * args.strategy->get_input_rows() * input_cols; |
| } |
| } |
| }; |
| |
| template <bool IsGeneric, typename TInput, typename TWeight, typename TOutput, typename TAccum, typename OutputStage> |
| struct StrategyType |
| { |
| using Type = DepthfirstMultiplierStrategy<TInput, TWeight, TOutput, TAccum>; |
| |
| template <typename WorkspaceType> |
| static void execute( |
| const DepthwiseArgs &args, const WorkspaceType *ws, const Type *strat, |
| const OutputStage &, const unsigned int, |
| const void *parameters, const void * |
| ) |
| { |
| strat->get_kernel()( |
| ws->input_rows, |
| ws->outptr_array, |
| parameters, args.channel_multiplier, |
| ws->activation_min, ws->activation_max |
| ); |
| } |
| }; |
| |
| template <typename TInput, typename TWeight, typename TOutput, typename TAccum, typename OutputStage> |
| struct StrategyType<true, TInput, TWeight, TOutput, TAccum, OutputStage> |
| { |
| using Type = GenericDepthfirstMultiplierStrategy<TInput, TWeight, TOutput, TAccum, OutputStage>; |
| |
| template <typename WorkspaceType> |
| static void execute( |
| const DepthwiseArgs &args, const WorkspaceType *ws, const Type *strat, |
| const OutputStage &, const unsigned int start_output_channel, |
| const void *parameters, const void *bias |
| ) |
| { |
| strat->get_kernel()( |
| ws->input_rows, ws->outptr_array, |
| reinterpret_cast<const TWeight *>(parameters), |
| bias == nullptr ? nullptr : reinterpret_cast<const TAccum *>(bias) + start_output_channel, |
| strat->get_kernel_rows() * strat->get_kernel_cols(), |
| args.channel_multiplier, |
| ws->activation_min, ws->activation_max |
| ); |
| } |
| }; |
| |
| template <typename TInput, typename TWeight, typename TOutput> |
| struct StrategyType<false, TInput, TWeight, TOutput, int32_t, arm_gemm::Requantize32> |
| { |
| using Type = DepthfirstMultiplierStrategy<TInput, TWeight, TOutput, int32_t>; |
| |
| template <typename WorkspaceType> |
| static void execute( |
| const DepthwiseArgs &args, const WorkspaceType *ws, const Type *strat, |
| const arm_gemm::Requantize32 &qp, const unsigned int, |
| const void *parameters, const void * |
| ) |
| { |
| strat->get_kernel()( |
| ws->input_rows, |
| ws->outptr_array, |
| parameters, args.channel_multiplier, |
| qp |
| ); |
| } |
| }; |
| |
| template <typename TInput, typename TWeight, typename TOutput> |
| struct StrategyType<true, TInput, TWeight, TOutput, int32_t, arm_gemm::Requantize32> |
| { |
| using Type = GenericDepthfirstMultiplierStrategy<TInput, TWeight, TOutput, int32_t, arm_gemm::Requantize32>; |
| |
| template <typename WorkspaceType> |
| static void execute( |
| const DepthwiseArgs &args, const WorkspaceType *ws, const Type *strat, |
| const arm_gemm::Requantize32 &qp, const unsigned int start_output_channel, |
| const void *parameters, const void * |
| ) |
| { |
| auto get_ptr = [start_output_channel] (const int32_t *ptr) -> const int32_t * |
| { |
| return ptr == nullptr ? nullptr : ptr + start_output_channel; |
| }; |
| |
| strat->get_kernel()( |
| ws->input_rows, ws->outptr_array, |
| reinterpret_cast<const TWeight *>(parameters), |
| get_ptr(qp.bias), |
| strat->get_kernel_rows() * strat->get_kernel_cols(), |
| args.channel_multiplier, |
| get_ptr(qp.per_channel_left_shifts), |
| get_ptr(qp.per_channel_muls), |
| get_ptr(qp.per_channel_right_shifts), |
| qp |
| ); |
| } |
| }; |
| |
| template <bool IsGeneric> struct PrepareInputSample; |
| |
| template <> struct PrepareInputSample<false> |
| { |
| template <typename WorkspaceType, typename StrategyType, typename T> |
| static void execute( |
| const DepthwiseArgs &, WorkspaceType *ws, const StrategyType *strat, |
| T *base_ptr, size_t ld_row, size_t ld_col, |
| const unsigned int input_pad_top, const unsigned int valid_rows, |
| const unsigned int input_pad_left, const unsigned int valid_cols |
| ) |
| { |
| fill_nchw_patch_array( |
| ws->input_rows, ws->input_patch, strat->get_input_rows(), strat->get_input_cols(), |
| base_ptr, ld_row, ld_col, |
| ws->input_padding, |
| input_pad_top, valid_rows, |
| input_pad_left, valid_cols |
| ); |
| } |
| }; |
| |
| template <> struct PrepareInputSample<true> |
| { |
| template <typename WorkspaceType, typename StrategyType, typename T> |
| static void execute( |
| const DepthwiseArgs &args, WorkspaceType *ws, const StrategyType *strat, |
| T *base_ptr, size_t ld_row, size_t ld_col, |
| const unsigned int input_pad_top, const unsigned int valid_rows, |
| const unsigned int input_pad_left, const unsigned int valid_cols |
| ) |
| { |
| fill_patch_array_generic_kernel( |
| ws->input_rows, ws->input_patch, |
| strat->get_output_rows(), strat->get_output_cols(), |
| args.kernel_rows, args.kernel_cols, |
| args.stride_rows, args.stride_cols, |
| base_ptr, ld_row, ld_col, |
| ws->input_padding, |
| input_pad_top, valid_rows, |
| input_pad_left, valid_cols |
| ); |
| } |
| }; |
| |
| } // namespace depthfirst_multiplier |
| |
| template <typename TInput, |
| typename TWeight=TInput, |
| typename TOutput=TInput, |
| typename TAccum=typename DefaultTAccum<TInput>::Type, |
| bool is_generic=false, |
| typename OutputStage=typename DefaultOutputStage<TOutput>::Type> |
| class DepthwiseDepthfirstMultiplier : public DepthfirstDriver<TInput, TWeight, TOutput> |
| { |
| protected: |
| using StratType = typename depthfirst_multiplier::StrategyType<is_generic, TInput, TWeight, TOutput, TAccum, OutputStage>::Type; |
| using WorkspaceManager = Workspace< |
| OutputArrayElement<TOutput>, |
| depthfirst_multiplier::InputPatchElement<TInput, is_generic, OutputStage>, |
| ActivationsElement<TOutput, OutputStage> |
| >; |
| using WorkingSpace = typename WorkspaceManager::WorkspaceType; |
| |
| OutputStage m_os; // Copy of the output parameters |
| const void *m_bias = nullptr; // Copy of the bias (should we need it) |
| |
| public: |
| DepthwiseDepthfirstMultiplier(StratType *const strat, const DepthwiseArgs &args, const OutputStage &os = {}) |
| : DepthfirstDriver<TInput, TWeight, TOutput>(strat, args), m_os(os) |
| { |
| } |
| |
| DepthwiseDepthfirstMultiplier(DepthwiseDepthfirstMultiplier &) = delete; |
| DepthwiseDepthfirstMultiplier &operator=(DepthwiseDepthfirstMultiplier &) = delete; |
| |
| size_t get_storage_size(void) const override |
| { |
| return reinterpret_cast<const StratType *>(this->m_strat.get()) |
| ->get_storage_size(this->m_args); |
| } |
| |
| void pack_parameters(void *buffer, const void *biases, const void *weights, size_t ld_weight_col, size_t ld_weight_row) override |
| { |
| reinterpret_cast<const StratType *>(this->m_strat.get()) |
| ->pack_parameters(this->m_args, buffer, biases, m_os, weights, ld_weight_col, ld_weight_row); |
| m_bias = biases; |
| depthwise_depthfirst::stash_bias(m_os, biases); |
| } |
| |
| size_t get_working_size_per_thread(const unsigned int n_input_channels) const override |
| { |
| DepthwiseArgs args(this->m_args); |
| args.input_channels = n_input_channels; |
| return WorkspaceManager::get_sizeof_workspace(WorkspaceArgs<IDepthfirstStrategy, OutputStage>(this->m_strat.get(), args, m_os)); |
| } |
| |
| void initialise_working_space(void *buffer, unsigned int n_input_channels) const override |
| { |
| DepthwiseArgs args(this->m_args); |
| args.input_channels = n_input_channels; |
| return WorkspaceManager::initialise(buffer, WorkspaceArgs<IDepthfirstStrategy, OutputStage>(this->m_strat.get(), args, m_os)); |
| } |
| |
| void compute_tile_padded( |
| unsigned int output_i, unsigned int output_j, |
| unsigned int output_channel_start, unsigned int output_channel_end, |
| const TensorSpec<const TInput *> &input, |
| const TensorSpec<TOutput *> &output, |
| const void *parameters, |
| void *working_space_raw |
| ) const override |
| { |
| // Get the working space |
| auto ws = reinterpret_cast<WorkingSpace *>(working_space_raw); |
| |
| const int ii = static_cast<int>(output_i * this->m_args.stride_rows) - this->m_args.padding.top; |
| const auto input_pad_top = static_cast<unsigned int>(ii < 0 ? -ii : 0); |
| const auto input_i = static_cast<unsigned int>(ii < 0 ? 0 : ii); |
| |
| const int ij = static_cast<int>(output_j * this->m_args.stride_cols) - this->m_args.padding.left; |
| const auto input_pad_left = static_cast<unsigned int>(ij < 0 ? -ij : 0); |
| const auto input_j = static_cast<unsigned int>(ij < 0 ? 0 : ij); |
| |
| // Compute the output pointer array. We'll update this array after every |
| // invocation of the kernel. |
| fill_pointer_array( |
| ws->outptr_array, this->m_strat->get_output_rows(), this->m_strat->get_output_cols(), |
| output.base + output_i*output.ld_row + output_j*output.ld_col + output_channel_start, |
| output.ld_row, output.ld_col, |
| ws->output_buffer, |
| 0, this->m_args.output_rows - output_i, // Top padding, # valid rows |
| 0, this->m_args.output_cols - output_j // Left padding, # valid columns |
| ); |
| |
| // Compute the parameter stride |
| DepthwiseArgs single_iter(this->m_args); |
| single_iter.input_channels = 1; |
| const size_t parameter_stride = reinterpret_cast<const StratType *>(this->m_strat.get()) |
| ->get_storage_size(single_iter); |
| |
| for (; output_channel_start < output_channel_end; |
| output_channel_start += this->m_args.channel_multiplier) |
| { |
| // Compute the input pointer array |
| const auto input_channel = output_channel_start / this->m_args.channel_multiplier; |
| |
| // Construct the input patch |
| depthfirst_multiplier::PrepareInputSample<is_generic>::execute( |
| this->m_args, ws, this->m_strat.get(), |
| input.base + input_channel + input_i*input.ld_row + input_j*input.ld_col, input.ld_row, input.ld_col, |
| input_pad_top, this->m_args.input_rows - input_i, |
| input_pad_left, this->m_args.input_cols - input_j |
| ); |
| |
| // Execute the kernel |
| depthfirst_multiplier::StrategyType<is_generic, TInput, TWeight, TOutput, TAccum, OutputStage>::execute( |
| this->m_args, ws, reinterpret_cast<const StratType *>(this->m_strat.get()), m_os, output_channel_start, |
| parameters, m_bias |
| ); |
| |
| // Update the output pointers |
| for (unsigned int n = 0; n < this->m_strat->get_output_rows() * this->m_strat->get_output_cols(); n++) |
| { |
| ws->outptr_array[n] += this->m_args.channel_multiplier; |
| } |
| |
| // Progress the parameters |
| parameters = reinterpret_cast<const char *>(parameters) + parameter_stride; |
| } |
| } |
| }; |
| |
| } // namespace depthwise |
| } // namespace arm_conv |