diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/cpu/kernels/CpuDirectConv3dKernel.cpp | 324 | ||||
-rw-r--r-- | src/cpu/kernels/CpuDirectConv3dKernel.h | 85 | ||||
-rw-r--r-- | src/cpu/operators/CpuDirectConv3d.cpp | 105 | ||||
-rw-r--r-- | src/cpu/operators/CpuDirectConv3d.h | 91 | ||||
-rw-r--r-- | src/runtime/NEON/functions/NEConv3D.cpp | 81 |
5 files changed, 686 insertions, 0 deletions
diff --git a/src/cpu/kernels/CpuDirectConv3dKernel.cpp b/src/cpu/kernels/CpuDirectConv3dKernel.cpp new file mode 100644 index 0000000000..fecdb2bcae --- /dev/null +++ b/src/cpu/kernels/CpuDirectConv3dKernel.cpp @@ -0,0 +1,324 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "src/cpu/kernels/CpuDirectConv3dKernel.h" + +#include "src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h" +#include "src/core/NEON/wrapper/wrapper.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/IAccessWindow.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "src/core/CPP/Validate.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" + +#include <algorithm> + +using namespace arm_compute::detail; + +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +namespace +{ +Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const Conv3dInfo &conv_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, weights, dst); + ARM_COMPUTE_RETURN_ERROR_ON(src->data_layout() != DataLayout::NDHWC); + ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, weights); + + const DataLayout data_layout = src->data_layout(); + const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); + + // Weight layout is D, H, W, Cin, Cout + ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 5); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(1) != src->dimension(channel_idx)); + + if(biases != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->dimension(0) != weights->dimension(0), + "biases size and number of output feature maps should match"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->num_dimensions() > 1, "biases should be one dimensional"); + } + + // Checks performed when output is configured + if(dst->total_size() != 0) + { + TensorShape output_shape = misc::shape_calculator::compute_conv3d_shape(src->tensor_shape(), weights->tensor_shape(), conv_info); + + DataType data_type = src->data_type(); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), output_shape); + ARM_COMPUTE_RETURN_ERROR_ON(dst->data_type() != data_type); + } + + return Status{}; +} + +/** Reduce a vector to be a scalar by accumulating all lanes in the vector + * + * @param[in] v Vector to be reduced. + * + * @return the wrapped-around number. + */ +auto vreduce(const float32x4_t &v) +{ + auto v0 = wrapper::vgethigh(v); + auto v1 = wrapper::vgetlow(v); + auto v_out = wrapper::vadd(v0, v1); + + float a = wrapper::vgetlane(v_out, 0); + float b = wrapper::vgetlane(v_out, 1); + return a + b; +} + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +auto vreduce(const float16x8_t &v) +{ + auto v0 = wrapper::vgethigh(v); + auto v1 = wrapper::vgetlow(v); + auto v_out = wrapper::vadd(v0, v1); + + float16_t a = wrapper::vgetlane(v_out, 0); + float16_t b = wrapper::vgetlane(v_out, 1); + float16_t c = wrapper::vgetlane(v_out, 2); + float16_t d = wrapper::vgetlane(v_out, 3); + return a + b + c + d; +} +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +} + +template <typename T> +void CpuDirectConv3dKernel::convolve_ndhwc(const Window &window, const ITensor *src, const ITensor *weights, const ITensor *biases, ITensor *dst) +{ + using vtype = wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>; + using vector_type = typename vtype::type; + using tag_type = typename vtype::tag_type; + constexpr int num_elems_read_per_iteration = 16 / sizeof(T); + + // Scalar quantities (N D H W Cin) + const int element_size = src->info()->element_size(); + const int input_stride_w = src->info()->strides_in_bytes().y() / element_size; + const int input_stride_h = src->info()->strides_in_bytes().z() / element_size; + const int input_stride_d = src->info()->strides_in_bytes()[3] / element_size; + const int input_stride_n = src->info()->strides_in_bytes()[4] / element_size; + const int input_dim_w = src->info()->dimension(1); + const int input_dim_h = src->info()->dimension(2); + const int input_dim_d = src->info()->dimension(3); + + // Kernel info (D H W Cin Cout) + const unsigned int kernel_stride_w = weights->info()->strides_in_bytes()[2] / element_size; + const unsigned int kernel_stride_h = weights->info()->strides_in_bytes()[3] / element_size; + const unsigned int kernel_stride_d = weights->info()->strides_in_bytes()[4] / element_size; + const int kernel_dim_w = weights->info()->dimension(2); + const int kernel_dim_h = weights->info()->dimension(3); + const int kernel_dim_d = weights->info()->dimension(4); + + // Convolution padding and stride + const int conv_pad_top = _conv_info.padding.top; + const int conv_pad_left = _conv_info.padding.left; + const int conv_pad_front = _conv_info.padding.front; + const int conv_stride_w = _conv_info.stride.width; + const int conv_stride_h = _conv_info.stride.height; + const int conv_stride_d = _conv_info.stride.depth; + + // Setup input window for the output iterator + Window window_out = window; + window_out.set(Window::DimX, Window::Dimension(0, 1, 1)); + + // Setup input window for the weights iterator + Window window_w = calculate_max_window(*weights->info(), Steps()); + window_w.set(Window::DimY, Window::Dimension(0, 1, 1)); + window_w.set(Window::DimZ, Window::Dimension(0, 1, 1)); + window_w.set(Window::DimW, Window::Dimension(0, 1, 1)); + window_w.set(4, Window::Dimension(0, 1, 1)); + + Iterator out(dst, window_out); + Iterator wei(weights, window_w); + + const T *biases_ptr = nullptr; + if(biases) + { + biases_ptr = reinterpret_cast<T *>(biases->buffer() + biases->info()->offset_first_element_in_bytes()); + } + execute_window_loop(window_out, [&](const Coordinates & id) + { + // We are computing the theoretical input starting points + const int in_w_start_t = static_cast<int>(id.y()) * conv_stride_w - conv_pad_left; + const int in_h_start_t = static_cast<int>(id.z()) * conv_stride_h - conv_pad_top; + const int in_d_start_t = static_cast<int>(id[3]) * conv_stride_d - conv_pad_front; + const int in_w_end_t = in_w_start_t + kernel_dim_w; + const int in_h_end_t = in_h_start_t + kernel_dim_h; + const int in_d_end_t = in_d_start_t + kernel_dim_d; + + // We are computing the valid initial and ending input points by checking the borders + const int in_w_start = std::max(in_w_start_t, 0); + const int in_h_start = std::max(in_h_start_t, 0); + const int in_d_start = std::max(in_d_start_t, 0); + const int in_w_end = std::min(in_w_end_t, input_dim_w); + const int in_h_end = std::min(in_h_end_t, input_dim_h); + const int in_d_end = std::min(in_d_end_t, input_dim_d); + + // We use the input points to select the valid weight points to use + const int wei_w_start = in_w_start - in_w_start_t; + const int wei_h_start = in_h_start - in_h_start_t; + const int wei_d_start = in_d_start - in_d_start_t; + const int wei_w_end = kernel_dim_w - (in_w_end_t - in_w_end); + const int wei_h_end = kernel_dim_h - (in_h_end_t - in_h_end); + const int wei_d_end = kernel_dim_d - (in_d_end_t - in_d_end); + + const int index_c_out_end = weights->info()->dimension(0); + const int index_c_in_end = weights->info()->dimension(1); + const T *const in_ptr_start = reinterpret_cast<const T *>(src->buffer() + src->info()->offset_first_element_in_bytes()) + id[4] * input_stride_n; + + execute_window_loop(window_w, [&](const Coordinates & id_w) + { + /* + * This is the loop in the weights, and it goes along OFM (output feature map) + */ + const auto weights_ptr_start = reinterpret_cast<const T *>(wei.ptr()); + T out_temp = static_cast<T>(0); + T *out_ptr = reinterpret_cast<T *>(out.ptr()); + for(int index_wei_d = wei_d_start, index_in_d = in_d_start; index_wei_d < wei_d_end; ++index_wei_d, ++index_in_d) + { + const auto in_ptr_d = in_ptr_start + index_in_d * input_stride_d; + const auto weights_ptr_d = weights_ptr_start + index_wei_d * kernel_stride_d; + for(int index_wei_h = wei_h_start, index_in_h = in_h_start; index_wei_h < wei_h_end; ++index_wei_h, ++index_in_h) + { + const T *const in_ptr_row = in_ptr_d + index_in_h * input_stride_h; + const T *const weights_ptr_row = weights_ptr_d + index_wei_h * kernel_stride_h; + for(int index_wei_w = wei_w_start, index_in_w = in_w_start; index_wei_w < wei_w_end; ++index_wei_w, ++index_in_w) + { + const T *in_ptr_mover = in_ptr_row + index_in_w * input_stride_w; + const T *weights_ptr_mover = weights_ptr_row + index_wei_w * kernel_stride_w; + int index_c_in = 0; + vector_type out_temp_vec = wrapper::vdup_n(static_cast<T>(0), tag_type()); + vector_type w_vec = wrapper::vdup_n(static_cast<T>(0), tag_type()); + for(; index_c_in <= index_c_in_end - num_elems_read_per_iteration; + index_c_in += num_elems_read_per_iteration, in_ptr_mover += num_elems_read_per_iteration) + { + const auto src_vec = wrapper::vloadq(in_ptr_mover); + //Load Cin weights + for(unsigned int k = 0; k < num_elems_read_per_iteration; ++k, weights_ptr_mover += index_c_out_end) + { + w_vec = wrapper::vsetlane(*weights_ptr_mover, w_vec, k); + } + out_temp_vec = wrapper::vmla(out_temp_vec, w_vec, src_vec); + } + out_temp += vreduce(out_temp_vec); + for(; index_c_in < index_c_in_end; ++index_c_in, ++in_ptr_mover, weights_ptr_mover += index_c_out_end) + { + const auto src_val = *(in_ptr_mover); + const auto w_val = *(weights_ptr_mover); + out_temp += src_val * w_val; + } + } + } + } + *(reinterpret_cast<T *>(out_ptr + id_w[0])) = (biases) ? out_temp + biases_ptr[id_w[0]] : out_temp; + }, + wei); + }, + out); +} + +void CpuDirectConv3dKernel::configure(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const Conv3dInfo &conv_info) +{ + ARM_COMPUTE_UNUSED(biases); + ARM_COMPUTE_ERROR_ON_NULLPTR(src, weights, dst); + + _conv_info = conv_info; + + // Get convolved dimensions + TensorShape output_shape = misc::shape_calculator::compute_conv3d_shape(src->tensor_shape(), weights->tensor_shape(), conv_info); + + DataType data_type = src->data_type(); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*dst, output_shape, 1, data_type); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, weights, biases, dst, conv_info)); + + // Configure kernel window + Window win = calculate_max_window(*dst, Steps()); + ICpuKernel::configure(win); +} + +Status CpuDirectConv3dKernel::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const Conv3dInfo &conv_info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, weights, biases, dst, conv_info)); + + return Status{}; +} + +void CpuDirectConv3dKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window); + + auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0); + auto weights = tensors.get_const_tensor(TensorType::ACL_SRC_1); + auto biases = tensors.get_const_tensor(TensorType::ACL_SRC_2); + auto dst = tensors.get_tensor(TensorType::ACL_DST); + + switch(src->info()->data_type()) + { + case DataType::F32: + { + convolve_ndhwc<float>(window, src, weights, biases, dst); + break; + } +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + case DataType::F16: + { + convolve_ndhwc<float16_t>(window, src, weights, biases, dst); + break; + } +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + default: + ARM_COMPUTE_ERROR("Data type not supported"); + break; + } +} + +const char *CpuDirectConv3dKernel::name() const +{ + return "CpuDirectConv3dKernel"; +} +} // namespace kernels +} // namespace cpu +} // namespace arm_compute
\ No newline at end of file diff --git a/src/cpu/kernels/CpuDirectConv3dKernel.h b/src/cpu/kernels/CpuDirectConv3dKernel.h new file mode 100644 index 0000000000..c7dcb0fb5e --- /dev/null +++ b/src/cpu/kernels/CpuDirectConv3dKernel.h @@ -0,0 +1,85 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ARM_COMPUTE_CPU_DIRECT_CONV3D_KERNEL_H +#define ARM_COMPUTE_CPU_DIRECT_CONV3D_KERNEL_H + +#include "arm_compute/runtime/FunctionDescriptors.h" +#include "src/core/common/Macros.h" +#include "src/cpu/ICpuKernel.h" +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +/** Interface for the kernel to perform 3D Direct Convolution Layer. */ +class CpuDirectConv3dKernel : public ICpuKernel +{ +public: + CpuDirectConv3dKernel() = default; + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuDirectConv3dKernel); + /** Set the src, weights, and dst tensor info. + * + * Valid data layouts: + * - NDHWC + * + * Valid data type configurations: + * |src0 |src1 |src2 |dst | + * |:--------------|:------------------|:------|:--------------| + * |F16 |F16 |F16 |F16 | + * |F32 |F32 |F32 |F32 | + * + * @param[in, out] src Input tensor info. + * @param[in] weights Set of kernels to convolve the input volume. + * The 2nd dimension must be the same as the input's volume 1st dimension. + * @param[in] biases Set of biases. Can be nullptr. + * @param[out] dst Output tensor info. + * The 1st dimensions must be equal to the 1st dimension of the @p kernels tensor. + * @param[in] conv_info Contains padding, stride, acitvation information. + * + */ + void configure(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const Conv3dInfo &conv_info); + /** Static function to check if given info will lead to a valid configuration + * + * Similar to CpuDirectConv3dKernel::configure() + * + * @return a status + */ + static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const Conv3dInfo &conv_info); + + // Inherited methods overridden: + void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override; + const char *name() const override; + +private: + /* Template function for convolution NDHWC */ + template <typename T> + void convolve_ndhwc(const Window &window, const ITensor *src, const ITensor *weights, const ITensor *biases, ITensor *dst); + + Conv3dInfo _conv_info{}; +}; +} // namespace kernels +} // namespace cpu +} // namespace arm_compute +#endif /*ARM_COMPUTE_CPU_DIRECTCONV3D_KERNEL_H */ diff --git a/src/cpu/operators/CpuDirectConv3d.cpp b/src/cpu/operators/CpuDirectConv3d.cpp new file mode 100644 index 0000000000..3827910d37 --- /dev/null +++ b/src/cpu/operators/CpuDirectConv3d.cpp @@ -0,0 +1,105 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "src/cpu/operators/CpuDirectConv3d.h" + +#include "arm_compute/core/PixelValue.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/runtime/NEON/NEScheduler.h" +#include "src/common/utils/Log.h" + +namespace arm_compute +{ +namespace cpu +{ +CpuDirectConv3d::~CpuDirectConv3d() = default; + +CpuDirectConv3d::CpuDirectConv3d(std::shared_ptr<IMemoryManager> memory_manager) + : _memory_group(std::move(memory_manager)), _conv_kernel(), _activationlayer_function(), _accumulator(), _is_activationlayer_enabled(false), _dim_split(Window::DimZ) +{ +} + +void CpuDirectConv3d::configure(ITensorInfo *src, ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const Conv3dInfo conv_info) +{ + ARM_COMPUTE_LOG_PARAMS(src, weights, biases, dst, conv_info); + ARM_COMPUTE_ERROR_ON(src->data_layout() != DataLayout::NDHWC); + + _conv_kernel = std::make_unique<kernels::CpuDirectConv3dKernel>(); + + // Free accumulator + if(_accumulator.buffer() != nullptr) + { + _accumulator.allocator()->free(); + } + + _dim_split = Window::DimY; + + _conv_kernel->configure(src, weights, biases, dst, conv_info); + + //Configure Activation Layer + _is_activationlayer_enabled = conv_info.act_info.enabled(); + if(_is_activationlayer_enabled) + { + _activationlayer_function = std::make_unique<CpuActivation>(); + _activationlayer_function->configure(dst, dst, conv_info.act_info); + } +} + +Status CpuDirectConv3d::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const Conv3dInfo conv_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, weights, dst); + + // output might not be initialized since it can be an intermediate tensor of another layer + DataType data_type = src->data_type(); + TensorInfo accumulator(dst->clone()->set_is_resizable(true).reset_padding().set_data_type(data_type)); + + // Validate Convolution kernel + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuDirectConv3dKernel::validate(src, weights, biases, &accumulator, conv_info)); + + if(conv_info.act_info.enabled()) + { + ARM_COMPUTE_RETURN_ON_ERROR(CpuActivation::validate(dst, nullptr, conv_info.act_info)); + } + + return Status{}; +} + +void CpuDirectConv3d::run(ITensorPack &tensors) +{ + MemoryGroupResourceScope scope_mg(_memory_group); + + auto dst = tensors.get_tensor(TensorType::ACL_DST); + + NEScheduler::get().schedule_op(_conv_kernel.get(), _dim_split, _conv_kernel->window(), tensors); + + if(_is_activationlayer_enabled) + { + ITensorPack pack; + pack.add_tensor(TensorType::ACL_SRC, dst); + pack.add_tensor(TensorType::ACL_DST, dst); + _activationlayer_function->run(pack); + } +} +} // namespace cpu +} // namespace arm_compute
\ No newline at end of file diff --git a/src/cpu/operators/CpuDirectConv3d.h b/src/cpu/operators/CpuDirectConv3d.h new file mode 100644 index 0000000000..ad04dee0fa --- /dev/null +++ b/src/cpu/operators/CpuDirectConv3d.h @@ -0,0 +1,91 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ARM_COMPUTE_CPU_DIRECTCONV3D_H +#define ARM_COMPUTE_CPU_DIRECTCONV3D_H + +#include "arm_compute/core/ITensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/experimental/Types.h" +#include "arm_compute/runtime/FunctionDescriptors.h" +#include "arm_compute/runtime/IMemoryManager.h" +#include "arm_compute/runtime/MemoryGroup.h" +#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" +#include "arm_compute/runtime/Tensor.h" +#include "src/core/NEON/kernels/NEFillBorderKernel.h" +#include "src/cpu/ICpuKernel.h" +#include "src/cpu/ICpuOperator.h" +#include "src/cpu/kernels/CpuDirectConv3dKernel.h" +#include "src/cpu/operators/CpuActivation.h" + +#include <memory> + +namespace arm_compute +{ +namespace cpu +{ +/** Function to run the direct convolution. + * + * This function calls the following kernels: + * + * -# @ref kernels::CpuDirectConv3dKernel + */ +class CpuDirectConv3d : public ICpuOperator +{ +public: + CpuDirectConv3d(std::shared_ptr<IMemoryManager> memory_manager = nullptr); + ~CpuDirectConv3d(); + /** Set the input, weights, biases and output tensor info. + * + * @param[in, out] src Input tensor info. + * @param[in] weights Set of kernels to convolve the input volume. + * The 2nd dimension must be the same as the input's volume 1st dimension. + * Data type supported: Same as @p src. + * @param[in] biases Set of biases. Can be nullptr. Data type supported: Same as @p src. + * @param[out] dst Output tensor info. + * The 1st dimensions must be equal to the 1st dimension of the @p kernels tensor. + * @param[in] conv_info Contains padding, stride, acitvation information. + */ + void configure(ITensorInfo *src, ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const Conv3dInfo conv_info); + /** Static function to check if given info will lead to a valid configuration + * + * Similar to CpuDirectConv3d::configure() + * + * @return a status + */ + static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const Conv3dInfo conv_info); + + // Inherited methods overridden: + void run(ITensorPack &tensors) override; + +private: + MemoryGroup _memory_group; + std::unique_ptr<kernels::CpuDirectConv3dKernel> _conv_kernel; + std::unique_ptr<CpuActivation> _activationlayer_function; + Tensor _accumulator; + bool _is_activationlayer_enabled{ false }; + unsigned int _dim_split{ 0 }; +}; +} // namespace cpu +} // namespace arm_compute +#endif /* ARM_COMPUTE_CPU_DIRECTCONV3D_H */ diff --git a/src/runtime/NEON/functions/NEConv3D.cpp b/src/runtime/NEON/functions/NEConv3D.cpp new file mode 100644 index 0000000000..b5e2e2a843 --- /dev/null +++ b/src/runtime/NEON/functions/NEConv3D.cpp @@ -0,0 +1,81 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/runtime/NEON/functions/NEConv3D.h" + +#include "arm_compute/core/PixelValue.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "src/common/utils/Log.h" +#include "src/core/helpers/MemoryHelpers.h" +#include "src/cpu/operators/CpuDirectConv3d.h" + +namespace arm_compute +{ +using namespace arm_compute::experimental; + +struct NEConv3D::Impl +{ + std::unique_ptr<cpu::ICpuOperator> op{ nullptr }; + ITensorPack run_pack{}; +}; + +NEConv3D::NEConv3D() + : _impl(std::make_unique<Impl>()) +{ +} + +NEConv3D::~NEConv3D() = default; + +void NEConv3D::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const Conv3dInfo &conv_info) +{ + // Perform validate step + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + ARM_COMPUTE_ERROR_THROW_ON(cpu::CpuDirectConv3d::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info)); + ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info); + + auto f = std::make_unique<cpu::CpuDirectConv3d>(); + f->configure(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info); + _impl->op = std::move(f); + + if(_impl->op) + { + _impl->run_pack = { { ACL_SRC_0, input }, { ACL_SRC_1, weights }, { ACL_SRC_2, biases }, { ACL_DST, output } }; + } +} + +Status NEConv3D::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const Conv3dInfo &conv_info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(cpu::CpuDirectConv3d::validate(input, weights, biases, output, conv_info)); + + return Status{}; +} + +void NEConv3D::run() +{ + if(_impl->op) + { + _impl->op->run(_impl->run_pack); + } +} +} // namespace arm_compute |