From 06b184ac568dc974986bae680957c4477f8ef6ca Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Tue, 29 Aug 2017 16:05:25 +0100 Subject: COMPMID-439 - Refactored NEQuantizationLayer and NEQuantizationLayer in order to support 3D input tensors Change-Id: I03eac2108a30bed56d40dfd52e75577a35d492e0 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/85783 Tested-by: Kaizen Reviewed-by: Michele DiGiorgio Reviewed-by: Georgios Pinitas --- .../NEON/kernels/NEDequantizationLayerKernel.cpp | 95 +++++++---- src/core/NEON/kernels/NEMinMaxLayerKernel.cpp | 190 +++++++++++++++++++++ .../NEON/kernels/NEQuantizationLayerKernel.cpp | 107 ++++++++---- 3 files changed, 322 insertions(+), 70 deletions(-) create mode 100644 src/core/NEON/kernels/NEMinMaxLayerKernel.cpp (limited to 'src/core') diff --git a/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp b/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp index 3bf2b35a09..70984f0a75 100644 --- a/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp +++ b/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp @@ -23,9 +23,9 @@ */ #include "arm_compute/core/NEON/kernels/NEDequantizationLayerKernel.h" +#include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" @@ -35,16 +35,16 @@ using namespace arm_compute; NEDequantizationLayerKernel::NEDequantizationLayerKernel() - : _input(nullptr), _output(nullptr), _min(nullptr), _max(nullptr) + : _input(nullptr), _output(nullptr), _min_max(nullptr) { } -void NEDequantizationLayerKernel::configure(const ITensor *input, ITensor *output, const float *min, const float *max) +void NEDequantizationLayerKernel::configure(const ITensor *input, ITensor *output, const ITensor *min_max) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); ARM_COMPUTE_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_ERROR_ON_NULLPTR(min); - ARM_COMPUTE_ERROR_ON_NULLPTR(max); + ARM_COMPUTE_ERROR_ON_NULLPTR(min_max); + ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() < 3); // Output tensor auto initialization if not yet initialized auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, DataType::F32, 0); @@ -52,17 +52,20 @@ void NEDequantizationLayerKernel::configure(const ITensor *input, ITensor *outpu ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); - _input = input; - _output = output; - _min = min; - _max = max; + _input = input; + _output = output; + _min_max = min_max; constexpr unsigned int num_elems_processed_per_iteration = 8; // Configure window Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - update_window_and_padding(win, AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration), output_access); + AccessWindowStatic min_max_access(min_max->info(), 0, 0, 2, min_max->info()->dimension(1)); + + // Update window and padding + update_window_and_padding(win, input_access, output_access, min_max_access); output_access.set_valid_region(win, input->info()->valid_region()); INEKernel::configure(win); @@ -74,31 +77,55 @@ void NEDequantizationLayerKernel::run(const Window &window, const ThreadInfo &in ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - Iterator input(_input, window); - Iterator output(_output, window); + Window window_input_output(window); + window_input_output.collapse_if_possible(INEKernel::window(), 3); + window_input_output.set(3, Window::Dimension(0, 1, 1)); + + Window window_min_max; + window_min_max.use_tensor_dimensions(_min_max->info()->tensor_shape()); + window_min_max.set(Window::DimX, Window::Dimension(0, 1, 1)); + window_min_max.collapse_if_possible(INEKernel::window(), 1); - const float32x4_t vmin = vdupq_n_f32(*_min); - const float range = *_max - *_min; - const float32x4_t scaling = vdupq_n_f32(range / 255.0f); + Iterator input(_input, window_input_output); + Iterator output(_output, window_input_output); + Iterator min_max(_min_max, window_min_max); - // Uniformly map values to range 8bit integers, i.e. [min, max] -> [0, 255] - execute_window_loop(window, [&](const Coordinates & id) + execute_window_loop(window_min_max, [&](const Coordinates & id_batch) { - const uint8x8_t val_u8 = vld1_u8(reinterpret_cast(input.ptr())); - const uint16x8_t val_u16 = vmovl_u8(val_u8); - const uint32x4_t val_u32_low = vmovl_u16(vget_low_u16(val_u16)); - const uint32x4_t val_u32_high = vmovl_u16(vget_high_u16(val_u16)); - float32x4_t val_low = vcvtq_f32_u32(val_u32_low); - float32x4_t val_high = vcvtq_f32_u32(val_u32_high); - - // Dequantize -> (q / 255.0 * range) + min - val_low = vmulq_f32(val_low, scaling); - val_high = vmulq_f32(val_high, scaling); - val_low = vaddq_f32(val_low, vmin); - val_high = vaddq_f32(val_high, vmin); - - const float32x4x2_t dequantized = vuzpq_f32(val_low, val_high); - vst2q_f32(reinterpret_cast(output.ptr()), dequantized); + // Get the min and max + const float min = *(reinterpret_cast(min_max.ptr()) + 0); + const float max = *(reinterpret_cast(min_max.ptr()) + 1); + + const float32x4_t vmin = vdupq_n_f32(min); + const float range = max - min; + const float32x4_t scaling = vdupq_n_f32(range / 255.0f); + + // Uniformly map values to range 8bit integers, i.e. [min, max] -> [0, 255] + execute_window_loop(window_input_output, [&](const Coordinates & id) + { + // Get the input values + const auto input_ptr = reinterpret_cast(input.ptr() + id_batch[1] * _input->info()->strides_in_bytes()[3]); + + const uint8x8_t val_u8 = vld1_u8(input_ptr); + const uint16x8_t val_u16 = vmovl_u8(val_u8); + const uint32x4_t val_u32_low = vmovl_u16(vget_low_u16(val_u16)); + const uint32x4_t val_u32_high = vmovl_u16(vget_high_u16(val_u16)); + float32x4_t val_low = vcvtq_f32_u32(val_u32_low); + float32x4_t val_high = vcvtq_f32_u32(val_u32_high); + + // Dequantize -> (q / 255.0 * range) + min + val_low = vmulq_f32(val_low, scaling); + val_high = vmulq_f32(val_high, scaling); + val_low = vaddq_f32(val_low, vmin); + val_high = vaddq_f32(val_high, vmin); + + const float32x4x2_t dequantized = vuzpq_f32(val_low, val_high); + + // Store the dequantized values + auto output_ptr = reinterpret_cast(output.ptr() + id_batch[1] * _output->info()->strides_in_bytes()[3]); + vst2q_f32(output_ptr, dequantized); + }, + input, output); }, - input, output); -} + min_max); +} \ No newline at end of file diff --git a/src/core/NEON/kernels/NEMinMaxLayerKernel.cpp b/src/core/NEON/kernels/NEMinMaxLayerKernel.cpp new file mode 100644 index 0000000000..5e6c48f4c2 --- /dev/null +++ b/src/core/NEON/kernels/NEMinMaxLayerKernel.cpp @@ -0,0 +1,190 @@ +/* + * Copyright (c) 2017 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/core/NEON/kernels/NEMinMaxLayerKernel.h" + +#include "arm_compute/core/Coordinates.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/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +#include +#include +#include +#include + +namespace arm_compute +{ +NEMinMaxLayerKernel::NEMinMaxLayerKernel() + : _input(nullptr), _output(nullptr), _mtx() +{ +} + +void NEMinMaxLayerKernel::configure(const ITensor *input, ITensor *output) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() < 3); + ARM_COMPUTE_ERROR_ON(output == nullptr); + + TensorShape output_shape{ input->info()->tensor_shape() }; + output_shape.set(Window::DimX, 2); + output_shape.remove_dimension(1); + output_shape.remove_dimension(1); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); + + _input = input; + _output = output; + + // Configure kernel window + constexpr unsigned int num_elems_processed_per_iteration = 1; + + Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(output->info(), 0, 2); + + update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); + + INEKernel::configure(win); +} + +void NEMinMaxLayerKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + + const int x_start = window.x().start(); + const int x_end = window.x().end(); + + Window window_output; + window_output.use_tensor_dimensions(_output->info()->tensor_shape()); + window_output.set(Window::DimX, Window::Dimension(0, 1, 1)); + + // Handle X dimension manually to split into two loops + // First one will use vector operations, second one processes the left over pixels + Window window_input(window); + window_input.set(Window::DimX, Window::Dimension(0, 1, 1)); + window_input.collapse_if_possible(INEKernel::window(), 3); + window_input.set(3, Window::Dimension(0, 1, 1)); + + Iterator input(_input, window_input); + Iterator output(_output, window_output); + + execute_window_loop(window_output, [&](const Coordinates & id_batch) + { + float32x2_t carry_min = vdup_n_f32(std::numeric_limits::max()); + float32x2_t carry_max = vdup_n_f32(std::numeric_limits::lowest()); + + float carry_min_scalar = std::numeric_limits::max(); + float carry_max_scalar = std::numeric_limits::lowest(); + + execute_window_loop(window_input, [&](const Coordinates & id) + { + int x = x_start; + const auto in_ptr = reinterpret_cast(input.ptr() + id_batch[1] * _input->info()->strides_in_bytes()[3]); + + // Vector loop + for(; x <= x_end - 8; x += 8) + { + const float32x4x2_t pixels = vld2q_f32(in_ptr + x); + const float32x4_t tmp_min1 = vminq_f32(pixels.val[0], pixels.val[1]); + const float32x4_t tmp_max1 = vmaxq_f32(pixels.val[0], pixels.val[1]); + const float32x2_t tmp_min2 = vmin_f32(vget_high_f32(tmp_min1), vget_low_f32(tmp_min1)); + const float32x2_t tmp_max2 = vmax_f32(vget_high_f32(tmp_max1), vget_low_f32(tmp_max1)); + carry_min = vmin_f32(tmp_min2, carry_min); + carry_max = vmax_f32(tmp_max2, carry_max); + } + + // Process leftover pixels + for(; x < x_end; ++x) + { + const float pixel = in_ptr[x]; + carry_min_scalar = std::min(pixel, carry_min_scalar); + carry_max_scalar = std::max(pixel, carry_max_scalar); + } + }, + input); + + // Reduce result + carry_min = vpmin_f32(carry_min, carry_min); + carry_max = vpmax_f32(carry_max, carry_max); + carry_min = vpmin_f32(carry_min, carry_min); + carry_max = vpmax_f32(carry_max, carry_max); + + // Extract max/min values + const float min_i = std::min(vget_lane_f32(carry_min, 0), carry_min_scalar); + const float max_i = std::max(vget_lane_f32(carry_max, 0), carry_max_scalar); + + auto out_ptr = reinterpret_cast(output.ptr()); + + // Perform reduction of local min/max values + update_min_max(out_ptr, min_i, max_i); + }, + output); +} + +void NEMinMaxLayerKernel::reset() +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + + float32x2_t reset_values = vdup_n_f32(0.0f); + reset_values = vset_lane_f32(std::numeric_limits::max(), reset_values, 0); + reset_values = vset_lane_f32(std::numeric_limits::min(), reset_values, 1); + + Window window_output; + window_output.use_tensor_dimensions(_output->info()->tensor_shape()); + window_output.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator output(_output, window_output); + + execute_window_loop(window_output, [&](const Coordinates & id) + { + vst1_f32(reinterpret_cast(output.ptr()), reset_values); + }, + output); +} + +void NEMinMaxLayerKernel::update_min_max(float *out_ptr, float min, float max) +{ + std::lock_guard lock(_mtx); + + const float32x2_t old_min = vld1_dup_f32(out_ptr); + const float32x2_t old_max = vld1_dup_f32(out_ptr + 1); + const float32x2_t new_min = vmin_f32(vdup_n_f32(min), old_min); + const float32x2_t new_max = vmax_f32(vdup_n_f32(max), old_max); + + vst1_f32(out_ptr, vzip_f32(new_min, new_max).val[0]); +} +} // namespace arm_compute \ No newline at end of file diff --git a/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp b/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp index a596d835cb..bff79f0f0c 100644 --- a/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp +++ b/src/core/NEON/kernels/NEQuantizationLayerKernel.cpp @@ -23,9 +23,9 @@ */ #include "arm_compute/core/NEON/kernels/NEQuantizationLayerKernel.h" +#include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" @@ -35,14 +35,15 @@ using namespace arm_compute; NEQuantizationLayerKernel::NEQuantizationLayerKernel() - : _input(nullptr), _output(nullptr), _min(nullptr), _max(nullptr) + : _input(nullptr), _output(nullptr), _min_max(nullptr) { } -void NEQuantizationLayerKernel::configure(const ITensor *input, ITensor *output, const float *min, const float *max) +void NEQuantizationLayerKernel::configure(const ITensor *input, ITensor *output, const ITensor *min_max) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); ARM_COMPUTE_ERROR_ON_NULLPTR(output); + ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() < 3); // Output tensor auto initialization if not yet initialized auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, DataType::U8, 0); @@ -50,17 +51,20 @@ void NEQuantizationLayerKernel::configure(const ITensor *input, ITensor *output, ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); - _input = input; - _output = output; - _min = min; - _max = max; + _input = input; + _output = output; + _min_max = min_max; constexpr unsigned int num_elems_processed_per_iteration = 8; // Configure window Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - update_window_and_padding(win, AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration), output_access); + AccessWindowStatic min_max_access(min_max->info(), 0, 0, 2, min_max->info()->dimension(1)); + + // Update window and padding + update_window_and_padding(win, input_access, output_access, min_max_access); output_access.set_valid_region(win, input->info()->valid_region()); INEKernel::configure(win); @@ -72,36 +76,67 @@ void NEQuantizationLayerKernel::run(const Window &window, const ThreadInfo &info ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - Iterator input(_input, window); - Iterator output(_output, window); + Window window_input_output(window); + window_input_output.collapse_if_possible(INEKernel::window(), 3); + window_input_output.set(3, Window::Dimension(0, 1, 1)); + + Window window_min_max; + window_min_max.use_tensor_dimensions(_min_max->info()->tensor_shape()); + window_min_max.set(Window::DimX, Window::Dimension(0, 1, 1)); + window_min_max.collapse_if_possible(INEKernel::window(), 1); - const float32x4_t vmin = vdupq_n_f32(*_min); - const float32x4_t inv_range = vdupq_n_f32(1.0f / (*_max - *_min)); - const float32x4_t quantization_max = vdupq_n_f32(255.0f); - const float32x4_t quantization_mul = vdupq_n_f32(256.0f); + Iterator input(_input, window_input_output); + Iterator output(_output, window_input_output); + Iterator min_max(_min_max, window_min_max); - // Uniformly map values to range 8bit integers, i.e. [min, max] -> [0, 255] - execute_window_loop(window, [&](const Coordinates & id) + execute_window_loop(window_min_max, [&](const Coordinates & id_batch) { - float32x4x2_t val = vld2q_f32(reinterpret_cast(input.ptr())); - // Map float values to range [0.0, 1.0] - val.val[0] = vsubq_f32(val.val[0], vmin); - val.val[1] = vsubq_f32(val.val[1], vmin); - val.val[0] = vmulq_f32(val.val[0], inv_range); - val.val[1] = vmulq_f32(val.val[1], inv_range); - - // Quantize - val.val[0] = vmulq_f32(val.val[0], quantization_mul); - val.val[1] = vmulq_f32(val.val[1], quantization_mul); - val.val[0] = vminq_f32(val.val[0], quantization_max); - val.val[1] = vminq_f32(val.val[1], quantization_max); - - const uint32x4_t val_u32_low = vcvtq_u32_f32(val.val[0]); - const uint32x4_t val_u32_high = vcvtq_u32_f32(val.val[1]); - const uint16x4x2_t val_u16 = vzip_u16(vmovn_u32(val_u32_low), vmovn_u32(val_u32_high)); - - const uint8x8_t quantized = vmovn_u16(vcombine_u16(val_u16.val[0], val_u16.val[1])); - vst1_u8(reinterpret_cast(output.ptr()), quantized); + // Get the min and max + float min = *(reinterpret_cast(min_max.ptr()) + 0); + float max = *(reinterpret_cast(min_max.ptr()) + 1); + + // Saturate the result if min = max + if(min == max) + { + min = 0.0f; + max = 1.0f; + } + + const float32x4_t vmin = vdupq_n_f32(min); + const float32x4_t inv_range = vdupq_n_f32(1.0f / (max - min)); + const float32x4_t quantization_max = vdupq_n_f32(255.0f); + const float32x4_t quantization_mul = vdupq_n_f32(256.0f); + + // Uniformly map values to range 8bit integers, i.e. [min, max] -> [0, 255] + execute_window_loop(window_input_output, [&](const Coordinates & id) + { + // Get the input values + const auto input_ptr = reinterpret_cast(input.ptr() + id_batch[1] * _input->info()->strides_in_bytes()[3]); + float32x4x2_t val = vld2q_f32(input_ptr); + + // Map float values to range [0.0, 1.0] + val.val[0] = vsubq_f32(val.val[0], vmin); + val.val[1] = vsubq_f32(val.val[1], vmin); + val.val[0] = vmulq_f32(val.val[0], inv_range); + val.val[1] = vmulq_f32(val.val[1], inv_range); + + // Quantize + val.val[0] = vmulq_f32(val.val[0], quantization_mul); + val.val[1] = vmulq_f32(val.val[1], quantization_mul); + val.val[0] = vminq_f32(val.val[0], quantization_max); + val.val[1] = vminq_f32(val.val[1], quantization_max); + + const uint32x4_t val_u32_low = vcvtq_u32_f32(val.val[0]); + const uint32x4_t val_u32_high = vcvtq_u32_f32(val.val[1]); + const uint16x4x2_t val_u16 = vzip_u16(vmovn_u32(val_u32_low), vmovn_u32(val_u32_high)); + + const uint8x8_t quantized = vmovn_u16(vcombine_u16(val_u16.val[0], val_u16.val[1])); + + // Store the quantized values + auto output_ptr = reinterpret_cast(output.ptr() + id_batch[1] * _output->info()->strides_in_bytes()[3]); + vst1_u8(output_ptr, quantized); + }, + input, output); }, - input, output); + min_max); } -- cgit v1.2.1