| // Copyright (c) Facebook, Inc. and its affiliates. |
| // All rights reserved. |
| // |
| // Copyright 2019 Google LLC |
| // |
| // This source code is licensed under the BSD-style license found in the |
| // LICENSE file in the root directory of this source tree. |
| |
| #include <assert.h> |
| #include <math.h> |
| #include <stdbool.h> |
| #include <stddef.h> |
| #include <stdint.h> |
| #include <stdlib.h> |
| #include <string.h> |
| |
| #include <xnnpack.h> |
| #include <xnnpack/allocator.h> |
| #include <xnnpack/common.h> |
| #include <xnnpack/indirection.h> |
| #include <xnnpack/log.h> |
| #include <xnnpack/math.h> |
| #include <xnnpack/operator.h> |
| #include <xnnpack/params-init.h> |
| #include <xnnpack/params.h> |
| |
| |
| static inline size_t compute_output_dimension( |
| size_t padded_input_dimension, |
| size_t kernel_dimension, |
| size_t dilation_dimension, |
| size_t stride_dimension) |
| { |
| const size_t effective_kernel_dimension = (kernel_dimension - 1) * dilation_dimension + 1; |
| return (padded_input_dimension - effective_kernel_dimension) / stride_dimension + 1; |
| } |
| |
| static inline size_t compute_output_dimension_with_tf_same_padding( |
| size_t input_dimension, |
| size_t stride_dimension) |
| { |
| return divide_round_up(input_dimension, stride_dimension); |
| } |
| |
| enum xnn_status xnn_create_max_pooling2d_nhwc_u8( |
| uint32_t input_padding_top, |
| uint32_t input_padding_right, |
| uint32_t input_padding_bottom, |
| uint32_t input_padding_left, |
| uint32_t pooling_height, |
| uint32_t pooling_width, |
| uint32_t stride_height, |
| uint32_t stride_width, |
| uint32_t dilation_height, |
| uint32_t dilation_width, |
| size_t channels, |
| size_t input_pixel_stride, |
| size_t output_pixel_stride, |
| uint8_t output_min, |
| uint8_t output_max, |
| uint32_t flags, |
| xnn_operator_t* max_pooling_op_out) |
| { |
| xnn_operator_t max_pooling_op = NULL; |
| enum xnn_status status = xnn_status_uninitialized; |
| |
| if (!xnn_params.initialized) { |
| xnn_log_error("failed to create %s operator: XNNPACK is not initialized", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8)); |
| goto error; |
| } |
| |
| status = xnn_status_invalid_parameter; |
| |
| const uint32_t pooling_size = pooling_height * pooling_width; |
| if (pooling_size == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "x%" PRIu32 " pooling size: " |
| "pooling size dimensions must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), pooling_width, pooling_height); |
| goto error; |
| } |
| |
| if (pooling_size == 1) { |
| xnn_log_error( |
| "failed to create %s operator with 1 pooling element: 1x1 pooling is meaningless", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8)); |
| goto error; |
| } |
| |
| if (stride_height == 0 || stride_width == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "x%" PRIu32 " stride: stride dimensions must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), stride_width, stride_height); |
| goto error; |
| } |
| |
| if (dilation_height == 0 || dilation_width == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "x%" PRIu32 " dilation: dilation dimensions must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), dilation_width, dilation_height); |
| goto error; |
| } |
| |
| if (channels == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %zu channels: number of channels must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), channels); |
| goto error; |
| } |
| |
| if (input_pixel_stride < channels) { |
| xnn_log_error( |
| "failed to create %s operator with input pixel stride of %zu: " |
| "stride must be at least as large as the number of channels (%zu)", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), input_pixel_stride, channels); |
| goto error; |
| } |
| |
| if (output_pixel_stride < channels) { |
| xnn_log_error( |
| "failed to create %s operator with output pixel stride of %zu: " |
| "stride must be at least as large as the number of channels (%zu)", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), output_pixel_stride, channels); |
| goto error; |
| } |
| |
| if (output_min >= output_max) { |
| xnn_log_error( |
| "failed to create %s operator with [%" PRIu8 ", %" PRIu8 "] output range: range min must be below range max", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), output_min, output_max); |
| goto error; |
| } |
| |
| const bool any_padding = (input_padding_left | input_padding_top | input_padding_right | input_padding_bottom) != 0; |
| if ((flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) != 0) { |
| if (any_padding) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "+%" PRIu32 "x%" PRIu32 "+%" PRIu32" padding: " |
| "TensorFlow SAME padding can't be combined with explicit padding specification", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), |
| input_padding_top, input_padding_left, input_padding_bottom, input_padding_right); |
| goto error; |
| } |
| } |
| |
| status = xnn_status_out_of_memory; |
| |
| max_pooling_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
| if (max_pooling_op == NULL) { |
| xnn_log_error( |
| "failed to allocate %zu bytes for %s operator descriptor", |
| sizeof(struct xnn_operator), xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8)); |
| goto error; |
| } |
| |
| max_pooling_op->padding_top = input_padding_top; |
| max_pooling_op->padding_right = input_padding_right; |
| max_pooling_op->padding_bottom = input_padding_bottom; |
| max_pooling_op->padding_left = input_padding_left; |
| |
| max_pooling_op->kernel_height = pooling_height; |
| max_pooling_op->kernel_width = pooling_width; |
| max_pooling_op->stride_height = stride_height; |
| max_pooling_op->stride_width = stride_width; |
| max_pooling_op->dilation_height = dilation_height; |
| max_pooling_op->dilation_width = dilation_width; |
| max_pooling_op->channels = channels; |
| max_pooling_op->input_pixel_stride = input_pixel_stride; |
| max_pooling_op->output_pixel_stride = output_pixel_stride; |
| |
| max_pooling_op->params.u8_minmax = xnn_init_u8_minmax_params(output_min, output_max); |
| |
| max_pooling_op->type = xnn_operator_type_max_pooling_nhwc_u8; |
| max_pooling_op->ukernel.type = xnn_ukernel_type_max_pooling; |
| max_pooling_op->flags = flags; |
| |
| max_pooling_op->state = xnn_run_state_invalid; |
| |
| *max_pooling_op_out = max_pooling_op; |
| return xnn_status_success; |
| |
| error: |
| xnn_delete_operator(max_pooling_op); |
| return status; |
| } |
| |
| enum xnn_status xnn_create_max_pooling2d_nhwc_f32( |
| uint32_t input_padding_top, |
| uint32_t input_padding_right, |
| uint32_t input_padding_bottom, |
| uint32_t input_padding_left, |
| uint32_t pooling_height, |
| uint32_t pooling_width, |
| uint32_t stride_height, |
| uint32_t stride_width, |
| uint32_t dilation_height, |
| uint32_t dilation_width, |
| size_t channels, |
| size_t input_pixel_stride, |
| size_t output_pixel_stride, |
| float output_min, |
| float output_max, |
| uint32_t flags, |
| xnn_operator_t* max_pooling_op_out) |
| { |
| xnn_operator_t max_pooling_op = NULL; |
| enum xnn_status status = xnn_status_uninitialized; |
| |
| if (!xnn_params.initialized) { |
| xnn_log_error("failed to setup %s operator: XNNPACK is not initialized", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32)); |
| return xnn_status_uninitialized; |
| } |
| |
| status = xnn_status_invalid_parameter; |
| |
| const uint32_t pooling_size = pooling_height * pooling_width; |
| if (pooling_size == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "x%" PRIu32 " pooling size: " |
| "pooling size dimensions must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), |
| pooling_width, pooling_height); |
| goto error; |
| } |
| |
| if (pooling_size == 1) { |
| xnn_log_error( |
| "failed to create %s operator with 1 pooling element: 1x1 pooling is meaningless", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32)); |
| goto error; |
| } |
| |
| if (stride_height == 0 || stride_width == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "x%" PRIu32 " stride: stride dimensions must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), stride_width, stride_height); |
| goto error; |
| } |
| |
| if (dilation_height == 0 || dilation_width == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "x%" PRIu32 " dilation: dilation dimensions must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), dilation_width, dilation_height); |
| goto error; |
| } |
| |
| if (channels == 0) { |
| xnn_log_error( |
| "failed to create %s operator with %zu channels: number of channels must be non-zero", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), channels); |
| goto error; |
| } |
| |
| if (input_pixel_stride < channels) { |
| xnn_log_error( |
| "failed to create %s operator with input pixel stride of %zu: " |
| "stride must be at least as large as the number of channels (%zu)", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), input_pixel_stride, channels); |
| goto error; |
| } |
| |
| if (output_pixel_stride < channels) { |
| xnn_log_error( |
| "failed to create %s operator with output pixel stride of %zu: " |
| "stride must be at least as large as the number of channels (%zu)", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), output_pixel_stride, channels); |
| goto error; |
| } |
| |
| if (isnan(output_min)) { |
| xnn_log_error( |
| "failed to create %s with NaN output lower bound: lower bound must be non-NaN", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32)); |
| goto error; |
| } |
| |
| if (isnan(output_max)) { |
| xnn_log_error( |
| "failed to create %s with NaN output upper bound: upper bound must be non-NaN", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32)); |
| goto error; |
| } |
| |
| if (output_min >= output_max) { |
| xnn_log_error( |
| "failed to create %s with [%.7g, %.7g] output range: lower bound must be below upper bound", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), output_min, output_max); |
| goto error; |
| } |
| |
| const bool any_padding = (input_padding_left | input_padding_top | input_padding_right | input_padding_bottom) != 0; |
| if ((flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) != 0) { |
| if (any_padding) { |
| xnn_log_error( |
| "failed to create %s operator with %" PRIu32 "+%" PRIu32 "x%" PRIu32 "+%" PRIu32" padding: " |
| "TensorFlow SAME padding can't be combined with explicit padding specification", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), |
| input_padding_top, input_padding_left, input_padding_bottom, input_padding_right); |
| goto error; |
| } |
| } |
| |
| status = xnn_status_out_of_memory; |
| |
| max_pooling_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
| if (max_pooling_op == NULL) { |
| xnn_log_error( |
| "failed to allocate %zu bytes for %s operator descriptor", |
| sizeof(struct xnn_operator), xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32)); |
| goto error; |
| } |
| |
| max_pooling_op->padding_top = input_padding_top; |
| max_pooling_op->padding_right = input_padding_right; |
| max_pooling_op->padding_bottom = input_padding_bottom; |
| max_pooling_op->padding_left = input_padding_left; |
| |
| max_pooling_op->kernel_height = pooling_height; |
| max_pooling_op->kernel_width = pooling_width; |
| max_pooling_op->stride_height = stride_height; |
| max_pooling_op->stride_width = stride_width; |
| max_pooling_op->dilation_height = dilation_height; |
| max_pooling_op->dilation_width = dilation_width; |
| max_pooling_op->channels = channels; |
| max_pooling_op->input_pixel_stride = input_pixel_stride; |
| max_pooling_op->output_pixel_stride = output_pixel_stride; |
| |
| max_pooling_op->params.f32_minmax = xnn_init_f32_minmax_params(output_min, output_max); |
| |
| max_pooling_op->type = xnn_operator_type_max_pooling_nhwc_f32; |
| max_pooling_op->ukernel.type = xnn_ukernel_type_max_pooling; |
| max_pooling_op->flags = flags; |
| |
| max_pooling_op->state = xnn_run_state_invalid; |
| |
| *max_pooling_op_out = max_pooling_op; |
| return xnn_status_success; |
| |
| error: |
| xnn_delete_operator(max_pooling_op); |
| return status; |
| } |
| |
| static enum xnn_status setup_max_pooling2d( |
| xnn_operator_t max_pooling_op, |
| size_t batch_size, |
| size_t input_height, |
| size_t input_width, |
| const void* input, |
| void* output, |
| uint32_t log2_input_element_size, |
| uint32_t log2_output_element_size, |
| struct maxpool_parameters maxpool[restrict XNN_MIN_ELEMENTS(1)], |
| const void* params, |
| size_t num_threads) |
| { |
| max_pooling_op->state = xnn_run_state_invalid; |
| |
| if (!xnn_params.initialized) { |
| xnn_log_error( |
| "failed to setup %s operator: XNNPACK is not initialized", |
| xnn_operator_type_to_string(max_pooling_op->type)); |
| return xnn_status_uninitialized; |
| } |
| |
| if (input_width == 0 || input_height == 0) { |
| xnn_log_error( |
| "failed to setup %s operator with %zux%zu input: input dimensions must be non-zero", |
| xnn_operator_type_to_string(max_pooling_op->type), input_width, input_height); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (batch_size == 0) { |
| max_pooling_op->state = xnn_run_state_skip; |
| return xnn_status_success; |
| } |
| |
| max_pooling_op->input_height = input_height; |
| max_pooling_op->input_width = input_width; |
| max_pooling_op->input = input; |
| |
| if (max_pooling_op->flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) { |
| max_pooling_op->output_height = compute_output_dimension_with_tf_same_padding( |
| input_height, max_pooling_op->stride_height); |
| max_pooling_op->output_width = compute_output_dimension_with_tf_same_padding( |
| input_width, max_pooling_op->stride_width); |
| |
| const uint32_t effective_kernel_height = (max_pooling_op->kernel_height - 1) * max_pooling_op->dilation_height + 1; |
| const uint32_t effective_kernel_width = (max_pooling_op->kernel_width - 1) * max_pooling_op->dilation_width + 1; |
| const uint32_t total_padding_height = |
| doz((max_pooling_op->output_height - 1) * max_pooling_op->stride_height + effective_kernel_height, input_height); |
| const uint32_t total_padding_width = |
| doz((max_pooling_op->output_width - 1) * max_pooling_op->stride_width + effective_kernel_width, input_width); |
| max_pooling_op->padding_top = total_padding_height / 2; |
| max_pooling_op->padding_left = total_padding_width / 2; |
| max_pooling_op->padding_bottom = total_padding_height - max_pooling_op->padding_top; |
| max_pooling_op->padding_right = total_padding_width - max_pooling_op->padding_left; |
| } else { |
| max_pooling_op->output_height = compute_output_dimension( |
| max_pooling_op->padding_top + input_height + max_pooling_op->padding_bottom, |
| max_pooling_op->kernel_height, |
| max_pooling_op->dilation_height, |
| max_pooling_op->stride_height); |
| max_pooling_op->output_width = compute_output_dimension( |
| max_pooling_op->padding_left + input_width + max_pooling_op->padding_right, |
| max_pooling_op->kernel_width, |
| max_pooling_op->dilation_width, |
| max_pooling_op->stride_width); |
| } |
| |
| const size_t pooling_height = max_pooling_op->kernel_height; |
| const size_t pooling_width = max_pooling_op->kernel_width; |
| const size_t pooling_size = pooling_height * pooling_width; |
| const size_t output_height = max_pooling_op->output_height; |
| const size_t output_width = max_pooling_op->output_width; |
| const uint32_t mr = maxpool->mr; |
| |
| const size_t step_width = |
| max_pooling_op->dilation_width > 1 ? pooling_width : min(max_pooling_op->stride_width, pooling_width); |
| const size_t step_height = pooling_size + (output_width - 1) * step_width * pooling_height; |
| |
| if (input_height != max_pooling_op->last_input_height || |
| input_width != max_pooling_op->last_input_width) |
| { |
| // Micro-kernel may read up to (mr - 1) elements after the end of indirection buffer. |
| const size_t indirection_buffer_size = sizeof(void*) * ((mr - 1) + output_height * step_height); |
| const void** indirection_buffer = |
| (const void**) xnn_reallocate_memory(max_pooling_op->indirection_buffer, indirection_buffer_size); |
| if (indirection_buffer == NULL) { |
| xnn_log_error("failed to allocate %zu bytes for indirection buffer", indirection_buffer_size); |
| return xnn_status_out_of_memory; |
| } |
| max_pooling_op->indirection_buffer = indirection_buffer; |
| |
| xnn_indirection_init_maxpool2d(max_pooling_op, step_height, step_width, log2_input_element_size); |
| |
| max_pooling_op->last_input = input; |
| max_pooling_op->last_input_height = input_height; |
| max_pooling_op->last_input_width = input_width; |
| } |
| |
| const uint32_t qr = maxpool->qr; |
| const size_t channels = max_pooling_op->channels; |
| |
| const size_t indirect_input_height_stride = step_height * sizeof(void*); |
| const size_t output_width_stride = max_pooling_op->output_pixel_stride << log2_output_element_size; |
| const size_t output_height_stride = output_width * output_width_stride; |
| const size_t multipass_adjustment = round_up(doz(pooling_size, mr), qr) + mr; |
| |
| max_pooling_op->context.max_pooling = (struct max_pooling_context) { |
| .indirect_input = max_pooling_op->indirection_buffer, |
| .indirect_input_height_stride = indirect_input_height_stride, |
| .input_offset = (size_t) ((uintptr_t) input - (uintptr_t) max_pooling_op->last_input), |
| .input_batch_stride = (input_height * input_width * max_pooling_op->input_pixel_stride) << log2_input_element_size, |
| .output = output, |
| .output_batch_stride = output_height * output_height_stride, |
| .output_height_stride = output_height_stride, |
| .output_width = output_width, |
| .pooling_size = pooling_size, |
| .channels = channels, |
| .input_increment = (pooling_height * step_width - multipass_adjustment) * sizeof(void*), |
| .output_increment = output_width_stride - (channels << log2_output_element_size), |
| .ukernel = maxpool->ukernel, |
| }; |
| memcpy(&max_pooling_op->context.max_pooling.params, params, sizeof(max_pooling_op->context.max_pooling.params)); |
| |
| max_pooling_op->compute.type = xnn_parallelization_type_2d; |
| max_pooling_op->compute.task_2d = (pthreadpool_task_2d_t) xnn_compute_max_pooling; |
| max_pooling_op->compute.range[0] = batch_size; |
| max_pooling_op->compute.range[1] = output_height; |
| max_pooling_op->state = xnn_run_state_ready; |
| |
| return xnn_status_success; |
| } |
| |
| enum xnn_status xnn_setup_max_pooling2d_nhwc_u8( |
| xnn_operator_t max_pooling_op, |
| size_t batch_size, |
| size_t input_height, |
| size_t input_width, |
| const uint8_t* input, |
| uint8_t* output, |
| pthreadpool_t threadpool) |
| { |
| if (max_pooling_op->type != xnn_operator_type_max_pooling_nhwc_u8) { |
| xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_u8), |
| xnn_operator_type_to_string(max_pooling_op->type)); |
| return xnn_status_invalid_parameter; |
| } |
| |
| return setup_max_pooling2d( |
| max_pooling_op, |
| batch_size, input_height, input_width, |
| input, output, |
| 0 /* log2(sizeof(input element)) = log2(sizeof(uint8_t)) */, |
| 0 /* log2(sizeof(output element)) = log2(sizeof(uint8_t)) */, |
| &xnn_params.u8.maxpool, |
| &max_pooling_op->params.u8_minmax, |
| pthreadpool_get_threads_count(threadpool)); |
| } |
| |
| enum xnn_status xnn_setup_max_pooling2d_nhwc_f32( |
| xnn_operator_t max_pooling_op, |
| size_t batch_size, |
| size_t input_height, |
| size_t input_width, |
| const float* input, |
| float* output, |
| pthreadpool_t threadpool) |
| { |
| if (max_pooling_op->type != xnn_operator_type_max_pooling_nhwc_f32) { |
| xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)", |
| xnn_operator_type_to_string(xnn_operator_type_max_pooling_nhwc_f32), |
| xnn_operator_type_to_string(max_pooling_op->type)); |
| return xnn_status_invalid_parameter; |
| } |
| |
| return setup_max_pooling2d( |
| max_pooling_op, |
| batch_size, input_height, input_width, |
| input, output, |
| 2 /* log2(sizeof(input element)) = log2(sizeof(float)) */, |
| 2 /* log2(sizeof(output element)) = log2(sizeof(float)) */, |
| &xnn_params.f32.maxpool, |
| &max_pooling_op->params.f32_minmax, |
| pthreadpool_get_threads_count(threadpool)); |
| } |
| |