| // 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 <stdbool.h> |
| #include <stddef.h> |
| #include <stdint.h> |
| #include <string.h> |
| #include <math.h> |
| |
| #include <xnnpack.h> |
| #include <xnnpack/allocator.h> |
| #include <xnnpack/log.h> |
| #include <xnnpack/math.h> |
| #include <xnnpack/operator.h> |
| #include <xnnpack/pack.h> |
| #include <xnnpack/params-init.h> |
| #include <xnnpack/params.h> |
| |
| |
| enum xnn_status xnn_create_fully_connected_nc_q8( |
| size_t input_channels, |
| size_t output_channels, |
| size_t input_stride, |
| size_t output_stride, |
| uint8_t input_zero_point, |
| float input_scale, |
| uint8_t kernel_zero_point, |
| float kernel_scale, |
| const uint8_t* kernel, |
| const int32_t* bias, |
| uint8_t output_zero_point, |
| float output_scale, |
| uint8_t output_min, |
| uint8_t output_max, |
| uint32_t flags, |
| xnn_operator_t* fully_connected_op_out) |
| { |
| xnn_operator_t fully_connected_op = NULL; |
| enum xnn_status status = xnn_status_uninitialized; |
| |
| if (!xnn_params.initialized) { |
| xnn_log_error("failed to create Fully Connected operator: XNNPACK is not initialized"); |
| goto error; |
| } |
| |
| status = xnn_status_invalid_parameter; |
| |
| if (input_channels == 0) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %zu input channels: number of channels must be non-zero", |
| input_channels); |
| goto error; |
| } |
| |
| if (output_channels == 0) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %zu output channels: number of channels must be non-zero", |
| output_channels); |
| goto error; |
| } |
| |
| if (input_stride < input_channels) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with input element stride of %zu: " |
| "stride must be at least as large as the number of input channels (%zu)", |
| input_stride, input_channels); |
| goto error; |
| } |
| |
| if (output_stride < output_channels) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with output element stride of %zu: " |
| "stride must be at least as large as the number of output channels (%zu)", |
| output_stride, output_channels); |
| goto error; |
| } |
| |
| if (input_scale <= 0.0f || !isnormal(input_scale)) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %.7g input scale: scale must be finite, normalized, and positive", |
| input_scale); |
| goto error; |
| } |
| |
| if (kernel_scale <= 0.0f || !isnormal(kernel_scale)) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %.7g kernel scale: scale must be finite, normalized, and positive", |
| kernel_scale); |
| goto error; |
| } |
| |
| if (output_scale <= 0.0f || !isnormal(output_scale)) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %.7g output scale: scale must be finite, normalized, and positive", |
| output_scale); |
| goto error; |
| } |
| |
| if (output_min >= output_max) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with [%" PRIu8 ", %" PRIu8 "] output range: " |
| "range min must be below range max", |
| output_min, output_max); |
| goto error; |
| } |
| |
| status = xnn_status_unsupported_parameter; |
| |
| const float requantization_scale = input_scale * kernel_scale / output_scale; |
| if (requantization_scale >= 1.0f) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %.7g input scale, %.7g kernel scale, and %.7g output scale: " |
| "requantization scale %.7g is greater or equal to 1.0", |
| input_scale, kernel_scale, output_scale, requantization_scale); |
| goto error; |
| } |
| |
| status = xnn_status_out_of_memory; |
| |
| fully_connected_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
| if (fully_connected_op == NULL) { |
| xnn_log_error("failed to allocate %zu bytes for Fully Connected operator descriptor", sizeof(struct xnn_operator)); |
| goto error; |
| } |
| |
| const uint32_t nr = xnn_params.q8.gemm.nr; |
| const uint32_t kr = UINT32_C(1) << xnn_params.q8.gemm.log2_kr; |
| |
| const uint32_t n_stride = round_up(output_channels, nr); |
| const uint32_t k_stride = round_up_po2(input_channels, kr); |
| |
| fully_connected_op->packed_weights = xnn_allocate_simd_memory(n_stride * (k_stride * sizeof(uint8_t) + sizeof(int32_t))); |
| if (fully_connected_op->packed_weights == NULL) { |
| xnn_log_error("failed to allocate %zu bytes for packed weights", |
| n_stride * (k_stride * sizeof(uint8_t) + sizeof(int32_t))); |
| goto error; |
| } |
| memset(fully_connected_op->packed_weights, kernel_zero_point, n_stride * (k_stride * sizeof(uint8_t) + sizeof(int32_t))); |
| |
| if (flags & XNN_FLAG_TRANSPOSE_WEIGHTS) { |
| xnn_pack_q8_gemm_io_w( |
| output_channels, input_channels, |
| nr, kr, |
| input_zero_point, kernel_zero_point, |
| kernel, bias, |
| fully_connected_op->packed_weights); |
| } else { |
| xnn_pack_q8_gemm_goi_w( |
| 1, output_channels, input_channels, |
| nr, kr, |
| input_zero_point, kernel_zero_point, |
| kernel, bias, |
| fully_connected_op->packed_weights); |
| } |
| |
| fully_connected_op->group_input_channels = input_channels; |
| fully_connected_op->group_output_channels = output_channels; |
| fully_connected_op->input_pixel_stride = input_stride; |
| fully_connected_op->output_pixel_stride = output_stride; |
| |
| fully_connected_op->kernel_zero_point = kernel_zero_point; |
| |
| fully_connected_op->q8_gemm_params = |
| xnn_init_q8_gemm_params( |
| input_zero_point, kernel_zero_point, |
| requantization_scale, output_zero_point, output_min, output_max); |
| |
| fully_connected_op->type = xnn_operator_type_fully_connected_nc_q8; |
| |
| fully_connected_op->ukernel.type = xnn_ukernel_type_gemm; |
| fully_connected_op->ukernel.gemm = (struct xnn_ukernel_gemm) { |
| .default_function = xnn_params.q8.gemm.gemm, |
| .mr = xnn_params.q8.gemm.mr, |
| .nr = nr, |
| .kr = kr, |
| }; |
| |
| fully_connected_op->state = xnn_run_state_invalid; |
| |
| *fully_connected_op_out = fully_connected_op; |
| return xnn_status_success; |
| |
| error: |
| xnn_delete_operator(fully_connected_op); |
| return status; |
| } |
| |
| enum xnn_status xnn_create_fully_connected_nc_f32( |
| size_t input_channels, |
| size_t output_channels, |
| size_t input_stride, |
| size_t output_stride, |
| const float* kernel, |
| const float* bias, |
| float output_min, |
| float output_max, |
| uint32_t flags, |
| xnn_operator_t* fully_connected_op_out) |
| { |
| xnn_operator_t fully_connected_op = NULL; |
| enum xnn_status status = xnn_status_uninitialized; |
| |
| if (!xnn_params.initialized) { |
| xnn_log_error("failed to create Fully Connected operator: XNNPACK is not initialized"); |
| goto error; |
| } |
| |
| status = xnn_status_invalid_parameter; |
| |
| if (input_channels == 0) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %zu input channels: number of channels must be non-zero", |
| input_channels); |
| goto error; |
| } |
| |
| if (output_channels == 0) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with %zu output channels: number of channels must be non-zero", |
| output_channels); |
| goto error; |
| } |
| |
| if (input_stride < input_channels) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with input element stride of %zu: " |
| "stride must be at least as large as the number of input channels (%zu)", |
| input_stride, input_channels); |
| goto error; |
| } |
| |
| if (output_stride < output_channels) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with output element stride of %zu: " |
| "stride must be at least as large as the number of output channels (%zu)", |
| output_stride, output_channels); |
| goto error; |
| } |
| |
| if (isnan(output_min)) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with NaN output lower bound: lower bound must be non-NaN"); |
| goto error; |
| } |
| |
| if (isnan(output_max)) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with NaN output upper bound: upper bound must be non-NaN"); |
| goto error; |
| } |
| |
| if (output_min >= output_max) { |
| xnn_log_error( |
| "failed to create Fully Connected operator with [%.7g, %.7g] output range: lower bound must be below upper bound", |
| output_min, output_max); |
| goto error; |
| } |
| |
| status = xnn_status_out_of_memory; |
| |
| fully_connected_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
| if (fully_connected_op == NULL) { |
| xnn_log_error("failed to allocate %zu bytes for Fully Connected operator descriptor", sizeof(struct xnn_operator)); |
| goto error; |
| } |
| |
| const uint32_t nr = xnn_params.f32.gemm.nr; |
| const uint32_t kr = UINT32_C(1) << xnn_params.f32.gemm.log2_kr; |
| const uint32_t sr = UINT32_C(1) << xnn_params.f32.gemm.log2_sr; |
| |
| const uint32_t n_stride = round_up(output_channels, nr); |
| const uint32_t k_stride = round_up_po2(input_channels, kr); |
| |
| fully_connected_op->packed_weights = xnn_allocate_simd_memory(n_stride * (k_stride * sizeof(float) + sizeof(float))); |
| if (fully_connected_op->packed_weights == NULL) { |
| xnn_log_error("failed to allocate %zu bytes for packed weights", |
| n_stride * (k_stride * sizeof(float) + sizeof(float))); |
| goto error; |
| } |
| memset(fully_connected_op->packed_weights, 0, n_stride * (k_stride * sizeof(float) + sizeof(float))); |
| |
| if (flags & XNN_FLAG_TRANSPOSE_WEIGHTS) { |
| xnn_pack_f32_gemm_io_w( |
| output_channels, input_channels, |
| nr, kr, sr, |
| kernel, bias, |
| fully_connected_op->packed_weights); |
| } else { |
| xnn_pack_f32_gemm_goi_w( |
| 1, output_channels, input_channels, |
| nr, kr, sr, |
| kernel, bias, |
| fully_connected_op->packed_weights); |
| } |
| |
| fully_connected_op->group_input_channels = input_channels; |
| fully_connected_op->group_output_channels = output_channels; |
| fully_connected_op->input_pixel_stride = input_stride; |
| fully_connected_op->output_pixel_stride = output_stride; |
| |
| fully_connected_op->f32_output_params = xnn_init_f32_output_params(output_min, output_max); |
| |
| fully_connected_op->type = xnn_operator_type_fully_connected_nc_f32; |
| |
| fully_connected_op->ukernel.type = xnn_ukernel_type_gemm; |
| fully_connected_op->ukernel.gemm = (struct xnn_ukernel_gemm) { |
| .default_function = xnn_params.f32.gemm.gemm, |
| .mr1_function = xnn_params.f32.gemm.gemm1, |
| .mr = xnn_params.f32.gemm.mr, |
| .nr = nr, |
| .kr = kr, |
| }; |
| |
| fully_connected_op->state = xnn_run_state_invalid; |
| |
| *fully_connected_op_out = fully_connected_op; |
| return xnn_status_success; |
| |
| error: |
| xnn_delete_operator(fully_connected_op); |
| return status; |
| } |
| |
| static enum xnn_status setup_fully_connected_nc( |
| xnn_operator_t fully_connected_op, |
| size_t batch_size, |
| const void* input, |
| void* output, |
| uint32_t log2_input_element_size, |
| uint32_t log2_filter_element_size, |
| uint32_t bias_element_size, |
| uint32_t log2_output_element_size, |
| const void* params, |
| size_t num_threads) |
| { |
| fully_connected_op->state = xnn_run_state_invalid; |
| |
| if (!xnn_params.initialized) { |
| xnn_log_error("failed to setup Fully Connected operator: XNNPACK is not initialized"); |
| return xnn_status_uninitialized; |
| } |
| |
| if (batch_size == 0) { |
| fully_connected_op->state = xnn_run_state_skip; |
| return xnn_status_success; |
| } |
| |
| fully_connected_op->batch_size = 1; |
| fully_connected_op->input_height = batch_size; |
| fully_connected_op->input_width = 1; |
| fully_connected_op->input = input; |
| |
| fully_connected_op->output_height = batch_size; |
| fully_connected_op->output_width = 1; |
| fully_connected_op->output = output; |
| |
| const size_t input_channels = fully_connected_op->group_input_channels; |
| const size_t output_channels = fully_connected_op->group_output_channels; |
| |
| uint32_t mr = fully_connected_op->ukernel.gemm.mr; |
| const uint32_t nr = fully_connected_op->ukernel.gemm.nr; |
| |
| xnn_gemm_ukernel_function gemm_ukernel = fully_connected_op->ukernel.gemm.default_function; |
| if (batch_size == 1 && fully_connected_op->ukernel.gemm.mr1_function != NULL) { |
| gemm_ukernel = fully_connected_op->ukernel.gemm.mr1_function; |
| mr = 1; |
| } |
| |
| fully_connected_op->context.gemm = (struct gemm_context) { |
| .k_scaled = input_channels << log2_input_element_size, |
| .w_stride = (round_up_po2(input_channels, fully_connected_op->ukernel.gemm.kr) << log2_input_element_size) + bias_element_size, |
| .a = input, |
| .a_stride = fully_connected_op->input_pixel_stride << log2_input_element_size, |
| .packed_w = fully_connected_op->packed_weights, |
| .c = output, |
| .cm_stride = fully_connected_op->output_pixel_stride << log2_output_element_size, |
| .cn_stride = nr << log2_output_element_size, |
| .log2_csize = log2_output_element_size, |
| .ukernel = gemm_ukernel, |
| }; |
| memcpy(&fully_connected_op->context.gemm.params, params, sizeof(fully_connected_op->context.gemm.params)); |
| |
| size_t nc = output_channels; |
| if (num_threads > 1) { |
| const size_t num_other_tiles = divide_round_up(batch_size, mr); |
| const size_t target_tiles_per_thread = 5; |
| const size_t max_nc = divide_round_up(output_channels * num_other_tiles, num_threads * target_tiles_per_thread); |
| if (max_nc < nc) { |
| nc = min(nc, divide_round_up(nc, max_nc * nr) * nr); |
| } |
| } |
| fully_connected_op->compute.type = xnn_parallelization_type_2d_tile_2d; |
| fully_connected_op->compute.task_2d_tile_2d = (pthreadpool_task_2d_tile_2d_t) xnn_compute_gemm; |
| fully_connected_op->compute.range[0] = batch_size; |
| fully_connected_op->compute.range[1] = output_channels; |
| fully_connected_op->compute.tile[0] = mr; |
| fully_connected_op->compute.tile[1] = nc; |
| fully_connected_op->state = xnn_run_state_ready; |
| |
| return xnn_status_success; |
| } |
| |
| enum xnn_status xnn_setup_fully_connected_nc_q8( |
| xnn_operator_t fully_connected_op, |
| size_t batch_size, |
| const uint8_t* input, |
| uint8_t* output, |
| pthreadpool_t threadpool) |
| { |
| if (fully_connected_op->type != xnn_operator_type_fully_connected_nc_q8) { |
| xnn_log_error("failed to setup Fully Connected (NC, Q8) operator: operator type mismatch"); |
| return xnn_status_invalid_parameter; |
| } |
| |
| return setup_fully_connected_nc( |
| fully_connected_op, |
| batch_size, |
| input, output, |
| 0 /* log2(sizeof(input element)) = log2(sizeof(uint8_t)) */, |
| 0 /* log2(sizeof(filter element)) = log2(sizeof(uint8_t)) */, |
| sizeof(int32_t) /* sizeof(bias element) */, |
| 0 /* log2(sizeof(output element)) = log2(sizeof(uint8_t)) */, |
| &fully_connected_op->q8_gemm_params, |
| pthreadpool_get_threads_count(threadpool)); |
| } |
| |
| enum xnn_status xnn_setup_fully_connected_nc_f32( |
| xnn_operator_t fully_connected_op, |
| size_t batch_size, |
| const float* input, |
| float* output, |
| pthreadpool_t threadpool) |
| { |
| if (fully_connected_op->type != xnn_operator_type_fully_connected_nc_f32) { |
| xnn_log_error("failed to setup Fully Connected (NC, F32) operator: operator type mismatch"); |
| return xnn_status_invalid_parameter; |
| } |
| |
| return setup_fully_connected_nc( |
| fully_connected_op, |
| batch_size, |
| input, output, |
| 2 /* log2(sizeof(input element)) = log2(sizeof(float)) */, |
| 2 /* log2(sizeof(filter element)) = log2(sizeof(float)) */, |
| sizeof(float) /* sizeof(bias element) */, |
| 2 /* log2(sizeof(output element)) = log2(sizeof(float)) */, |
| &fully_connected_op->f32_output_params, |
| pthreadpool_get_threads_count(threadpool)); |
| } |