XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 1 | // Copyright 2019 Google LLC |
| 2 | // |
| 3 | // This source code is licensed under the BSD-style license found in the |
| 4 | // LICENSE file in the root directory of this source tree. |
| 5 | |
| 6 | #include <math.h> |
| 7 | #include <stddef.h> |
| 8 | #include <stdint.h> |
| 9 | #include <stdlib.h> |
| 10 | |
| 11 | #include <xnnpack.h> |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 12 | #include <xnnpack/allocator.h> |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 13 | #include <xnnpack/log.h> |
Marat Dukhan | eeaa7bd | 2019-10-25 17:31:25 -0700 | [diff] [blame] | 14 | #include <xnnpack/operator.h> |
| 15 | #include <xnnpack/params-init.h> |
| 16 | #include <xnnpack/params.h> |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 17 | |
| 18 | |
| 19 | enum xnn_status xnn_create_hardswish_nc_f32( |
| 20 | size_t channels, |
| 21 | size_t input_stride, |
| 22 | size_t output_stride, |
| 23 | uint32_t flags, |
| 24 | xnn_operator_t* hardswish_op_out) |
| 25 | { |
| 26 | xnn_operator_t hardswish_op = NULL; |
| 27 | enum xnn_status status = xnn_status_uninitialized; |
| 28 | |
| 29 | if (!xnn_params.initialized) { |
| 30 | xnn_log_error("failed to create HardSwish operator: XNNPACK is not initialized"); |
| 31 | goto error; |
| 32 | } |
| 33 | |
| 34 | status = xnn_status_invalid_parameter; |
| 35 | |
| 36 | if (channels == 0) { |
| 37 | xnn_log_error( |
| 38 | "failed to create HardSwish operator with %zu channels: number of channels must be non-zero", channels); |
| 39 | goto error; |
| 40 | } |
| 41 | |
| 42 | if (input_stride < channels) { |
| 43 | xnn_log_error( |
| 44 | "failed to create HardSwish operator with input element stride of %zu: " |
| 45 | "stride must be at least as large as the number of channels (%zu)", |
| 46 | input_stride, channels); |
| 47 | goto error; |
| 48 | } |
| 49 | |
| 50 | if (output_stride < channels) { |
| 51 | xnn_log_error( |
| 52 | "failed to create HardSwish operator with output element stride of %zu: " |
| 53 | "stride must be at least as large as the number of channels (%zu)", |
| 54 | output_stride, channels); |
| 55 | goto error; |
| 56 | } |
| 57 | |
| 58 | status = xnn_status_out_of_memory; |
| 59 | |
Marat Dukhan | 04f03be | 2019-11-19 12:36:47 -0800 | [diff] [blame] | 60 | hardswish_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 61 | if (hardswish_op == NULL) { |
| 62 | xnn_log_error("failed to allocate %zu bytes for xnn_operator structure", sizeof(struct xnn_operator)); |
| 63 | goto error; |
| 64 | } |
| 65 | |
| 66 | hardswish_op->channels = channels; |
| 67 | hardswish_op->input_pixel_stride = input_stride; |
| 68 | hardswish_op->output_pixel_stride = output_stride; |
Marat Dukhan | eeaa7bd | 2019-10-25 17:31:25 -0700 | [diff] [blame] | 69 | hardswish_op->f32_hswish_params = xnn_init_f32_hswish_params(); |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 70 | |
Marat Dukhan | efc47b8 | 2019-11-18 09:25:38 -0800 | [diff] [blame] | 71 | hardswish_op->type = xnn_operator_type_hardswish_nc_f32; |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 72 | hardswish_op->ukernel.type = xnn_ukernel_type_hswish; |
| 73 | |
| 74 | hardswish_op->state = xnn_run_state_invalid; |
| 75 | |
| 76 | *hardswish_op_out = hardswish_op; |
| 77 | return xnn_status_success; |
| 78 | |
| 79 | error: |
| 80 | xnn_delete_operator(hardswish_op); |
| 81 | return status; |
| 82 | } |
| 83 | |
| 84 | enum xnn_status xnn_setup_hardswish_nc_f32( |
| 85 | xnn_operator_t hardswish_op, |
| 86 | size_t batch_size, |
| 87 | const float* input, |
| 88 | float* output, |
| 89 | pthreadpool_t threadpool) |
| 90 | { |
Marat Dukhan | efc47b8 | 2019-11-18 09:25:38 -0800 | [diff] [blame] | 91 | if (hardswish_op->type != xnn_operator_type_hardswish_nc_f32) { |
XNNPACK Team | b455b12 | 2019-09-27 18:10:33 -0700 | [diff] [blame] | 92 | xnn_log_error("failed to setup HardSwish (F32) operator: operator type mismatch"); |
| 93 | return xnn_status_invalid_parameter; |
| 94 | } |
| 95 | hardswish_op->state = xnn_run_state_invalid; |
| 96 | |
| 97 | if (!xnn_params.initialized) { |
| 98 | xnn_log_error("failed to setup HardSwish operator: XNNPACK is not initialized"); |
| 99 | return xnn_status_uninitialized; |
| 100 | } |
| 101 | |
| 102 | if (batch_size == 0) { |
| 103 | hardswish_op->state = xnn_run_state_skip; |
| 104 | return xnn_status_success; |
| 105 | } |
| 106 | |
| 107 | const size_t channels = hardswish_op->channels; |
| 108 | const size_t input_stride = hardswish_op->input_pixel_stride; |
| 109 | const size_t output_stride = hardswish_op->output_pixel_stride; |
| 110 | if ((((input_stride ^ channels) | (output_stride ^ channels)) == 0) || batch_size == 1) { |
| 111 | const size_t block_size = 4096; |
| 112 | hardswish_op->context.univector_contiguous = (struct univector_contiguous_context) { |
| 113 | .x = input, |
| 114 | .x_stride = input_stride * sizeof(float), |
| 115 | .y = output, |
| 116 | .y_stride = output_stride * sizeof(float), |
| 117 | .ukernel = xnn_params.f32.hswish, |
| 118 | .params.f32_hswish = hardswish_op->f32_hswish_params, |
| 119 | }; |
| 120 | hardswish_op->compute.type = xnn_parallelization_type_1d_tile_1d; |
| 121 | hardswish_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_univector_contiguous; |
| 122 | hardswish_op->compute.range[0] = batch_size * channels * sizeof(float); |
| 123 | hardswish_op->compute.tile[0] = block_size; |
| 124 | } else { |
| 125 | hardswish_op->context.univector_strided = (struct univector_strided_context) { |
| 126 | .n = channels * sizeof(float), |
| 127 | .x = input, |
| 128 | .x_stride = input_stride * sizeof(float), |
| 129 | .y = output, |
| 130 | .y_stride = output_stride * sizeof(float), |
| 131 | .ukernel = xnn_params.f32.hswish, |
| 132 | .params.f32_hswish = hardswish_op->f32_hswish_params, |
| 133 | }; |
| 134 | hardswish_op->compute.type = xnn_parallelization_type_1d_tile_1d; |
| 135 | hardswish_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_univector_strided; |
| 136 | hardswish_op->compute.range[0] = batch_size; |
| 137 | hardswish_op->compute.tile[0] = 1; |
| 138 | } |
| 139 | hardswish_op->state = xnn_run_state_ready; |
| 140 | |
| 141 | return xnn_status_success; |
| 142 | } |