| // Copyright 2020 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 <stddef.h> |
| #include <stdint.h> |
| |
| #include <xnnpack.h> |
| #include <xnnpack/log.h> |
| #include <xnnpack/operator.h> |
| #include <xnnpack/params.h> |
| #include <xnnpack/requantization.h> |
| #include <xnnpack/subgraph.h> |
| #include <xnnpack/subgraph-validation.h> |
| |
| |
| static enum xnn_status create_fully_connected_operator( |
| const struct xnn_node* node, |
| const struct xnn_value* values, |
| size_t num_values, |
| struct xnn_operator_data* opdata, |
| const struct xnn_caches* caches) |
| { |
| assert(node->num_inputs >= 2); |
| assert(node->num_inputs <= 3); |
| const uint32_t input_id = node->inputs[0]; |
| assert(input_id != XNN_INVALID_VALUE_ID); |
| assert(input_id < num_values); |
| const uint32_t filter_id = node->inputs[1]; |
| assert(filter_id != XNN_INVALID_VALUE_ID); |
| assert(filter_id < num_values); |
| |
| assert(node->num_outputs == 1); |
| const uint32_t output_id = node->outputs[0]; |
| assert(output_id != XNN_INVALID_VALUE_ID); |
| assert(output_id < num_values); |
| |
| const size_t num_input_elements = xnn_shape_multiply_all_dims(&values[node->inputs[0]].shape); |
| size_t output_channels, input_channels; |
| if (node->flags & XNN_FLAG_TRANSPOSE_WEIGHTS) { |
| input_channels = values[node->inputs[1]].shape.dim[0]; |
| output_channels = values[node->inputs[1]].shape.dim[1]; |
| } else { |
| output_channels = values[node->inputs[1]].shape.dim[0]; |
| input_channels = values[node->inputs[1]].shape.dim[1]; |
| } |
| |
| const void* filter_data = values[filter_id].data; |
| assert(filter_data != NULL); |
| |
| const void* bias_data = NULL; |
| if (node->num_inputs > 2) { |
| const uint32_t bias_id = node->inputs[2]; |
| assert(bias_id != XNN_INVALID_VALUE_ID); |
| assert(bias_id < num_values); |
| |
| bias_data = values[bias_id].data; |
| assert(bias_data != NULL); |
| } |
| |
| enum xnn_status status; |
| switch (node->compute_type) { |
| #ifndef XNN_NO_F16_OPERATORS |
| case xnn_compute_type_fp16: |
| status = xnn_create_fully_connected_nc_f16( |
| input_channels, |
| output_channels, |
| input_channels /* input stride */, |
| output_channels /* output stride */, |
| filter_data, |
| bias_data, |
| node->activation.output_min, |
| node->activation.output_max, |
| node->flags | XNN_FLAG_FP32_STATIC_WEIGHTS, |
| caches, |
| &opdata->operator_objects[0]); |
| break; |
| #endif // XNN_NO_F16_OPERATORS |
| case xnn_compute_type_fp32: |
| status = xnn_create_fully_connected_nc_f32( |
| input_channels, |
| output_channels, |
| input_channels /* input stride */, |
| output_channels /* output stride */, |
| filter_data, |
| bias_data, |
| node->activation.output_min, |
| node->activation.output_max, |
| node->flags /* flags */, |
| caches, |
| &opdata->operator_objects[0]); |
| break; |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_compute_type_qs8: |
| { |
| const float output_scale = values[output_id].quantization.scale; |
| const int32_t output_zero_point = values[output_id].quantization.zero_point; |
| const int8_t output_min = xnn_qs8_quantize(node->activation.output_min, output_scale, output_zero_point); |
| const int8_t output_max = xnn_qs8_quantize(node->activation.output_max, output_scale, output_zero_point); |
| status = xnn_create_fully_connected_nc_qs8( |
| input_channels, |
| output_channels, |
| input_channels /* input stride */, |
| output_channels /* output stride */, |
| (int8_t) values[input_id].quantization.zero_point, |
| values[input_id].quantization.scale, |
| values[filter_id].quantization.scale, |
| filter_data, |
| bias_data, |
| (int8_t) output_zero_point, |
| output_scale, output_min, output_max, |
| node->flags /* flags */, |
| caches, |
| &opdata->operator_objects[0]); |
| break; |
| } |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_compute_type_qu8: |
| { |
| const float output_scale = values[output_id].quantization.scale; |
| const int32_t output_zero_point = values[output_id].quantization.zero_point; |
| const uint8_t output_min = xnn_qu8_quantize(node->activation.output_min, output_scale, output_zero_point); |
| const uint8_t output_max = xnn_qu8_quantize(node->activation.output_max, output_scale, output_zero_point); |
| status = xnn_create_fully_connected_nc_qu8( |
| input_channels, |
| output_channels, |
| input_channels /* input stride */, |
| output_channels /* output stride */, |
| (uint8_t) values[input_id].quantization.zero_point, |
| values[input_id].quantization.scale, |
| (uint8_t) values[filter_id].quantization.zero_point, |
| values[filter_id].quantization.scale, |
| filter_data, |
| bias_data, |
| (uint8_t) output_zero_point, |
| output_scale, output_min, output_max, |
| node->flags /* flags */, |
| caches, |
| &opdata->operator_objects[0]); |
| break; |
| } |
| #endif // !defined(XNN_NO_QU8_OPERATORS) |
| default: |
| XNN_UNREACHABLE; |
| } |
| if (status == xnn_status_success) { |
| opdata->batch_size = num_input_elements / input_channels; |
| opdata->inputs[0] = input_id; |
| opdata->outputs[0] = output_id; |
| } |
| return status; |
| } |
| |
| static enum xnn_status setup_fully_connected_operator( |
| const struct xnn_operator_data* opdata, |
| const struct xnn_blob* blobs, |
| size_t num_blobs, |
| pthreadpool_t threadpool) |
| { |
| const uint32_t input_id = opdata->inputs[0]; |
| assert(input_id != XNN_INVALID_VALUE_ID); |
| assert(input_id < num_blobs); |
| |
| const uint32_t output_id = opdata->outputs[0]; |
| assert(output_id != XNN_INVALID_VALUE_ID); |
| assert(output_id < num_blobs); |
| |
| const struct xnn_blob* input_blob = blobs + input_id; |
| const void* input_data = input_blob->data; |
| assert(input_data != NULL); |
| |
| const struct xnn_blob* output_blob = blobs + output_id; |
| void* output_data = output_blob->data; |
| assert(output_data != NULL); |
| |
| switch (opdata->operator_objects[0]->type) { |
| #ifndef XNN_NO_F16_OPERATORS |
| case xnn_operator_type_fully_connected_nc_f16: |
| return xnn_setup_fully_connected_nc_f16( |
| opdata->operator_objects[0], |
| opdata->batch_size, |
| input_data, |
| output_data, |
| threadpool); |
| #endif // !defined(XNN_NO_F16_OPERATORS) |
| case xnn_operator_type_fully_connected_nc_f32: |
| return xnn_setup_fully_connected_nc_f32( |
| opdata->operator_objects[0], |
| opdata->batch_size, |
| input_data, |
| output_data, |
| threadpool); |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_operator_type_fully_connected_nc_qs8: |
| return xnn_setup_fully_connected_nc_qs8( |
| opdata->operator_objects[0], |
| opdata->batch_size, |
| input_data, |
| output_data, |
| threadpool); |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_operator_type_fully_connected_nc_qu8: |
| return xnn_setup_fully_connected_nc_qu8( |
| opdata->operator_objects[0], |
| opdata->batch_size, |
| input_data, |
| output_data, |
| threadpool); |
| #endif // !defined(XNN_NO_QU8_OPERATORS) |
| default: |
| XNN_UNREACHABLE; |
| } |
| } |
| |
| static inline enum xnn_compute_type validate_datatypes_with_bias( |
| enum xnn_datatype input_datatype, |
| enum xnn_datatype filter_datatype, |
| enum xnn_datatype bias_datatype, |
| enum xnn_datatype output_datatype) |
| { |
| switch (filter_datatype) { |
| case xnn_datatype_fp32: |
| if (input_datatype == xnn_datatype_fp32 && |
| bias_datatype == xnn_datatype_fp32 && |
| output_datatype == xnn_datatype_fp32) |
| { |
| return xnn_compute_type_fp32; |
| } |
| break; |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_datatype_qint8: |
| if (input_datatype == xnn_datatype_qint8 && |
| bias_datatype == xnn_datatype_qint32 && |
| output_datatype == xnn_datatype_qint8) |
| { |
| return xnn_compute_type_qs8; |
| } |
| break; |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_datatype_quint8: |
| if (input_datatype == xnn_datatype_quint8 && |
| bias_datatype == xnn_datatype_qint32 && |
| output_datatype == xnn_datatype_quint8) |
| { |
| return xnn_compute_type_qu8; |
| } |
| break; |
| #endif // !defined(XNN_NO_QU8_OPERATORS) |
| default: |
| XNN_UNREACHABLE; |
| } |
| return xnn_compute_type_invalid; |
| } |
| |
| static inline enum xnn_compute_type validate_datatypes_without_bias( |
| enum xnn_datatype input_datatype, |
| enum xnn_datatype filter_datatype, |
| enum xnn_datatype output_datatype) |
| { |
| switch (filter_datatype) { |
| case xnn_datatype_fp32: |
| if (input_datatype == xnn_datatype_fp32 && output_datatype == xnn_datatype_fp32) { |
| return xnn_compute_type_fp32; |
| } |
| break; |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_datatype_qint8: |
| if (input_datatype == xnn_datatype_qint8 && output_datatype == xnn_datatype_qint8) { |
| return xnn_compute_type_qs8; |
| } |
| break; |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_datatype_quint8: |
| if (input_datatype == xnn_datatype_quint8 && output_datatype == xnn_datatype_quint8) { |
| return xnn_compute_type_qu8; |
| } |
| break; |
| #endif // !defined(XNN_NO_QU8_OPERATORS) |
| default: |
| XNN_UNREACHABLE; |
| } |
| return xnn_compute_type_invalid; |
| } |
| |
| enum xnn_status xnn_define_fully_connected( |
| xnn_subgraph_t subgraph, |
| float output_min, |
| float output_max, |
| uint32_t input_id, |
| uint32_t filter_id, |
| uint32_t bias_id, |
| uint32_t output_id, |
| uint32_t flags) |
| { |
| enum xnn_status status; |
| if ((status = xnn_subgraph_check_xnnpack_initialized(xnn_node_type_fully_connected)) != xnn_status_success) { |
| return status; |
| } |
| |
| status = xnn_subgraph_check_output_min_max(xnn_node_type_fully_connected, output_min, output_max); |
| if (status != xnn_status_success) { |
| return status; |
| } |
| |
| if ((status = xnn_subgraph_check_input_node_id(xnn_node_type_fully_connected, input_id, subgraph->num_values)) != |
| xnn_status_success) { |
| return status; |
| } |
| |
| const struct xnn_value* input_value = &subgraph->values[input_id]; |
| status = xnn_subgraph_check_input_type_dense(xnn_node_type_fully_connected, input_id, input_value); |
| if (status != xnn_status_success) { |
| return status; |
| } |
| |
| switch (input_value->datatype) { |
| case xnn_datatype_fp32: |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_datatype_qint8: |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_datatype_quint8: |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| break; |
| default: |
| xnn_log_error( |
| "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value datatype %s (%d)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), input_id, |
| xnn_datatype_to_string(input_value->datatype), input_value->datatype); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (filter_id >= subgraph->num_values) { |
| xnn_log_error( |
| "failed to define %s operator with filter ID #%" PRIu32 ": invalid Value ID", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), filter_id); |
| return xnn_status_invalid_parameter; |
| } |
| |
| const struct xnn_value* filter_value = &subgraph->values[filter_id]; |
| if (filter_value->type != xnn_value_type_dense_tensor) { |
| xnn_log_error( |
| "failed to define %s operator with filter ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), filter_id, filter_value->type); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (filter_value->data == NULL) { |
| xnn_log_error( |
| "failed to define %s operator with filter ID #%" PRIu32 ": non-static Value", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), filter_id); |
| return xnn_status_invalid_parameter; |
| } |
| |
| switch (filter_value->datatype) { |
| case xnn_datatype_fp32: |
| break; |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_datatype_qint8: |
| if (filter_value->quantization.zero_point != 0) { |
| xnn_log_error( |
| "failed to define %s operator with filter ID #%" PRIu32 ": unsupported quantization zero point %" PRId32 " for datatype %s", |
| xnn_node_type_to_string(xnn_node_type_convolution_2d), filter_id, |
| filter_value->quantization.zero_point, xnn_datatype_to_string(filter_value->datatype)); |
| } |
| break; |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_datatype_quint8: |
| break; |
| #endif // !defined(XNN_NO_QU8_OPERATORS) |
| default: |
| xnn_log_error( |
| "failed to define %s operator with filter ID #%" PRIu32 ": unsupported Value datatype %s (%d)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), filter_id, |
| xnn_datatype_to_string(filter_value->datatype), filter_value->datatype); |
| return xnn_status_invalid_parameter; |
| } |
| |
| const struct xnn_value* bias_value = NULL; |
| if (bias_id != XNN_INVALID_VALUE_ID) { |
| if (bias_id >= subgraph->num_values) { |
| xnn_log_error( |
| "failed to define %s operator with bias ID #%" PRIu32 ": invalid Value ID", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), bias_id); |
| return xnn_status_invalid_parameter; |
| } |
| |
| bias_value = &subgraph->values[bias_id]; |
| if (bias_value->type != xnn_value_type_dense_tensor) { |
| xnn_log_error( |
| "failed to define %s operator with bias ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), bias_id, bias_value->type); |
| return xnn_status_invalid_parameter; |
| } |
| |
| if (bias_value->data == NULL) { |
| xnn_log_error( |
| "failed to define %s operator with bias ID #%" PRIu32 ": non-static Value", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), bias_id); |
| return xnn_status_invalid_parameter; |
| } |
| |
| switch (bias_value->datatype) { |
| case xnn_datatype_fp32: |
| #if !defined(XNN_NO_QS8_OPERATORS) || !defined(XNN_NO_QU8_OPERATORS) |
| case xnn_datatype_qint32: |
| #endif // !defined(XNN_NO_QS8_OPERATORS) || !defined(XNN_NO_QU8_OPERATORS) |
| break; |
| default: |
| xnn_log_error( |
| "failed to define %s operator with bias ID #%" PRIu32 ": unsupported Value datatype %s (%d)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), bias_id, |
| xnn_datatype_to_string(bias_value->datatype), bias_value->datatype); |
| return xnn_status_invalid_parameter; |
| } |
| } |
| |
| status = xnn_subgraph_check_output_node_id(xnn_node_type_fully_connected, output_id, subgraph->num_values); |
| if (status != xnn_status_success) { |
| return status; |
| } |
| |
| const struct xnn_value* output_value = &subgraph->values[output_id]; |
| status = xnn_subgraph_check_output_type_dense(xnn_node_type_fully_connected, output_id, output_value); |
| if (status != xnn_status_success) { |
| return status; |
| } |
| |
| switch (output_value->datatype) { |
| case xnn_datatype_fp32: |
| #ifndef XNN_NO_QS8_OPERATORS |
| case xnn_datatype_qint8: |
| #endif // !defined(XNN_NO_QS8_OPERATORS) |
| #ifndef XNN_NO_QU8_OPERATORS |
| case xnn_datatype_quint8: |
| #endif // !defined(XNN_NO_QU8_OPERATORS) |
| break; |
| default: |
| xnn_log_error( |
| "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value datatype %s (%d)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), output_id, |
| xnn_datatype_to_string(output_value->datatype), output_value->datatype); |
| return xnn_status_invalid_parameter; |
| } |
| |
| enum xnn_compute_type compute_type = xnn_compute_type_invalid; |
| if (bias_value != NULL) { |
| compute_type = validate_datatypes_with_bias( |
| input_value->datatype, filter_value->datatype, bias_value->datatype, output_value->datatype); |
| if (compute_type == xnn_compute_type_invalid) { |
| xnn_log_error( |
| "failed to define %s operator with input ID #%" PRIu32 ", filter ID #%" PRIu32 ", bias ID #%" PRIu32 ", and output ID #%" PRIu32 |
| ": mismatching datatypes across input (%s), filter (%s), bias (%s), and output (%s)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), input_id, filter_id, bias_id, output_id, |
| xnn_datatype_to_string(input_value->datatype), |
| xnn_datatype_to_string(filter_value->datatype), |
| xnn_datatype_to_string(bias_value->datatype), |
| xnn_datatype_to_string(output_value->datatype)); |
| return xnn_status_invalid_parameter; |
| } |
| } else { |
| compute_type = validate_datatypes_without_bias( |
| input_value->datatype, filter_value->datatype, output_value->datatype); |
| if (compute_type == xnn_compute_type_invalid) { |
| xnn_log_error( |
| "failed to define %s operator with input ID #%" PRIu32 ", filter ID #%" PRIu32 ", and output ID #%" PRIu32 |
| ": mismatching datatypes across input (%s), filter (%s), and output (%s)", |
| xnn_node_type_to_string(xnn_node_type_fully_connected), input_id, filter_id, output_id, |
| xnn_datatype_to_string(input_value->datatype), |
| xnn_datatype_to_string(filter_value->datatype), |
| xnn_datatype_to_string(output_value->datatype)); |
| return xnn_status_invalid_parameter; |
| } |
| } |
| |
| struct xnn_node* node = xnn_subgraph_new_node(subgraph); |
| if (node == NULL) { |
| return xnn_status_out_of_memory; |
| } |
| |
| node->type = xnn_node_type_fully_connected; |
| node->compute_type = compute_type; |
| node->activation.output_min = output_min; |
| node->activation.output_max = output_max; |
| node->num_inputs = 2 + (size_t) (bias_id != XNN_INVALID_VALUE_ID); |
| node->inputs[0] = input_id; |
| node->inputs[1] = filter_id; |
| node->inputs[2] = bias_id; |
| node->num_outputs = 1; |
| node->outputs[0] = output_id; |
| node->flags = flags; |
| |
| node->create = create_fully_connected_operator; |
| node->setup = setup_fully_connected_operator; |
| |
| return xnn_status_success; |
| } |