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// 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;
}