blob: 9a4108823c832712637161b18b5fac5944b0928c [file] [log] [blame]
// 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 <stdlib.h>
#include <xnnpack.h>
#include <xnnpack/allocator.h>
#include <xnnpack/log.h>
#include <xnnpack/operator.h>
#include <xnnpack/params-init.h>
#include <xnnpack/params.h>
static enum xnn_status create_unary_elementwise_nc(
size_t channels,
size_t input_stride,
size_t output_stride,
uint32_t flags,
const void* params,
size_t params_size,
enum xnn_operator_type operator_type,
xnn_operator_t* unary_elementwise_op_out)
{
xnn_operator_t unary_elementwise_op = NULL;
if (!xnn_params.initialized) {
xnn_log_error("failed to create %s operator: XNNPACK is not initialized",
xnn_operator_type_to_string(operator_type));
return xnn_status_uninitialized;
}
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_clamp_nc_f32), channels);
return xnn_status_invalid_parameter;
}
if (input_stride < channels) {
xnn_log_error(
"failed to create %s operator with input element stride of %zu: "
"stride must be at least as large as the number of channels (%zu)",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_f32), input_stride, channels);
return xnn_status_invalid_parameter;
}
if (output_stride < channels) {
xnn_log_error(
"failed to create %s operator with output element stride of %zu: "
"stride must be at least as large as the number of channels (%zu)",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_f32), output_stride, channels);
return xnn_status_invalid_parameter;
}
unary_elementwise_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator));
if (unary_elementwise_op == NULL) {
xnn_log_error(
"failed to allocate %zu bytes for %s operator descriptor",
sizeof(struct xnn_operator), xnn_operator_type_to_string(operator_type));
return xnn_status_out_of_memory;
}
unary_elementwise_op->channels = channels;
unary_elementwise_op->input_pixel_stride = input_stride;
unary_elementwise_op->output_pixel_stride = output_stride;
if (params_size != 0) {
memcpy(&unary_elementwise_op->params, params, params_size);
}
unary_elementwise_op->type = operator_type;
unary_elementwise_op->ukernel.type = xnn_ukernel_type_unary_elementwise;
unary_elementwise_op->state = xnn_run_state_invalid;
*unary_elementwise_op_out = unary_elementwise_op;
return xnn_status_success;
}
static enum xnn_status setup_unary_elementwise_nc(
xnn_operator_t unary_elementwise_op,
size_t batch_size,
const void* input,
void* output,
xnn_univector_ukernel_function ukernel,
uint32_t log2_element_size,
const void* params,
size_t params_size)
{
if (!xnn_params.initialized) {
xnn_log_error("failed to setup %s operator: XNNPACK is not initialized",
xnn_operator_type_to_string(unary_elementwise_op->type));
return xnn_status_uninitialized;
}
if (batch_size == 0) {
unary_elementwise_op->state = xnn_run_state_skip;
return xnn_status_success;
}
const size_t channels = unary_elementwise_op->channels;
const size_t input_stride = unary_elementwise_op->input_pixel_stride;
const size_t output_stride = unary_elementwise_op->output_pixel_stride;
if ((((input_stride ^ channels) | (output_stride ^ channels)) == 0) || batch_size == 1) {
const size_t block_size = 4096;
unary_elementwise_op->context.univector_contiguous = (struct univector_contiguous_context) {
.x = input,
.x_stride = input_stride << log2_element_size,
.y = output,
.y_stride = output_stride << log2_element_size,
.ukernel = ukernel,
};
if (params_size != 0) {
memcpy(&unary_elementwise_op->context.univector_contiguous.params, params, params_size);
}
unary_elementwise_op->compute.type = xnn_parallelization_type_1d_tile_1d;
unary_elementwise_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_univector_contiguous;
unary_elementwise_op->compute.range[0] = (batch_size * channels) << log2_element_size;
unary_elementwise_op->compute.tile[0] = block_size;
} else {
unary_elementwise_op->context.univector_strided = (struct univector_strided_context) {
.n = channels << log2_element_size,
.x = input,
.x_stride = input_stride << log2_element_size,
.y = output,
.y_stride = output_stride << log2_element_size,
.ukernel = ukernel,
};
if (params_size != 0) {
memcpy(&unary_elementwise_op->context.univector_strided.params, params, params_size);
}
unary_elementwise_op->compute.type = xnn_parallelization_type_1d_tile_1d;
unary_elementwise_op->compute.task_1d_tile_1d = (pthreadpool_task_1d_tile_1d_t) xnn_compute_univector_strided;
unary_elementwise_op->compute.range[0] = batch_size;
unary_elementwise_op->compute.tile[0] = 1;
}
unary_elementwise_op->state = xnn_run_state_ready;
return xnn_status_success;
}
enum xnn_status xnn_create_clamp_nc_u8(
size_t channels,
size_t input_stride,
size_t output_stride,
uint8_t output_min,
uint8_t output_max,
uint32_t flags,
xnn_operator_t* clamp_op_out)
{
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_clamp_nc_u8), output_min, output_max);
return xnn_status_invalid_parameter;
}
const union xnn_u8_minmax_params params = xnn_init_u8_minmax_params(output_min, output_max);
return create_unary_elementwise_nc(
channels, input_stride, output_stride, flags,
&params, sizeof(params),
xnn_operator_type_clamp_nc_u8,
clamp_op_out);
}
enum xnn_status xnn_create_clamp_nc_f32(
size_t channels,
size_t input_stride,
size_t output_stride,
float output_min,
float output_max,
uint32_t flags,
xnn_operator_t* clamp_op_out)
{
if (isnan(output_min)) {
xnn_log_error(
"failed to create %s operator with NaN output lower bound: lower bound must be non-NaN",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_f32));
return xnn_status_invalid_parameter;
}
if (isnan(output_max)) {
xnn_log_error(
"failed to create %s operator with NaN output upper bound: upper bound must be non-NaN",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_f32));
return xnn_status_invalid_parameter;
}
if (output_min >= output_max) {
xnn_log_error(
"failed to create %s operator with [%.7g, %.7g] output range: lower bound must be below upper bound",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_f32), output_min, output_max);
return xnn_status_invalid_parameter;
}
const union xnn_f32_minmax_params params = xnn_init_f32_minmax_params(output_min, output_max);
return create_unary_elementwise_nc(
channels, input_stride, output_stride, flags,
&params, sizeof(params),
xnn_operator_type_clamp_nc_f32,
clamp_op_out);
}
enum xnn_status xnn_create_hardswish_nc_f32(
size_t channels,
size_t input_stride,
size_t output_stride,
uint32_t flags,
xnn_operator_t* hardswish_op_out)
{
const union xnn_f32_hswish_params params = xnn_init_f32_hswish_params();
return create_unary_elementwise_nc(
channels, input_stride, output_stride, flags,
&params, sizeof(params),
xnn_operator_type_hardswish_nc_f32,
hardswish_op_out);
}
enum xnn_status xnn_create_sigmoid_nc_f32(
size_t channels,
size_t input_stride,
size_t output_stride,
uint32_t flags,
xnn_operator_t* sigmoid_op_out)
{
return create_unary_elementwise_nc(
channels, input_stride, output_stride, flags,
NULL, 0,
xnn_operator_type_sigmoid_nc_f32,
sigmoid_op_out);
}
enum xnn_status xnn_setup_clamp_nc_u8(
xnn_operator_t clamp_op,
size_t batch_size,
const uint8_t* input,
uint8_t* output,
pthreadpool_t threadpool)
{
if (clamp_op->type != xnn_operator_type_clamp_nc_u8) {
xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_u8),
xnn_operator_type_to_string(clamp_op->type));
return xnn_status_invalid_parameter;
}
clamp_op->state = xnn_run_state_invalid;
return setup_unary_elementwise_nc(
clamp_op,
batch_size, input, output,
xnn_params.u8.clamp,
0 /* log2(sizeof(uint8_t)) */,
&clamp_op->params.u8_minmax, sizeof(clamp_op->params.u8_minmax));
}
enum xnn_status xnn_setup_clamp_nc_f32(
xnn_operator_t clamp_op,
size_t batch_size,
const float* input,
float* output,
pthreadpool_t threadpool)
{
if (clamp_op->type != xnn_operator_type_clamp_nc_f32) {
xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)",
xnn_operator_type_to_string(xnn_operator_type_clamp_nc_f32),
xnn_operator_type_to_string(clamp_op->type));
return xnn_status_invalid_parameter;
}
clamp_op->state = xnn_run_state_invalid;
return setup_unary_elementwise_nc(
clamp_op,
batch_size, input, output,
xnn_params.f32.clamp,
2 /* log2(sizeof(float)) */,
&clamp_op->params.f32_minmax, sizeof(clamp_op->params.f32_minmax));
}
enum xnn_status xnn_setup_hardswish_nc_f32(
xnn_operator_t hardswish_op,
size_t batch_size,
const float* input,
float* output,
pthreadpool_t threadpool)
{
if (hardswish_op->type != xnn_operator_type_hardswish_nc_f32) {
xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)",
xnn_operator_type_to_string(xnn_operator_type_hardswish_nc_f32),
xnn_operator_type_to_string(hardswish_op->type));
return xnn_status_invalid_parameter;
}
hardswish_op->state = xnn_run_state_invalid;
return setup_unary_elementwise_nc(
hardswish_op,
batch_size, input, output,
xnn_params.f32.hswish,
2 /* log2(sizeof(float)) */,
&hardswish_op->params.f32_hswish, sizeof(hardswish_op->params.f32_hswish));
}
enum xnn_status xnn_setup_sigmoid_nc_f32(
xnn_operator_t sigmoid_op,
size_t batch_size,
const float* input,
float* output,
pthreadpool_t threadpool)
{
if (sigmoid_op->type != xnn_operator_type_sigmoid_nc_f32) {
xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)",
xnn_operator_type_to_string(xnn_operator_type_sigmoid_nc_f32),
xnn_operator_type_to_string(sigmoid_op->type));
return xnn_status_invalid_parameter;
}
sigmoid_op->state = xnn_run_state_invalid;
return setup_unary_elementwise_nc(
sigmoid_op,
batch_size, input, output,
xnn_params.f32.sigmoid,
2 /* log2(sizeof(float)) */,
NULL, 0);
}