chromium/third_party/xnnpack/src/src/normalization.c

// Copyright 2022 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 <stdlib.h>
#include <string.h>

#include "xnnpack.h"
#include "xnnpack/common.h"
#include "xnnpack/math.h"

void xnn_normalize_slice(
    const size_t num_dims,
    const size_t offsets[XNN_MIN_ELEMENTS(1)],
    const size_t sizes[XNN_MIN_ELEMENTS(1)],
    const size_t input_shape[XNN_MIN_ELEMENTS(1)],
    size_t normalized_offsets[XNN_MIN_ELEMENTS(XNN_MAX_TENSOR_DIMS)],
    size_t normalized_input_shape[XNN_MIN_ELEMENTS(XNN_MAX_TENSOR_DIMS)],
    size_t normalized_output_shape[XNN_MIN_ELEMENTS(XNN_MAX_TENSOR_DIMS)],
    size_t* num_normalized_dims)
{ … }

// Returns true if input stride and output stride are NULL or the expected input/output stride matches the actual input/output stride.
static bool can_dimension_be_removed(
    const size_t* input_stride,
    const size_t* output_stride,
    const size_t* shape,
    const size_t* inverted_perm,
    size_t input_dim,
    const size_t num_dims) { … }

// Remove dimension perm[dim] from shape, perm, input & output strides.
static void fold_into_previous_dim(
    size_t* shape,
    size_t* perm,
    size_t* inverted_perm,
    size_t* input_stride,
    size_t* output_stride,
    size_t num_dims,
    size_t input_dim)
{ … }

void xnn_normalize_transpose_permutation(
    const size_t num_dims,
    const size_t element_size,
    const size_t* perm,
    const size_t* shape,
    const size_t* input_stride,
    const size_t* output_stride,
    size_t* normalized_num_dims,
    size_t* normalized_element_size_out,
    size_t* normalized_perm,
    size_t* normalized_shape,
    size_t* normalized_input_stride,
    size_t* normalized_output_stride)
{ … }

static int cmp_value_size_t(const void* a_ptr, const void* b_ptr) { … }

void xnn_normalize_reduction(
    size_t* num_reduction_axes_ptr,
    size_t* reduction_axes,
    size_t* num_input_dims_ptr,
    size_t* input_dims)
{ … }