-  while (*__s != '\0' && *__s != __accept1 && *__s != __accept2)
-    ++__s;
-  return *__s == '\0' ? NULL : (char *) (size_t) __s;
-}
-
-__STRING_INLINE char *__strpbrk_c3 (const char *__s, int __accept1,
-				    int __accept2, int __accept3);
-__STRING_INLINE char *
-__strpbrk_c3 (const char *__s, int __accept1, int __accept2, int __accept3)
-{

// SECTION 1. Implementation for `TF_RandomAccessFile`
// ----------------------------------------------------------------------------
namespace tf_random_access_file {

// TODO(b/139060984): Implement later

}  // namespace tf_random_access_file

// SECTION 2. Implementation for `TF_WritableFile`
// ----------------------------------------------------------------------------
namespace tf_writable_file {

# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.
try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.

***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.

### Contributing code

}

// TODO(agarwal): use an automatic mechanism for handling None arguments to
// gradient functions.
//
// Some gradient functions can accept None arguments for gradients. The
// following maps the operation name to the indices at which the corresponding
// gradient function can accept None values. e.g. FusedBatchNorm outputs 5
// values and hence receives 5 gradient values during backprop. However the

                            &gcs_file->gcs_client, status_));

  read = tf_random_access_file::Read(file, 0, content_view.length(), result,
                                     status_);
  ASSERT_TF_OK(status_);
  ASSERT_TRUE(CompareSubString(0, content_view.length(), result, read));

  read = tf_random_access_file::Read(file, 0, 4, result, status_);
  ASSERT_TF_OK(status_);

                  std::string* bucket, std::string* object, TF_Status* status);

namespace tf_random_access_file {
void Cleanup(TF_RandomAccessFile* file);
int64_t Read(const TF_RandomAccessFile* file, uint64_t offset, size_t n,
             char* buffer, TF_Status* status);
}  // namespace tf_random_access_file

namespace tf_writable_file {
void Cleanup(TF_WritableFile* file);

#!/usr/bin/env python3
# pylint:disable=protected-access
#
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

  // device. If is_async=false (constructor argument) this means the ops have
  // run and have results. If is_async=true it means that all of the
  // device-specific executors have scheduled the op.
  //
  // Accepts inferred shapes for outputs (`expected_output_shapes`), which if
  // fully defined will avoid querying the shapes of the underlying
  // TensorHandles when ParallelTensor::Shape is called. This allows async