tensorflow.org, TensorFlow’s GitHub organization, or any other official TensorFlow web presence allowing for community interactions, as well as at all official TensorFlow events, whether offline or online.

The Code of Conduct also applies within project spaces and in public spaces whenever an individual is representing TensorFlow or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account,...

  }

  // Check for inconsistent state. If there is a block later in the same file
  // in the cache, and our current block is not block size, this likely means
  // we have inconsistent state within the cache. Note: it's possible some
  // incomplete reads may still go undetected.
  if (block->data.size() < block_size_) {
    Key fmax = std::make_pair(key.first, std::numeric_limits<size_t>::max());

init files creation process and is subsequently stored in the wheel file after
the build. It also contains a few paths that cannot be directly imported. These
paths point to attributes or sub-modules within a module's namespace, but they
don't correspond to an actual file or directory on the filesystem. The list of
such paths is stored in the packages_for_skip variable and will be skipped
during the test.

##### How to Build

build --distinct_host_configuration=false

# Disable clang extension that rejects type definitions within offsetof. 
# This was added in clang-16 by https://reviews.llvm.org/D133574.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.

# TensorFlow continuous integration

> **Warning** This folder is still under construction. It is part of an ongoing
> effort to improve the structure of CI and build related files within the
> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

namespace tensorflow {

// Abstract interface to a context.
//
// This serves as a factory for creating `AbstractOperation`s and for
// registering traced functions.
// Operations creation within a context can only be executed in that context
// (for now at least).
// Implementations of the context may contain some state e.g. an execution
// environment, a traced representation etc.
class AbstractContext {
 protected:

# any.sh has two run modes.
#
# 1. RUN, TEST, OR BUILD BAZEL TARGET(S) WITHIN A TFCI ENVIRONMENT
#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#       export TF_ANY_MODE="test" or "build" or "run" (default: "test")
#       ./any.sh
#
# 2. RUN ANY OTHER SCRIPT AND ENV WITH NO SIDE EFFECTS (NO UPLOADS)
#    To use:

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

# DevInfra CI Directory

> **Warning** This folder is still under construction. It is part of an ongoing
> effort to improve the structure of CI and build related files within the
> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

Issue Reporting: File an issue against this repo and tag

typedef struct TF_Input {
  TF_Operation* oper;
  int index;  // The index of the input within oper.
} TF_Input;

// Represents a specific output of an operation.
typedef struct TF_Output {
  TF_Operation* oper;
  int index;  // The index of the output within oper.
} TF_Output;

// TF_Function is a grouping of operations with defined inputs and outputs.