{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

implement, and therefore security issues deriving from their absence are not
considered a vulnerability in TensorFlow.

### Resource allocation

A denial of service caused by one model could bring down the entire server, but
we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from
happening (e.g., rate limits, ACLs, monitors to restart broken servers).

// LINT.IfChange
typedef struct TF_FilesystemOps {
  /// Acquires all resources used by the filesystem.
  ///
  /// This operation must be provided. See "REQUIRED OPERATIONS" above.
  void (*init)(TF_Filesystem* filesystem, TF_Status* status);

  /// Releases all resources used by the filesystem
  ///
  /// NOTE: TensorFlow does not unload DSOs. Thus, the only way a filesystem

for machine learning. It has a comprehensive, flexible ecosystem of
[tools](https://www.tensorflow.org/resources/tools),
[libraries](https://www.tensorflow.org/resources/libraries-extensions), and
[community](https://www.tensorflow.org/community) resources that lets
researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

  };
  explicit AbstractOperation(AbstractOperationKind kind) : kind_(kind) {}
  virtual ~AbstractOperation() {}

 public:
  AbstractOperationKind getKind() const { return kind_; }

  // Release any underlying resources, including the interface object.
  //
  // WARNING: The destructor of this class is marked as protected to disallow
  // clients from directly destroying this object since it may manage it's own

  explicit AbstractContext(AbstractContextKind kind) : kind_(kind) {}
  virtual ~AbstractContext() {}

 public:
  AbstractContextKind getKind() const { return kind_; }

  // Release any underlying resources, including the interface object.
  //
  // WARNING: The destructor of this class is marked as protected to disallow
  // clients from directly destroying this object since it may manage its own

# almost all of the same cache layers
export DOCKER_BUILDKIT=1
for target in jax tf; do
  IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG"
  docker pull "$IMAGE" || true
  # Due to some flakiness of resources pulled in the build, allow the docker
  # command to reattempt build a few times in the case of failure (b/302558736)
  set +e
  for i in $(seq 1 5)
  do
    docker build \

# LLVM/Clang: https://apt.llvm.org/
apt-key adv --fetch-keys https://apt.llvm.org/llvm-snapshot.gpg.key

# Set up custom sources
cat >/etc/apt/sources.list.d/custom.list <<SOURCES
# More Python versions: Deadsnakes
deb http://ppa.launchpad.net/deadsnakes/ppa/ubuntu focal main
deb-src http://ppa.launchpad.net/deadsnakes/ppa/ubuntu focal main

# LLVM/Clang 17 repository

                                                        TF_Status* status);

// Some TF ops need a step container to be set to limit the lifetime of some
// resources (mostly TensorArray and Stack, used in while loop gradients in
// graph mode). Calling this on a context tells it to start a step.
TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);

// Item points are invalidated after a call to TF_StringStreamDone.
TF_CAPI_EXPORT extern bool TF_StringStreamNext(TF_StringStream* list,
                                               const char** result);

// Frees the resources associated with given string list. All pointers returned
// by TF_StringStreamNext are invalid after this call.
TF_CAPI_EXPORT extern void TF_StringStreamDone(TF_StringStream* list);