* https://www.tensorflow.org/guide/migrate

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in
# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.

}

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.
namespace internal {
Status Reset(AbstractOperation* op_, const char* op,
             const char* raw_device_name, ForwardOperation* forward_op_) {
  forward_op_->op_name = op;
  forward_op_->attrs.Reset(op);

    : AbstractContext(kTape), parent_ctx_(c), tape_(tape), registry_(registry) {
  // TODO(srbs): Make AbstractContext ref counted.
  // parent_ctx_->Ref();
}
void TapeContext::Release() {
  // TODO(srbs): Change to Unref()
  delete this;
}
TapeContext::~TapeContext() {
  // TODO(srbs): Make AbstractContext ref counted.
  // parent_ctx_->Unref();
}
TapeOperation* TapeContext::CreateOperation() {

# limitations under the License.
# ==============================================================================

# script to run pip-compile for keras, tensorboard, estimator deps.
# if there is a change in requirements.in then all lock files will be updated
# accordingly.

mv BUILD.bazel BUILD

SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12")

for VERSION in "${SUPPORTED_VERSIONS[@]}"
do

    EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
    auto remote_arg =
        tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h1_task2));
    // The input handles should never change since they have been mirrored.
    ASSERT_FALSE(remote_arg->HasLocalMirror(nullptr));
  }

  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);

namespace internal {

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.

// Records the op name in the `ForwardOperation`.
Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

// Records the inputs in the `ForwardOperation`.

if [[ "$TFCI_WHL_SIZE_LIMIT_ENABLE" == "1" ]] && [[ -n "$(find . -iname "*.whl" -size "+$TFCI_WHL_SIZE_LIMIT")" ]]; then
  echo "Error: Generated wheel is too big! Limit is $TFCI_WHL_SIZE_LIMIT"
  echo '(search for TFCI_WHL_SIZE_LIMIT to change it)'
  ls -sh *.whl
  exit 2
fi

# Quick install checks
venv=$(mktemp -d)
"python${TFCI_PYTHON_VERSION}" -m venv "$venv"
python="$venv/bin/python3"

/// as well. Here is a short summary of what changes are allowed:
///   * adding a new method at the end of a table is allowed at any time;
///   * any other change to these tables is only allowed on a major TensorFlow
///     version change (e.g., from 2.x to 3.0). This is provided as an escape
///     hatch to allow cleaning up these tables. Since any of these changes

# support through e.g. `--config=cuda` (or `--config=cuda_clang` in OSS).
alias(
    name = "is_cuda_enabled",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_enabled",
        "@local_config_cuda//cuda:using_clang",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(

your code interacts with the filesystem, network, etc. and uses checkpointed
variables as part of those interactions (ex: using a string variable to build a
filesystem path), a maliciously created checkpoint might be able to change the
targets of those operations, which could result in arbitrary
read/write/executions.

### Running a TensorFlow server

TensorFlow is a platform for distributed computing, and as such there is a