# 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.

# -e: abort script if one command fails
# -u: error if undefined variable used
# -o pipefail: entire command fails if pipe fails. watch out for yes | ...

2. Running the CI scripts locally, as explained below
3. **Google employees only**: Google employees can use an internal-only tool
called "MLCI" that makes testing more convenient: it can execute any full CI job
against a pending change. Search for "MLCI" internally to find it.

You may invoke a CI script of your choice by following these instructions:

```bash
cd tensorflow-git-dir

// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextUpdateServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,
    int64_t init_timeout_in_ms, TF_Status* status);

// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeout(

    * 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);

/// only load compatible plugins and discard all others.

// LINT.IfChange(random_access_file_ops_version)
constexpr int TF_RANDOM_ACCESS_FILE_OPS_API = 0;
constexpr int TF_RANDOM_ACCESS_FILE_OPS_ABI = 0;
constexpr size_t TF_RANDOM_ACCESS_FILE_OPS_SIZE =
    sizeof(TF_RandomAccessFileOps);
// LINT.ThenChange()

// LINT.IfChange(writable_file_ops_version)
constexpr int TF_WRITABLE_FILE_OPS_API = 0;

    the output is different from (incorrect) previous versions. Note this
    breaking change only impacts `tf.image.extract_glimpse` and
    `tf.compat.v2.image.extract_glimpse` API endpoints. The behavior of
    `tf.compat.v1.image.extract_glimpse` does not change. The behavior of
    existing C++ kernel `ExtractGlimpse` does not change either, so saved models

# 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`.