// error information in *status.
TF_CAPI_EXPORT extern void TFE_ContextOptionsSetConfig(
    TFE_ContextOptions* options, const void* proto, size_t proto_len,
    TF_Status* status);

// Controls how to act when we try to run an operation on a given device but
// some input tensors are not on that device.
// LINT.IfChange
// Note: Keep in sync with internal copy of enum in eager/context.h.

```

To specify the file via a Bazel command argument, use the following:

```
--repo_env=REQUIREMENTS_FILE_NAME=my_requirements.in
```

### How to run the updater

```
bash updater.sh
```

## How to add a new Python version

Note: Updating the
[rules-python](https://github.com/bazelbuild/rules_python/releases) version may
be required before going through the steps below. This is due to the new Python

2)  Reference [TensorFlow Lite Model Colab](https://colab.research.google.com/gist/ymodak/0dfeb28255e189c5c48d9093f296e9a8/tensorflow-lite-debugger-colab.ipynb): Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).

```

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

## How to Test Your Changes to TensorFlow

You may check how your changes will affect TensorFlow by:

1. Creating a PR and observing the presubmit test results
2. Running the CI scripts locally, as explained below

// APIs specific to Eager modes
// -----------------------------------------------------------------------------

// Temporary APIs till we figure out how to create scalar valued Eager
// tensors and how to get value out of eager abstract tensors.
TF_AbstractTensor* TF_CreateAbstractTensorFromEagerTensor(TFE_TensorHandle* t,
                                                          TF_Status* s);

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

### Contributing code

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a

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

```
bazel build //:test_import_api_packages
```

##### How to Run

```
bazel test //:test_import_api_packages --test_output=all

  status = env_->GetChildren(dirpath, &children);
  EXPECT_PRED2(UnimplementedOrReturnsCode, status, Code::OK);
  if (!status.ok()) GTEST_SKIP() << "GetChildren() not supported: " << status;

  // All entries must show up in the vector.
  // Must contain only the last name in filenames and dirnames.
  const std::vector<std::string> expected_children = {"a_file", "another_file",

    string expected_msg =
        "No gradient defined for op: TestOpWithNoGradient. Please see "
        "https://www.tensorflow.org/code/"
        "tensorflow/cc/gradients/README.md"
        " for instructions on how to add C++ gradients.";
    EXPECT_EQ(expected_msg, TF_Message(s_));
  }

  // Run the graph and ensure that the gradient values are as expected.
  void RunGraphsAndCompareOutputs(TF_Output* grad_outputs,

  files = subprocess.check_output(
      ["grep", "-rlE", '(failures|errors)="[1-9]', sys.argv[1]]
  )
except subprocess.CalledProcessError as e:
  print("No failures found to log!")
  exit(0)

# For test cases, only show the ones that failed that have text (a log)
seen = collections.Counter()
runfiles_matcher = re.compile(r"(/.*\.runfiles/)")


for f in files.strip().splitlines():