TF_ExecutionContextGetTFEContext(graph_ctx, status.get());
  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(status.get()));

  TF_DeleteExecutionContext(graph_ctx);
}

// The above tests are run for a combination of:
// - graphdef and MLIR tracing engine
INSTANTIATE_TEST_SUITE_P(Tracing, UnifiedCAPI,
                         ::testing::Combine(::testing::Values("graphdef",

//
// As we need these URI schemes to instantiate the test suite when
// `testing::InitGoogleTest` gets called, here we just store them to an
// internal scheme registry. See `URISchemeRegister` above.
static bool GetURIScheme(const std::string& scheme) {
  tensorflow::SchemeVector()->push_back(scheme);
  return true;
}

// This function is used for cloud filesystem

  TF_DeleteTensor(tensor);
  TFE_DeleteTensorHandle(retvals[0]);

  TFE_DeleteOp(op);

  TFE_DeleteContext(ctx);
  TF_DeleteStatus(status);
}

// Same test as above, expect use SetOpAttrValueScalar to set attrs.
TEST(CAPI, TestTFE_SetOpAttrs) {
  // Test that TFE_OpSetAttrString doesn't hold on to the value after it
  // returns.
  TF_Status* status = TF_NewStatus();

    TF_DeleteGraph(graph_);
    TF_DeleteStatus(s_);
  }

  TF_OperationDescription* init(string type) {
    // Construct op_name to match the name used by REGISTER_OP in the
    // ATTR_TEST_REGISTER calls above.
    string op_name = "CApiAttributesTestOp";
    if (type.find("list(") == 0) {
      op_name += "List";
      type = type.replace(0, 5, "");
      type = type.replace(type.size() - 1, 1, "");
    }

   | 1.13.1 - 2.0  | 10.0  |
   
   | 1.5.0 - 1.12.0 | 9.0 |
   
     * If you have above configuration and using _**Windows**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the %PATH% environment variable.
       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
     * If you have above configuration and using _**Ubuntu/Linux**_ platform -

```
(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```

                      _CONTRIB_WARNING)
# The templated code that replaces the placeholder above sometimes
# sets the __all__ variable. If it does, we have to be sure to add
# "contrib".
if "__all__" in vars():
  vars()["__all__"].append("contrib")

from tensorflow.python.platform import flags
# The "app" module will be imported as part of the placeholder section above.
_current_module.app.flags = flags  # pylint: disable=undefined-variable

which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.

modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

  /// operations.
  ///
  /// This operation must be provided. See "REQUIRED OPERATIONS" above.
  void (*cleanup)(TF_ReadOnlyMemoryRegion* region);

  /// Returns a pointer to the memory region.
  ///
  /// This operation must be provided. See "REQUIRED OPERATIONS" above.
  const void* (*data)(const TF_ReadOnlyMemoryRegion* region);

  /// Returns the length of the memory region in bytes.
  ///