const char* name);

// Enables tracing of RunMetadata on the ops executed from this context.
TF_CAPI_EXPORT extern void TFE_ContextEnableRunMetadata(TFE_Context* ctx);

// Disables tracing of RunMetadata on the ops executed from this context.
TF_CAPI_EXPORT extern void TFE_ContextDisableRunMetadata(TFE_Context* ctx);

* Add ops to `tensorflow.raw_ops` that were missing.

* `tf.CheckpointOptions`

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# A shared object which includes registration mechanisms for ops and
# kernels. Does not include the implementations of any ops or kernels. Instead,
# the library which loads libtensorflow_framework.so
# (e.g. _pywrap_tensorflow_internal.so for Python, libtensorflow.so for the C
# API) is responsible for registering ops with libtensorflow_framework.so. In
# addition to this core set of ops, user libraries which are loaded (via

    TFE_Executor*, TF_Status* status);

// When an error happens, any pending operations are discarded, and newly issued
// ops return an error. This call clears the error state and re-enables
// execution of newly issued ops.
//
// Note that outputs of discarded ops remain in a corrupt state and should not
// be used for future calls.
// TODO(agarwal): mark the affected handles and raise errors if they are used.

	// md5sum of the data to written is required as input for PutObject.

	md5hex := getMD5Hash(textData)
	sha256hex := ""

	// benchmark utility which helps obtain number of allocations and bytes allocated per ops.
	b.ReportAllocs()
	// the actual benchmark for PutObject starts here. Reset the benchmark timer.
	b.ResetTimer()
	for i := 0; i < b.N; i++ {
		// insert the object.

  // TF eager runtime.
  // TODO(b/172877902): These helper functions are currently used to support
  // PyFuncOp on TFRT, and might be useful for ops that directly use low
  // level TF APIs. Remove/replace the following functions when TFRT native
  // ops are implemented.
  //===--------------------------------------------------------------------===//
  // Create an abstract tensor handle from tensorflow::Tensor.

					" --injectConfigFile testdata/inject-config-inline-iop.yaml -f testdata/deployment/hello.yaml",
				" "),
			GoldenFilename: "testdata/deployment/hello.yaml.iop.injected",
		},
		{ // case 6 with iops and values override
			Args: strings.Split(
				"--operatorFileName testdata/istio-operator.yaml"+
					" --injectConfigFile testdata/inject-config-iop.yaml -f testdata/deployment/hello.yaml"+

---
name: TensorFlow Lite Op Request
about: Use this template for reporting Lite ops you are using or missing
labels: 'comp:lite'

---

**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installed from (source or binary):
- TensorFlow version (or github SHA if from source):


**Provide the text output from tflite_convert**

```
# Copy and paste here
```

  bool async = false;
  TFE_ContextDevicePlacementPolicy device_placement_policy{
      TFE_DEVICE_PLACEMENT_SILENT};
  // If true, use TFRT backend
  bool use_tfrt = false;
  // Whether to run elementary eager ops wrapped in a call op.
  bool run_eager_op_as_function = false;
  // Whether to rewrite jit_compile functions.
  bool jit_compile_rewrite = false;
};