TracingContext* tracing_ctx = dyn_cast<TracingContext>(unwrap(func));
  if (!tracing_ctx) {
    tsl::Set_TF_Status_from_Status(
        s, tensorflow::errors::InvalidArgument(
               "TF_AddFunctionParameter must be called on a TracingContext."));
    return nullptr;
  }
  tensorflow::PartialTensorShape partial_shape;
  if (shape.num_dims != -1) {
    DCHECK(shape.dim_sizes != nullptr);

  virtual Status InitializeLocalOnlyContext(const ServerDef& server_def,
                                            int keep_alive_secs) = 0;

  // Set up a multi-client distributed execution environment. Must be called
  // on all tasks in the cluster. This call internally coordinates with other
  // tasks to initialize the eager context and TF server for multi-client
  // execution.

  Cleanup(Cleanup&& src)  // NOLINT
      : released_(src.is_released()), f_(src.release()) {}

  // Implicitly move-constructible from any compatible Cleanup<G>.
  // The source will be released as if src.release() were called.
  // A moved-from Cleanup can be safely destroyed or reassigned.
  template <typename G>
  Cleanup(Cleanup<G>&& src)  // NOLINT
      : released_(src.is_released()), f_(src.release()) {}

// things like the available devices, resource manager etc.
// TFE_Context must outlive all tensor handles created using it. In other
// words, TFE_DeleteContext() must be called after all tensor handles have
// been deleted (with TFE_DeleteTensorHandle).
//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(

from the `envs` directory that is filled with configuration options:

-   Nightly jobs (Run nightly on the `nightly` branch)
    -   Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh`
-   Continuous jobs (Run on every GitHub commit)
    -   Uses `pycpp.sh`
-   Presubmit jobs (Run on every GitHub PR)
    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

// returned will be on the device in which the TFE_TensorHandle resides (so e.g.
// for a GPU tensor this will return a pointer to GPU memory). The pointer is
// only guaranteed to be valid until TFE_DeleteTensorHandle is called on this
// TensorHandle. Only supports POD data types.
TF_CAPI_EXPORT extern void* TFE_TensorHandleDevicePointer(TFE_TensorHandle*,
                                                          TF_Status*);

```bash
apt-get install -y clang-tidy
```

You can check a C/C++ file by doing:


```bash
clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc
diff <my_cc_file> /tmp/my_cc_file.cc
```

#### Python coding style

Changes to TensorFlow Python code should conform to

# limitations under the License.
# ==============================================================================
source "${BASH_SOURCE%/*}/utilities/setup.sh"

/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,

// gradients.
//
// `ZerosLike` is not expected to be called and returns a nullptr. The creation
// of default zeros grads is handled by the `DefaultGradientFunction` registered
// for each op.
// TODO(srbs): We need to define `ZerosLike` here to keep the compiler happy.
// Figure out a way to avoid this.
// TODO(srbs): Should ZerosLike check-fail instead of returning nullptr?
class TapeTensor {
 public: