void Watch(int64_t tensor_id, Gradient* tangent);

  // Removes the gradient associated with tensor_id. Should be called when the
  // Tensor associated with `tensor_id` is deleted.
  void DeleteGradient(int64_t tensor_id);

  // Runs forward autodiff. Should be called whenever a new operation is
  // available and the accumulator is active.
  //

  p.text = runfiles_matcher.sub("[testroot]/", p.text)
  source_file = p.getparent().getparent().get("source_file", "")
  p.text += f"\nNOTE: From {source_file}"
  if "bazel_pip" in source_file:
    p.text += (
        "\nNOTE: This is a --config=pip test. Remove 'bazel_pip' to find"
        " the file."
    )
  n_failures = seen[key]
  p.text += f"\nNOTE: Number of failures for this test: {seen[key]}."

  TestRemoteExecuteUpdateServerDefResourceAccess(true);
}

void TestRemoteExecuteUpdateServerDefWithFailures(bool async) {
  // Fail fast on GetStatus requests so we can get errors instead of timeout
  // when updating cluster with non-exsitent worker
  tensorflow::setenv("GRPC_FAIL_FAST", "TRUE", /*overwrite=*/1);

  tensorflow::ServerDef server_def = GetServerDef(2);
  // This server def has the task index set to 0.

    for (const EdgeSpec& e : e_edges) {
      ASSERT_TRUE(a_edges.find(e) != a_edges.end())
          << "Failed to find expected edge " << e.ToString()
          << " in fdef: " << fdef.DebugString();
    }
    for (const EdgeSpec& e : c_edges) {
      ASSERT_TRUE(a_edges.find(e) != a_edges.end())
          << "Failed to find expected control edge " << e.ToString()
          << " in fdef: " << fdef.DebugString();
    }

      "ApiDefMap is not supported on mobile.");
#else
  mutex_lock l(api_def_map->lock);
  if (api_def_map->update_docs_called) {
    status->status = FailedPrecondition(
        "TF_ApiDefMapPut cannot be called after TF_ApiDefMapGet has been "
        "called.");
    return;
  }
  string api_def_text(text, text_len);
  status->status = api_def_map->api_def_map.LoadApiDef(api_def_text);

  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.

// 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*);