// Returns number of elements across all dimensions.
  virtual Status NumElements(int64_t* num_elements) const = 0;
  // Returns size of specified dimension
  //
  // -1 indicates an unknown axis length; this is unreachable for most standard
  // ImmediateExecutionTensorHandles, but comes up for example when computing
  // the shape of a parallel tensor with component shapes differing across
  // devices.

// the datatype for boolean tensors.
#ifndef TF_Bool
#define TF_Bool unsigned char
#endif  // TF_Bool

// Macro used to calculate struct size for maintaining ABI stability across
// different struct implementations.
#ifndef TF_OFFSET_OF_END
#define TF_OFFSET_OF_END(TYPE, MEMBER) \
  (offsetof(TYPE, MEMBER) + sizeof(((TYPE *)0)->MEMBER))
#endif  // TF_OFFSET_OF_END

    feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in
    [tensorflow/addons](https://github.com/tensorflow/addons) to get some
    airtime before a decision is made regarding whether they are to be migrated
    to the core.
*   As every PR requires several CPU/GPU hours of CI testing, we discourage

The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
"""
contrib = _LazyLoader("contrib", globals(), "tensorflow.contrib",

*   `tf.contrib`:

    *   `tf.contrib` has been deprecated, and functionality has been either
        migrated to the core TensorFlow API, to an ecosystem project such as
        [tensorflow/addons](https://www.github.com/tensorflow/addons) or
        [tensorflow/io](https://www.github.com/tensorflow/io), or removed
        entirely.
    *   Remove `tf.contrib.timeseries` dependency on TF distributions.

system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas...

                                                   const void* proto,
                                                   size_t proto_len,
                                                   TF_Status* status);

// Aborts all ongoing collectives with the specified status. After abortion,
// subsequent collectives will error with this status immediately. To reset the
// collectives, create a new EagerContext.
//

# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build:rbe_linux_cpu --copt=-Wno-gnu-offsetof-extensions
# Python config is the same across all containers because the binary is the same
build:rbe_linux_cpu --repo_env=TF_PYTHON_CONFIG_REPO="@sigbuild-r2.17-clang_config_python"
build:rbe_linux_cpu --python_path="/usr/bin/python3"

      TF_Status* status) const;

  void AsyncWait(TFE_Context* context, TF_Status* status) const;

  // Device strings for component devices that only include a
  // worker/task/replica if any of those differ across components. Useful for
  // printing debug messages.
  std::vector<std::string> SummarizeDeviceNames() const;

 private:
  // A sequence of device names, indicating which devices replicated operations

                                              TF_Tensor* to, TF_Status* status);

// --------------------------------------------------------------------------
// Used to return strings across the C API. The caller does not take ownership
// of the underlying data pointer and is not responsible for freeing it.
typedef struct TF_StringView {
  const char* data;
  size_t len;
} TF_StringView;