)

load("@pypi//:requirements.bzl", "install_deps")

install_deps()

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.

  // a tensor with the result.
  AbstractTensorHandle* AggregateGradients(
      gtl::ArraySlice<AbstractTensorHandle*> gradient_tensors) const override;

  // Calls the passed-in backward function.
  // op_type is the op's name provided in RecordOperation.
  Status CallBackwardFunction(
      const string& op_type, GradientFunction* gradient_function,

// --------------------------------------------------------------------------
TF_SessionOptions* TF_NewSessionOptions() {
  TF_SessionOptions* out = new TF_SessionOptions;
  // Disable optimizations for static graph to allow calls to Session::Extend.
  out->options.config.mutable_experimental()
      ->set_disable_optimize_for_static_graph(true);
  return out;
}
void TF_DeleteSessionOptions(TF_SessionOptions* opt) { delete opt; }

// This file extends/implements core graph optimizer base classes in terms of
// the C API defined in grappler.h. A class "CSomething" represents a
// "Something" that can be manipulated via calls in the C interface and a C
// struct called "TP_Something".

#include "tensorflow/c/experimental/grappler/grappler.h"

#include <algorithm>
#include <cstddef>
#include <cstring>
#include <string>

// 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.
TF_CAPI_EXPORT extern void TFE_ExecutorClearError(TFE_Executor*);

// Sets a custom Executor for the current thread. All nodes created by this

# under the root of srcjars jars created by bazel, rather than under
# the maven-style src/main/java subdirectory.
#
# Bazel manages annotation generated source as follows: First, it
# calls javac with options that create generated files under a
# bazel-out directory. Next, it archives the generated source files
# into a srcjar directly under the root. There doesn't appear to be a

/// pointers that operate on the corresponding data. Thus, the first argument of
/// each of these functions is a pointer to the paired struct and this argument
/// can be used to track state in between calls (from an object oriented point
/// of view, this can be viewed as a "vtable" for a "class" -- that is the
/// corresponding struct above --; the first argument is in place of `this`).
///

        `compression=None` to `tf.data.experimental.service.distribute(...)`.
    *   `tf.data.Dataset.batch()` now supports `num_parallel_calls` and
        `deterministic` arguments. `num_parallel_calls` is used to indicate that
        multiple input batches should be computed in parallel. With
        `num_parallel_calls` set, `deterministic` is used to indicate that
        outputs can be obtained in the non-deterministic order.

// TODO(b/291142876) Simplify TFE_ContextSetServerDefWithTimeoutAndRetries and
// TFE_ContextUpdateServerDefWithTimeout to be simple wrappers around the same
// C++ function.
// Retries are used for CreateContext calls, which is used in
// ParameterServerStrategy initialization to be robust to worker preemption.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeoutAndRetries(

constexpr char kAppendMode[] = "GCS_APPEND_MODE";
// If GCS_APPEND_MODE=compose then instead the new data is uploaded to a
// temporary object and composed with the original object. This is disabled by
// default as the multiple API calls required add a risk of stranding temporary
// objects.
constexpr char kComposeAppend[] = "compose";

// We can cast `google::cloud::StatusCode` to `TF_Code` because they have the
// same integer values. See