std::list<size_t> calls;
  auto fetcher = [&calls, block_size](const string& filename, size_t offset,
                                      size_t n, char* buffer,
                                      TF_Status* status) -> int64_t {
    EXPECT_EQ(n, block_size);
    EXPECT_FALSE(calls.empty()) << "at offset = " << offset;
    if (!calls.empty()) {
      EXPECT_EQ(offset, calls.front());
      calls.pop_front();
    }

#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/file_system_helper.h"
#include "tsl/platform/errors.h"

// TODO(b/139060984): After all filesystems are converted, all calls to
// methods from `FileSystem` will have to be replaced to calls to private
// methods here, as part of making this class a singleton and the only way to
// register/use filesystems.

namespace tensorflow {

using UniquePtrTo_TF_Status =

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Setup a session and a partial run handle.  The partial run will allow
  // computation of A + 2 + B in two phases (calls to TF_SessionPRun):
  // 1. Feed A and get (A+2)
  // 2. Feed B and get (A+2)+B
  TF_SessionOptions* opts = TF_NewSessionOptions();
  TF_Session* sess = TF_NewSession(graph, opts, s);
  TF_DeleteSessionOptions(opts);

// Clears the internal caches in the TFE context. Useful when reseeding random
// ops.
TF_CAPI_EXPORT extern void TFE_ContextClearCaches(TFE_Context* ctx);

// Sets a thread-local device placement policy. After this call, other calls to
// TFE_Execute in the same thread will use the device policy specified here
// instead of the device policy used to construct the context. This has no
// effect on the device policy used by other program threads.

  // it will be compatible with it: the name will be updated by device placement
  // logic to refer to the specific device chosen.
  //
  // Example: If one calls `op->SetDeviceName("/device:GPU")`, the value
  // returned by DeviceName should be "/device:GPU:*" until a particular GPU is
  // chosen for the operation by the device placement logic in the

)

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