import inspect as _inspect
import os as _os
import site as _site
import sys as _sys

# Do not remove this line; See https://github.com/tensorflow/tensorflow/issues/42596
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader

# ==============================================================================

# Bring in all of the public TensorFlow interface into this
# module.

# pylint: disable=g-bad-import-order
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import

from tensorflow.python.platform import flags  # pylint: disable=g-import-not-at-top
from tensorflow.python.platform import app  # pylint: disable=g-import-not-at-top
app.flags = flags

  tensorflow::unwrap(ctx)->SetExecutorForThread(executor->executor());
}

TFE_Executor* TFE_ContextGetExecutorForThread(TFE_Context* ctx) {
  return new TFE_Executor(&tensorflow::unwrap(ctx)->Executor());
}

void TFE_HostAddressSpace(TFE_Context* ctx, TF_Buffer* buf) {
  auto address_space = tensorflow::DeviceNameUtils::AddressSpace(
      tensorflow::unwrap(ctx)->HostCPUParsedName());

  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h));
  if (handle->Type() != TensorHandle::LOCAL) {
    status->status = tensorflow::errors::InvalidArgument(
        "DLPack doesn't support ", handle->TypeString(), " tensor");
    return nullptr;
  }

tf_cc_test(
    name = "modular_filesystem_test",
    size = "small",
    srcs = ["modular_filesystem_test.cc"],
    linkopts = ["-ldl"],
    tags = [
        "manual",  # Requires DSOs as arguments, eventual setup
        "notap",  # b/139060984, requires implementing modular support for Google filesystem
    ],
    deps = [
        ":modular_filesystem",
        "//tensorflow/core:framework_internal",
        "//tensorflow/core/lib/io:path",

import importlib
import inspect as _inspect
import os as _os
import site as _site
import sys as _sys

# pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.platform import tf_logging as _logging

AbstractContext* BuildFunction(const char* fn_name) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TF_ExecutionContext* graph_ctx = TF_CreateFunction(fn_name, status.get());
  return unwrap(graph_ctx);
}

Status CreateParamsForInputs(AbstractContext* ctx,
                             absl::Span<AbstractTensorHandle* const> inputs,
                             std::vector<AbstractTensorHandle*>* params) {

        "@local_tsl//tsl/platform:ctstring",
        "@local_xla//xla/tsl/c:srcs",
    ],
    visibility = ["//visibility:public"],
)

cc_library(
    name = "pywrap_required_hdrs",
    textual_hdrs = [
        "c_api_internal.h",
        "c_api_macros.h",
        "conversion_macros.h",
        "python_api.h",
        "tensor_interface.h",
        "tf_status_helper.h",

    TFE_OpSetDevice(matmul, cpu_device_name.c_str(), status);
    EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
    auto remote_arg =
        tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h1_task2));
    // The input handles should never change since they have been mirrored.
    ASSERT_FALSE(remote_arg->HasLocalMirror(nullptr));
  }

  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;

# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via
# REGISTER_OP and REGISTER_KERNEL_BUILDER (which use symbols from
# libtensorflow_framework.so), and pywrap_tensorflow can then use these
# ops. Since other languages use the same libtensorflow_framework.so, op
# libraries are language agnostic.
#