# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.
try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

  x = constant_op.constant([1], name='x_const')
  y = constant_op.constant([2], name='y_const')
  test_func(x, y, name='func_call')  # pylint: disable=unexpected-keyword-arg


def tfsplits(_):
  """A more complex graph, including splits."""
  x = array_ops.placeholder(dtypes.float32, shape=[2, 2], name='x')
  y = array_ops.placeholder(dtypes.float32, shape=[2, 2], name='y')
  for _ in range(3):

# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.

try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

_losses = _KerasLazyLoader(
    globals(), submodule="losses", name="losses", mode="v2")
_metrics = _KerasLazyLoader(
    globals(), submodule="metrics", name="metrics", mode="v2")
_optimizers = _KerasLazyLoader(
    globals(), submodule="optimizers", name="optimizers", mode="v2")
_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers", mode="v2")
setattr(_current_module, "losses", _losses)

from tensorflow.compiler.mlir.quantization.tensorflow.python import py_function_lib
from tensorflow.compiler.mlir.quantization.tensorflow.python import save_model
from tensorflow.core.protobuf import meta_graph_pb2

# Mapping of signature def key -> SignatureDef.
_SignatureDefMap = Mapping[str, meta_graph_pb2.SignatureDef]


def _serialize_signature_def_map(
    signature_def_map: _SignatureDefMap,

_current_module = _sys.modules[__name__]

# Lazy load Keras v1
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
if _tf_uses_legacy_keras:
  _module_dir = _module_util.get_parent_dir_for_name("tf_keras.api._v1.keras")
else:
  _module_dir = _module_util.get_parent_dir_for_name("keras.api._v1.keras")

"""Serves as a common "main" function for all the SavedModel tests.

There is a fair amount of setup needed to initialize tensorflow and get it
into a proper TF2 execution mode. This hides that boilerplate.
"""

import tempfile

from absl import app
from absl import flags
from absl import logging
import tensorflow.compat.v2 as tf

    'tensorflow/compiler/mlir/tfrt',
    'tensorflow/compiler/mlir/tools/kernel_gen',
    os.path.join(external_srcdir, 'local_xla/xla/mlir_hlo'),
    'tensorflow/core/ir/importexport/',
    'tensorflow/core/ir/tests/',
    'tensorflow/core/transforms/',
    'tensorflow/dtensor/mlir/tests',
]
config.mlir_tf_tools_dirs = [
    os.path.join(real_test_srcdir, os.environ['TEST_WORKSPACE'], s)
    for s in mlir_tf_tools_dirs

"""Serves as a common "main" function for all the SavedModel tests.

There is a fair amount of setup needed to initialize tensorflow and get it
into a proper TF2 execution mode. This hides that boilerplate.
"""

import tempfile
from absl import app
from absl import flags
from absl import logging
import tensorflow.compat.v1 as tf