tensorflow/models

# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Helper code to run complete models from within python."""

import os
import shutil
import sys
import tempfile

from absl import flags
from absl.testing import flagsaver

from official.utils.flags import core as flags_core


@flagsaver.flagsaver
def run_synthetic(main,
                  tmp_root,
                  extra_flags=None,
                  synth=True,
                  train_epochs=1,
                  epochs_between_evals=1):
  """Performs a minimal run of a model.

    This function is intended to test for syntax errors throughout a model. A
  very limited run is performed using synthetic data.

  Args:
    main: The primary function used to exercise a code path. Generally this
      function is "<MODULE>.main(argv)".
    tmp_root: Root path for the temp directory created by the test class.
    extra_flags: Additional flags passed by the caller of this function.
    synth: Use synthetic data.
    train_epochs: Value of the --train_epochs flag.
    epochs_between_evals: Value of the --epochs_between_evals flag.
  """

  extra_flags = [] if extra_flags is None else extra_flags

  model_dir = tempfile.mkdtemp(dir=tmp_root)

  args = [sys.argv[0], "--model_dir", model_dir] + extra_flags

  if synth:
    args.append("--use_synthetic_data")

  if train_epochs is not None:
    args.extend(["--train_epochs", str(train_epochs)])

  if epochs_between_evals is not None:
    args.extend(["--epochs_between_evals", str(epochs_between_evals)])

  try:
    flags_core.parse_flags(argv=args)
    main(flags.FLAGS)
  finally:
    if os.path.exists(model_dir):
      shutil.rmtree(model_dir)