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# Copyright 2018 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.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
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)
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