keras_cifar_benchmark.py 3.84 KB
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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.
# ==============================================================================
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"""Executes Keras benchmarks and accuracy tests."""
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from __future__ import absolute_import
from __future__ import division
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from __future__ import print_function

import os

from absl import flags
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from absl.testing import flagsaver
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import tensorflow as tf  # pylint: disable=g-bad-import-order

from official.resnet import cifar10_main as cifar_main
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from official.resnet.keras import keras_cifar_main
from official.resnet.keras import keras_common

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DATA_DIR = '/data/cifar10_data/'


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class KerasCifar10BenchmarkTests(object):
  """Benchmarks and accuracy tests for KerasCifar10."""

  local_flags = None

  def __init__(self, output_dir=None):
    self.oss_report_object = None
    self.output_dir = output_dir
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  def keras_resnet56_1_gpu(self):
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    """Test keras based model with Keras fit and distribution strategies."""
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    self._setup()
    flags.FLAGS.num_gpus = 1
    flags.FLAGS.data_dir = DATA_DIR
    flags.FLAGS.batch_size = 128
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    flags.FLAGS.train_epochs = 182
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    flags.FLAGS.model_dir = self._get_model_dir('keras_resnet56_1_gpu')
    flags.FLAGS.resnet_size = 56
    flags.FLAGS.dtype = 'fp32'
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    stats = keras_cifar_main.run(flags.FLAGS)
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    self._fill_report_object(stats)
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  def keras_resnet56_4_gpu(self):
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    """Test keras based model with Keras fit and distribution strategies."""
    self._setup()
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    flags.FLAGS.num_gpus = 4
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    flags.FLAGS.data_dir = self._get_model_dir('keras_resnet56_4_gpu')
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    flags.FLAGS.batch_size = 128
    flags.FLAGS.train_epochs = 182
    flags.FLAGS.model_dir = ''
    flags.FLAGS.resnet_size = 56
    flags.FLAGS.dtype = 'fp32'
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    stats = keras_cifar_main.run(flags.FLAGS)
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    self._fill_report_object(stats)
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  def keras_resnet56_no_dist_strat_1_gpu(self):
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    """Test keras based model with Keras fit but not distribution strategies."""
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    self._setup()
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    flags.FLAGS.turn_off_distribution_strategy = True
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    flags.FLAGS.num_gpus = 1
    flags.FLAGS.data_dir = DATA_DIR
    flags.FLAGS.batch_size = 128
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    flags.FLAGS.train_epochs = 182
    flags.FLAGS.model_dir = self._get_model_dir(
        'keras_resnet56_no_dist_strat_1_gpu')
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    flags.FLAGS.resnet_size = 56
    flags.FLAGS.dtype = 'fp32'
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    stats = keras_cifar_main.run(flags.FLAGS)
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    self._fill_report_object(stats)

  def _fill_report_object(self, stats):
    if self.oss_report_object:
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      self.oss_report_object.top_1 = stats['accuracy_top_1']
      self.oss_report_object.add_other_quality(stats['training_accuracy_top_1'],
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                                               'top_1_train_accuracy')
    else:
      raise ValueError('oss_report_object has not been set.')
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  def _get_model_dir(self, folder_name):
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    return os.path.join(self.output_dir, folder_name)
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  def _setup(self):
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    """Setups up and resets flags before each test."""
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    tf.logging.set_verbosity(tf.logging.DEBUG)
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    if KerasCifar10BenchmarkTests.local_flags is None:
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      keras_common.define_keras_flags()
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      cifar_main.define_cifar_flags()
      # Loads flags to get defaults to then override.
      flags.FLAGS(['foo'])
      saved_flag_values = flagsaver.save_flag_values()
      KerasCifar10BenchmarkTests.local_flags = saved_flag_values
      return
    flagsaver.restore_flag_values(KerasCifar10BenchmarkTests.local_flags)