Moving Keras ResNet models to `official/vision/image_classification` and...

Moving Keras ResNet models to `official/vision/image_classification` and benchmarks to `official/benchmark`.

PiperOrigin-RevId: 264268533

official/resnet/keras/keras_cifar_benchmark.py → official/benchmark/keras_cifar_benchmark.py

@@ -22,8 +22,8 @@ import time
 from absl import flags
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
-from official.resnet.keras import keras_benchmark
-from official.resnet.keras import keras_cifar_main
+from official.benchmark import keras_benchmark
+from official.vision.image_classification import resnet_cifar_main
 
 MIN_TOP_1_ACCURACY = 0.929
 MAX_TOP_1_ACCURACY = 0.938
@@ -47,7 +47,7 @@ class Resnet56KerasAccuracy(keras_benchmark.KerasBenchmark):
     """
 
     self.data_dir = os.path.join(root_data_dir, CIFAR_DATA_DIR_NAME)
-    flag_methods = [keras_cifar_main.define_cifar_flags]
+    flag_methods = [resnet_cifar_main.define_cifar_flags]
 
     super(Resnet56KerasAccuracy, self).__init__(
         output_dir=output_dir, flag_methods=flag_methods)
@@ -199,7 +199,7 @@ class Resnet56KerasAccuracy(keras_benchmark.KerasBenchmark):
 
   def _run_and_report_benchmark(self):
     start_time_sec = time.time()
-    stats = keras_cifar_main.run(FLAGS)
+    stats = resnet_cifar_main.run(FLAGS)
     wall_time_sec = time.time() - start_time_sec
 
     super(Resnet56KerasAccuracy, self)._report_benchmark(
@@ -215,7 +215,7 @@ class Resnet56KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
   """Short performance tests for ResNet56 via Keras and CIFAR-10."""
 
   def __init__(self, output_dir=None, default_flags=None):
-    flag_methods = [keras_cifar_main.define_cifar_flags]
+    flag_methods = [resnet_cifar_main.define_cifar_flags]
 
     super(Resnet56KerasBenchmarkBase, self).__init__(
         output_dir=output_dir,
@@ -224,7 +224,7 @@ class Resnet56KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
 
   def _run_and_report_benchmark(self):
     start_time_sec = time.time()
-    stats = keras_cifar_main.run(FLAGS)
+    stats = resnet_cifar_main.run(FLAGS)
     wall_time_sec = time.time() - start_time_sec
 
     super(Resnet56KerasBenchmarkBase, self)._report_benchmark(

official/resnet/keras/keras_imagenet_benchmark.py → official/benchmark/keras_imagenet_benchmark.py

@@ -21,8 +21,8 @@ import time
 from absl import flags
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
-from official.resnet.keras import keras_benchmark
-from official.resnet.keras import keras_imagenet_main
+from official.benchmark import keras_benchmark
+from official.vision.image_classification import resnet_imagenet_main
 
 MIN_TOP_1_ACCURACY = 0.76
 MAX_TOP_1_ACCURACY = 0.77
@@ -44,7 +44,7 @@ class Resnet50KerasAccuracy(keras_benchmark.KerasBenchmark):
                 named arguments before updating the constructor.
     """
 
-    flag_methods = [keras_imagenet_main.define_imagenet_keras_flags]
+    flag_methods = [resnet_imagenet_main.define_imagenet_keras_flags]
 
     self.data_dir = os.path.join(root_data_dir, 'imagenet')
     super(Resnet50KerasAccuracy, self).__init__(
@@ -158,7 +158,7 @@ class Resnet50KerasAccuracy(keras_benchmark.KerasBenchmark):
                                 top_1_min=MIN_TOP_1_ACCURACY,
                                 top_1_max=MAX_TOP_1_ACCURACY):
     start_time_sec = time.time()
-    stats = keras_imagenet_main.run(flags.FLAGS)
+    stats = resnet_imagenet_main.run(flags.FLAGS)
     wall_time_sec = time.time() - start_time_sec
 
     super(Resnet50KerasAccuracy, self)._report_benchmark(
@@ -177,7 +177,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
   """Resnet50 benchmarks."""
 
   def __init__(self, output_dir=None, default_flags=None):
-    flag_methods = [keras_imagenet_main.define_imagenet_keras_flags]
+    flag_methods = [resnet_imagenet_main.define_imagenet_keras_flags]
 
     super(Resnet50KerasBenchmarkBase, self).__init__(
         output_dir=output_dir,
@@ -186,7 +186,7 @@ class Resnet50KerasBenchmarkBase(keras_benchmark.KerasBenchmark):
 
   def _run_and_report_benchmark(self):
     start_time_sec = time.time()
-    stats = keras_imagenet_main.run(FLAGS)
+    stats = resnet_imagenet_main.run(FLAGS)
     wall_time_sec = time.time() - start_time_sec
     # Number of logged step time entries that are excluded in performance
     # report. We keep results from last 100 batches in this case.
@@ -779,7 +779,7 @@ class TrivialKerasBenchmarkReal(keras_benchmark.KerasBenchmark):
   """Trivial model with real data benchmark tests."""
 
   def __init__(self, output_dir=None, root_data_dir=None, **kwargs):
-    flag_methods = [keras_imagenet_main.define_imagenet_keras_flags]
+    flag_methods = [resnet_imagenet_main.define_imagenet_keras_flags]
 
     def_flags = {}
     def_flags['use_trivial_model'] = True
@@ -799,7 +799,7 @@ class TrivialKerasBenchmarkReal(keras_benchmark.KerasBenchmark):
 
   def _run_and_report_benchmark(self):
     start_time_sec = time.time()
-    stats = keras_imagenet_main.run(FLAGS)
+    stats = resnet_imagenet_main.run(FLAGS)
     wall_time_sec = time.time() - start_time_sec
 
     super(TrivialKerasBenchmarkReal, self)._report_benchmark(

official/resnet/README.md

 # ResNet in TensorFlow
 
 * For the Keras version of the ResNet model, see
-  [`official/resnet/keras`](keras).
+  [`official/vision/image_classification`](../vision/image_classification).
 * For the Keras custom training loop version, see
   [`official/resnet/ctl`](ctl).
-* For the Estimator version, see [`official/r1/resnet`](../r1/resnet).
\ No newline at end of file
+* For the Estimator version, see [`official/r1/resnet`](../r1/resnet).

official/resnet/__init__.py

-# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2019 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.

official/resnet/keras/__init__.py

+# Copyright 2019 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.
+# ==============================================================================
+
+"""Bring in the shared Keras ResNet modules into this module.
+
+The TensorFlow official Keras models are moved under
+    official/vision/image_classification
+In order to be backward compatible with models that directly import its modules,
+we import the Keras ResNet modules under official.resnet.keras.
+
+New TF models should not depend on modules directly under this path.
+"""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from official.vision.image_classification import cifar_preprocessing
+from official.vision.image_classification import common as keras_common
+from official.vision.image_classification import imagenet_preprocessing
+from official.vision.image_classification import resnet_cifar_main as keras_cifar_main
+from official.vision.image_classification import resnet_cifar_model
+from official.vision.image_classification import resnet_imagenet_main as keras_imagenet_main
+from official.vision.image_classification import resnet_model
+
+del absolute_import
+del division
+del print_function

official/resnet/keras/README.md → official/vision/image_classification/README.md

-This folder contains the Keras implementation of the ResNet models. For more 
-information about the models, please refer to this [README file](../README.md).
+This folder contains the Keras implementation of the ResNet models. For more
+information about the models, please refer to this [README file](../../README.md).
 
-Similar to the [estimator implementation](/official/resnet), the Keras 
+Similar to the [estimator implementation](../../r1/resnet), the Keras
 implementation has code for both CIFAR-10 data and ImageNet data. The CIFAR-10
-version uses a ResNet56 model implemented in 
-[`resnet_cifar_model.py`](./resnet_cifar_model.py), and the ImageNet version 
+version uses a ResNet56 model implemented in
+[`resnet_cifar_model.py`](./resnet_cifar_model.py), and the ImageNet version
 uses a ResNet50 model implemented in [`resnet_model.py`](./resnet_model.py).
 
-To use 
-either dataset, make sure that you have the latest version of TensorFlow 
-installed and 
+To use
+either dataset, make sure that you have the latest version of TensorFlow
+installed and
 [add the models folder to your Python path](/official/#running-the-models),
-otherwise you may encounter an error like `ImportError: No module named 
+otherwise you may encounter an error like `ImportError: No module named
 official.resnet`.
 
 ## CIFAR-10
@@ -36,7 +36,7 @@ python keras_cifar_main.py --data_dir=/path/to/cifar
 
 ## ImageNet
 
-Download the ImageNet dataset and convert it to TFRecord format. 
+Download the ImageNet dataset and convert it to TFRecord format.
 The following [script](https://github.com/tensorflow/tpu/blob/master/tools/datasets/imagenet_to_gcs.py)
 and [README](https://github.com/tensorflow/tpu/tree/master/tools/datasets#imagenet_to_gcspy)
 provide a few options.
@@ -56,17 +56,17 @@ python keras_imagenet_main.py --data_dir=/path/to/imagenet
 
 There are more flag options you can specify. Here are some examples:
 
-- `--use_synthetic_data`: when set to true, synthetic data, rather than real 
+- `--use_synthetic_data`: when set to true, synthetic data, rather than real
 data, are used;
 - `--batch_size`: the batch size used for the model;
 - `--model_dir`: the directory to save the model checkpoint;
 - `--train_epochs`: number of epoches to run for training the model;
 - `--train_steps`: number of steps to run for training the model. We now only
 support a number that is smaller than the number of batches in an epoch.
-- `--skip_eval`: when set to true, evaluation as well as validation during 
+- `--skip_eval`: when set to true, evaluation as well as validation during
 training is skipped
 
-For example, this is a typical command line to run with ImageNet data with 
+For example, this is a typical command line to run with ImageNet data with
 batch size 128 per GPU:
 
 ```bash
@@ -82,19 +82,19 @@ python -m keras_imagenet_main \
 See [`keras_common.py`](keras_common.py) for full list of options.
 
 ## Using multiple GPUs
-You can train these models on multiple GPUs using `tf.distribute.Strategy` API. 
-You can read more about them in this 
+You can train these models on multiple GPUs using `tf.distribute.Strategy` API.
+You can read more about them in this
 [guide](https://www.tensorflow.org/guide/distribute_strategy).
 
-In this example, we have made it easier to use is with just a command line flag 
-`--num_gpus`. By default this flag is 1 if TensorFlow is compiled with CUDA, 
+In this example, we have made it easier to use is with just a command line flag
+`--num_gpus`. By default this flag is 1 if TensorFlow is compiled with CUDA,
 and 0 otherwise.
 
 - --num_gpus=0: Uses tf.distribute.OneDeviceStrategy with CPU as the device.
 - --num_gpus=1: Uses tf.distribute.OneDeviceStrategy with GPU as the device.
-- --num_gpus=2+: Uses tf.distribute.MirroredStrategy to run synchronous 
+- --num_gpus=2+: Uses tf.distribute.MirroredStrategy to run synchronous
 distributed training across the GPUs.
 
-If you wish to run without `tf.distribute.Strategy`, you can do so by setting 
+If you wish to run without `tf.distribute.Strategy`, you can do so by setting
 `--distribution_strategy=off`.
 

official/resnet/keras/cifar_preprocessing.py → official/vision/image_classification/cifar_preprocessing.py

@@ -22,7 +22,7 @@ import os
 from absl import logging
 import tensorflow as tf
 
-from official.resnet.keras import imagenet_preprocessing
+from official.vision.image_classification import imagenet_preprocessing
 
 HEIGHT = 32
 WIDTH = 32

official/resnet/keras/keras_common.py → official/vision/image_classification/common.py

@@ -20,17 +20,13 @@ from __future__ import print_function
 import multiprocessing
 import os
 
-import numpy as np
-
-# pylint: disable=g-bad-import-order
 from absl import flags
+import numpy as np
 import tensorflow as tf
 
+from tensorflow.python.keras.optimizer_v2 import gradient_descent as gradient_descent_v2
 from official.utils.flags import core as flags_core
 from official.utils.misc import keras_utils
-# pylint: disable=ungrouped-imports
-from tensorflow.python.keras.optimizer_v2 import (gradient_descent as
-                                                  gradient_descent_v2)
 
 FLAGS = flags.FLAGS
 BASE_LEARNING_RATE = 0.1  # This matches Jing's version.

official/resnet/keras/keras_common_test.py → official/vision/image_classification/common_test.py

@@ -12,21 +12,21 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""Tests for the keras_common module."""
+"""Tests for the common module."""
 from __future__ import absolute_import
 from __future__ import print_function
 
 from mock import Mock
 import numpy as np
-import tensorflow as tf  # pylint: disable=g-bad-import-order
-from tensorflow.python.platform import googletest
+import tensorflow as tf
 
-from official.resnet.keras import keras_common
+from tensorflow.python.platform import googletest
 from official.utils.misc import keras_utils
+from official.vision.image_classification import common
 
 
 class KerasCommonTests(tf.test.TestCase):
-  """Tests for keras_common."""
+  """Tests for common."""
 
   @classmethod
   def setUpClass(cls):  # pylint: disable=invalid-name
@@ -42,7 +42,7 @@ class KerasCommonTests(tf.test.TestCase):
                         keras_utils.BatchTimestamp(1, 2),
                         keras_utils.BatchTimestamp(2, 3)]
     th.train_finish_time = 12345
-    stats = keras_common.build_stats(history, eval_output, [th])
+    stats = common.build_stats(history, eval_output, [th])
 
     self.assertEqual(1.145, stats['loss'])
     self.assertEqual(.99988, stats['training_accuracy_top_1'])
@@ -57,7 +57,7 @@ class KerasCommonTests(tf.test.TestCase):
 
     history = self._build_history(1.145, cat_accuracy_sparse=.99988)
     eval_output = self._build_eval_output(.928, 1.9844)
-    stats = keras_common.build_stats(history, eval_output, None)
+    stats = common.build_stats(history, eval_output, None)
 
     self.assertEqual(1.145, stats['loss'])
     self.assertEqual(.99988, stats['training_accuracy_top_1'])

official/resnet/keras/keras_cifar_main.py → official/vision/image_classification/resnet_cifar_main.py

@@ -22,13 +22,13 @@ from absl import app as absl_app
 from absl import flags
 import tensorflow as tf
 
-from official.resnet.keras import cifar_preprocessing
-from official.resnet.keras import keras_common
-from official.resnet.keras import resnet_cifar_model
 from official.utils.flags import core as flags_core
 from official.utils.logs import logger
 from official.utils.misc import distribution_utils
 from official.utils.misc import keras_utils
+from official.vision.image_classification import cifar_preprocessing
+from official.vision.image_classification import common
+from official.vision.image_classification import resnet_cifar_model
 
 
 LR_SCHEDULE = [  # (multiplier, epoch to start) tuples
@@ -55,7 +55,7 @@ def learning_rate_schedule(current_epoch,
     Adjusted learning rate.
   """
   del current_batch, batches_per_epoch  # not used
-  initial_learning_rate = keras_common.BASE_LEARNING_RATE * batch_size / 128
+  initial_learning_rate = common.BASE_LEARNING_RATE * batch_size / 128
   learning_rate = initial_learning_rate
   for mult, start_epoch in LR_SCHEDULE:
     if current_epoch >= start_epoch:
@@ -83,8 +83,8 @@ def run(flags_obj):
 
   # Execute flag override logic for better model performance
   if flags_obj.tf_gpu_thread_mode:
-    keras_common.set_gpu_thread_mode_and_count(flags_obj)
-  keras_common.set_cudnn_batchnorm_mode()
+    common.set_gpu_thread_mode_and_count(flags_obj)
+  common.set_cudnn_batchnorm_mode()
 
   dtype = flags_core.get_tf_dtype(flags_obj)
   if dtype == 'fp16':
@@ -116,7 +116,7 @@ def run(flags_obj):
 
   if flags_obj.use_synthetic_data:
     distribution_utils.set_up_synthetic_data()
-    input_fn = keras_common.get_synth_input_fn(
+    input_fn = common.get_synth_input_fn(
         height=cifar_preprocessing.HEIGHT,
         width=cifar_preprocessing.WIDTH,
         num_channels=cifar_preprocessing.NUM_CHANNELS,
@@ -150,7 +150,7 @@ def run(flags_obj):
         parse_record_fn=cifar_preprocessing.parse_record)
 
   with strategy_scope:
-    optimizer = keras_common.get_optimizer()
+    optimizer = common.get_optimizer()
     model = resnet_cifar_model.resnet56(classes=cifar_preprocessing.NUM_CLASSES)
 
     # TODO(b/138957587): Remove when force_v2_in_keras_compile is on longer
@@ -171,7 +171,7 @@ def run(flags_obj):
                    if flags_obj.report_accuracy_metrics else None),
           run_eagerly=flags_obj.run_eagerly)
 
-  callbacks = keras_common.get_callbacks(
+  callbacks = common.get_callbacks(
       learning_rate_schedule, cifar_preprocessing.NUM_IMAGES['train'])
 
   train_steps = cifar_preprocessing.NUM_IMAGES['train'] // flags_obj.batch_size
@@ -216,12 +216,12 @@ def run(flags_obj):
   if not strategy and flags_obj.explicit_gpu_placement:
     no_dist_strat_device.__exit__()
 
-  stats = keras_common.build_stats(history, eval_output, callbacks)
+  stats = common.build_stats(history, eval_output, callbacks)
   return stats
 
 
 def define_cifar_flags():
-  keras_common.define_keras_flags(dynamic_loss_scale=False)
+  common.define_keras_flags(dynamic_loss_scale=False)
 
   flags_core.set_defaults(data_dir='/tmp/cifar10_data/cifar-10-batches-bin',
                           model_dir='/tmp/cifar10_model',

official/resnet/keras/keras_cifar_test.py → official/vision/image_classification/resnet_cifar_test.py

@@ -18,17 +18,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from tempfile import mkdtemp
+import tempfile
+
 import tensorflow as tf
 
-from official.resnet.keras import cifar_preprocessing
-from official.resnet.keras import keras_cifar_main
-from official.resnet.keras import keras_common
-from official.utils.misc import keras_utils
-from official.utils.testing import integration
-# pylint: disable=ungrouped-imports
 from tensorflow.python.eager import context
 from tensorflow.python.platform import googletest
+from official.utils.misc import keras_utils
+from official.utils.testing import integration
+from official.vision.image_classification import cifar_preprocessing
+from official.vision.image_classification import resnet_cifar_main
 
 
 class KerasCifarTest(googletest.TestCase):
@@ -43,13 +42,13 @@ class KerasCifarTest(googletest.TestCase):
 
   def get_temp_dir(self):
     if not self._tempdir:
-      self._tempdir = mkdtemp(dir=googletest.GetTempDir())
+      self._tempdir = tempfile.mkdtemp(dir=googletest.GetTempDir())
     return self._tempdir
 
   @classmethod
   def setUpClass(cls):  # pylint: disable=invalid-name
     super(KerasCifarTest, cls).setUpClass()
-    keras_cifar_main.define_cifar_flags()
+    resnet_cifar_main.define_cifar_flags()
 
   def setUp(self):
     super(KerasCifarTest, self).setUp()
@@ -72,7 +71,7 @@ class KerasCifarTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_cifar_main.run,
+        main=resnet_cifar_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -88,7 +87,7 @@ class KerasCifarTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_cifar_main.run,
+        main=resnet_cifar_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -112,7 +111,7 @@ class KerasCifarTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_cifar_main.run,
+        main=resnet_cifar_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -134,7 +133,7 @@ class KerasCifarTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_cifar_main.run,
+        main=resnet_cifar_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -157,7 +156,7 @@ class KerasCifarTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_cifar_main.run,
+        main=resnet_cifar_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -178,7 +177,7 @@ class KerasCifarTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_cifar_main.run,
+        main=resnet_cifar_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )

official/resnet/keras/keras_imagenet_main.py → official/vision/image_classification/resnet_imagenet_main.py

@@ -21,17 +21,17 @@ from __future__ import print_function
 from absl import app as absl_app
 from absl import flags
 from absl import logging
-import tensorflow as tf  # pylint: disable=g-bad-import-order
+import tensorflow as tf
 
-from official.resnet.keras import imagenet_preprocessing
-from official.resnet.keras import keras_common
-from official.resnet.keras import resnet_model
-from official.resnet.keras import trivial_model
 from official.utils.flags import core as flags_core
 from official.utils.logs import logger
 from official.utils.misc import distribution_utils
 from official.utils.misc import keras_utils
 from official.utils.misc import model_helpers
+from official.vision.image_classification import common
+from official.vision.image_classification import imagenet_preprocessing
+from official.vision.image_classification import resnet_model
+from official.vision.image_classification import trivial_model
 
 
 LR_SCHEDULE = [    # (multiplier, epoch to start) tuples
@@ -57,7 +57,7 @@ def learning_rate_schedule(current_epoch,
   Returns:
     Adjusted learning rate.
   """
-  initial_lr = keras_common.BASE_LEARNING_RATE * batch_size / 256
+  initial_lr = common.BASE_LEARNING_RATE * batch_size / 256
   epoch = current_epoch + float(current_batch) / batches_per_epoch
   warmup_lr_multiplier, warmup_end_epoch = LR_SCHEDULE[0]
   if epoch < warmup_end_epoch:
@@ -89,10 +89,10 @@ def run(flags_obj):
 
   # Execute flag override logic for better model performance
   if flags_obj.tf_gpu_thread_mode:
-    keras_common.set_gpu_thread_mode_and_count(flags_obj)
+    common.set_gpu_thread_mode_and_count(flags_obj)
   if flags_obj.data_delay_prefetch:
-    keras_common.data_delay_prefetch()
-  keras_common.set_cudnn_batchnorm_mode()
+    common.data_delay_prefetch()
+  common.set_cudnn_batchnorm_mode()
 
   dtype = flags_core.get_tf_dtype(flags_obj)
   if dtype == 'float16':
@@ -129,7 +129,7 @@ def run(flags_obj):
   # pylint: disable=protected-access
   if flags_obj.use_synthetic_data:
     distribution_utils.set_up_synthetic_data()
-    input_fn = keras_common.get_synth_input_fn(
+    input_fn = common.get_synth_input_fn(
         height=imagenet_preprocessing.DEFAULT_IMAGE_SIZE,
         width=imagenet_preprocessing.DEFAULT_IMAGE_SIZE,
         num_channels=imagenet_preprocessing.NUM_CHANNELS,
@@ -169,7 +169,7 @@ def run(flags_obj):
 
   lr_schedule = 0.1
   if flags_obj.use_tensor_lr:
-    lr_schedule = keras_common.PiecewiseConstantDecayWithWarmup(
+    lr_schedule = common.PiecewiseConstantDecayWithWarmup(
         batch_size=flags_obj.batch_size,
         epoch_size=imagenet_preprocessing.NUM_IMAGES['train'],
         warmup_epochs=LR_SCHEDULE[0][1],
@@ -178,7 +178,7 @@ def run(flags_obj):
         compute_lr_on_cpu=True)
 
   with strategy_scope:
-    optimizer = keras_common.get_optimizer(lr_schedule)
+    optimizer = common.get_optimizer(lr_schedule)
     if dtype == 'float16':
       # TODO(reedwm): Remove manually wrapping optimizer once mixed precision
       # can be enabled with a single line of code.
@@ -211,7 +211,7 @@ def run(flags_obj):
                    if flags_obj.report_accuracy_metrics else None),
           run_eagerly=flags_obj.run_eagerly)
 
-  callbacks = keras_common.get_callbacks(
+  callbacks = common.get_callbacks(
       learning_rate_schedule, imagenet_preprocessing.NUM_IMAGES['train'])
 
   train_steps = (
@@ -261,14 +261,14 @@ def run(flags_obj):
   if not strategy and flags_obj.explicit_gpu_placement:
     no_dist_strat_device.__exit__()
 
-  stats = keras_common.build_stats(history, eval_output, callbacks)
+  stats = common.build_stats(history, eval_output, callbacks)
   return stats
 
 
 def define_imagenet_keras_flags():
-  keras_common.define_keras_flags()
+  common.define_keras_flags()
   flags_core.set_defaults(train_epochs=90)
-  flags.adopt_module_key_flags(keras_common)
+  flags.adopt_module_key_flags(common)
 
 
 def main(_):

official/resnet/keras/keras_imagenet_test.py → official/vision/image_classification/resnet_imagenet_test.py

@@ -18,16 +18,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from tempfile import mkdtemp
+import tempfile
+
 import tensorflow as tf
 
-from official.resnet.keras import imagenet_preprocessing
-from official.resnet.keras import keras_imagenet_main
-from official.utils.misc import keras_utils
-from official.utils.testing import integration
-# pylint: disable=ungrouped-imports
 from tensorflow.python.eager import context
 from tensorflow.python.platform import googletest
+from official.utils.misc import keras_utils
+from official.utils.testing import integration
+from official.vision.image_classification import imagenet_preprocessing
+from official.vision.image_classification import resnet_imagenet_main
 
 
 class KerasImagenetTest(googletest.TestCase):
@@ -42,13 +42,13 @@ class KerasImagenetTest(googletest.TestCase):
 
   def get_temp_dir(self):
     if not self._tempdir:
-      self._tempdir = mkdtemp(dir=googletest.GetTempDir())
+      self._tempdir = tempfile.mkdtemp(dir=googletest.GetTempDir())
     return self._tempdir
 
   @classmethod
   def setUpClass(cls):  # pylint: disable=invalid-name
     super(KerasImagenetTest, cls).setUpClass()
-    keras_imagenet_main.define_imagenet_keras_flags()
+    resnet_imagenet_main.define_imagenet_keras_flags()
 
   def setUp(self):
     super(KerasImagenetTest, self).setUp()
@@ -71,7 +71,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -87,7 +87,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -111,7 +111,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -133,7 +133,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -156,7 +156,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -180,7 +180,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -204,7 +204,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -229,7 +229,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -250,7 +250,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )
@@ -272,7 +272,7 @@ class KerasImagenetTest(googletest.TestCase):
     extra_flags = extra_flags + self._extra_flags
 
     integration.run_synthetic(
-        main=keras_imagenet_main.run,
+        main=resnet_imagenet_main.run,
         tmp_root=self.get_temp_dir(),
         extra_flags=extra_flags
     )