Release MobileDet code and model, and require tf_slim installation for OD API. (#8562)

* Merged commit includes the following changes:
311933687  by Sergio Guadarrama:

    Removes spurios use of tf.compat.v2, which results in spurious tf.compat.v1.compat.v2. Adds basic test to nasnet_utils.
    Replaces all remaining import tensorflow as tf with import tensorflow.compat.v1 as tf

--
311766063  by Sergio Guadarrama:

    Removes explicit tf.compat.v1 in all call sites (we already import tf.compat.v1, so this code was  doing tf.compat.v1.compat.v1). The existing code worked in latest version of tensorflow, 2.2, (and 1.15) but not in 1.14 or in 2.0.0a, this CL fixes it.

--
311624958  by Sergio Guadarrama:

    Updates README that doesn't render properly in github documentation

--
310980959  by Sergio Guadarrama:

    Moves research_models/slim off tf.contrib.slim/layers/framework to tf_slim

--
310263156  by Sergio Guadarrama:

    Adds model breakdown for MobilenetV3

--
308640516  by Sergio Guadarrama:

    Internal change

308244396  by Sergio Guadarrama:

    GroupNormalization support for MobilenetV3.

--
307475800  by Sergio Guadarrama:

    Internal change

--
302077708  by Sergio Guadarrama:

    Remove `disable_tf2` behavior from slim py_library targets

--
301208453  by Sergio Guadarrama:

    Automated refactoring to make code Python 3 compatible.

--
300816672  by Sergio Guadarrama:

    Internal change

299433840  by Sergio Guadarrama:

    Internal change

299221609  by Sergio Guadarrama:

    Explicitly disable Tensorflow v2 behaviors for all TF1.x binaries and tests

--
299179617  by Sergio Guadarrama:

    Internal change

299040784  by Sergio Guadarrama:

    Internal change

299036699  by Sergio Guadarrama:

    Internal change

298736510  by Sergio Guadarrama:

    Internal change

298732599  by Sergio Guadarrama:

    Internal change

298729507  by Sergio Guadarrama:

    Internal change

298253328  by Sergio Guadarrama:

    Internal change

297788346  by Sergio Guadarrama:

    Internal change

297785278  by Sergio Guadarrama:

    Internal change

297783127  by Sergio Guadarrama:

    Internal change

297725870  by Sergio Guadarrama:

    Internal change

297721811  by Sergio Guadarrama:

    Internal change

297711347  by Sergio Guadarrama:

    Internal change

297708059  by Sergio Guadarrama:

    Internal change

297701831  by Sergio Guadarrama:

    Internal change

297700038  by Sergio Guadarrama:

    Internal change

297670468  by Sergio Guadarrama:

    Internal change.

--
297350326  by Sergio Guadarrama:

    Explicitly replace "import tensorflow" with "tensorflow.compat.v1" for TF2.x migration

--
297201668  by Sergio Guadarrama:

    Explicitly replace "import tensorflow" with "tensorflow.compat.v1" for TF2.x migration

--
294483372  by Sergio Guadarrama:

    Internal change

PiperOrigin-RevId: 311933687

* Merged commit includes the following changes:
312578615  by Menglong Zhu:

    Modify the LSTM feature extractors to be python 3 compatible.

--
311264357  by Menglong Zhu:

    Removes contrib.slim

--
308957207  by Menglong Zhu:

    Automated refactoring to make code Python 3 compatible.

--
306976470  by yongzhe:

    Internal change

306777559  by Menglong Zhu:

    Internal change

--
299232507  by lzyuan:

    Internal update.

--
299221735  by lzyuan:

    Add small epsilon on max_range for quantize_op to prevent range collapse.

--

PiperOrigin-RevId: 312578615

* Merged commit includes the following changes:
310447280  by lzc:

    Internal changes.

--

PiperOrigin-RevId: 310447280
Co-authored-by: Sergio Guadarrama <sguada@google.com>
Co-authored-by: Menglong Zhu <menglong@google.com>

research/object_detection/utils/visualization_utils.py

@@ -36,7 +36,7 @@ import PIL.ImageFont as ImageFont
 import six
 from six.moves import range
 from six.moves import zip
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 from object_detection.core import keypoint_ops
 from object_detection.core import standard_fields as fields

research/object_detection/utils/visualization_utils_test.py

@@ -25,15 +25,28 @@ import numpy as np
 import PIL.Image as Image
 import six
 from six.moves import range
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 from object_detection.core import standard_fields as fields
+from object_detection.utils import test_case
 from object_detection.utils import visualization_utils
 
 _TESTDATA_PATH = 'object_detection/test_images'
 
 
-class VisualizationUtilsTest(tf.test.TestCase):
+def get_iterator_next_for_testing(dataset, is_tf2):
+
+  # In TF2, lookup tables are not supported in one shot iterators, but
+  # initialization is implicit.
+  if is_tf2:
+    return dataset.make_initializable_iterator().get_next()
+  # In TF1, we use one shot iterator because it does not require running
+  # a separate init op.
+  else:
+    return dataset.make_one_shot_iterator().get_next()
+
+
+class VisualizationUtilsTest(test_case.TestCase):
 
   def test_get_prime_multiplier_for_color_randomness(self):
     # Show that default multipler is not 1 and does not divide the total number
@@ -151,13 +164,12 @@ class VisualizationUtilsTest(tf.test.TestCase):
   def test_draw_bounding_boxes_on_image_tensors(self):
     """Tests that bounding box utility produces reasonable results."""
     category_index = {1: {'id': 1, 'name': 'dog'}, 2: {'id': 2, 'name': 'cat'}}
-
     fname = os.path.join(_TESTDATA_PATH, 'image1.jpg')
     image_np = np.array(Image.open(fname))
     images_np = np.stack((image_np, image_np), axis=0)
     original_image_shape = [[636, 512], [636, 512]]
 
-    with tf.Graph().as_default():
+    def graph_fn():
       images_tensor = tf.constant(value=images_np, dtype=tf.uint8)
       image_shape = tf.constant(original_image_shape, dtype=tf.int32)
       boxes = tf.constant([[[0.4, 0.25, 0.75, 0.75], [0.5, 0.3, 0.6, 0.9]],
@@ -178,22 +190,20 @@ class VisualizationUtilsTest(tf.test.TestCase):
               keypoints=keypoints,
               min_score_thresh=0.2,
               keypoint_edges=keypoint_edges))
-
-      with self.test_session() as sess:
-        sess.run(tf.global_variables_initializer())
-
-        # Write output images for visualization.
-        images_with_boxes_np = sess.run(images_with_boxes)
-        self.assertEqual(images_np.shape[0], images_with_boxes_np.shape[0])
-        self.assertEqual(images_np.shape[3], images_with_boxes_np.shape[3])
-        self.assertEqual(
-            tuple(original_image_shape[0]), images_with_boxes_np.shape[1:3])
-        for i in range(images_with_boxes_np.shape[0]):
-          img_name = 'image_' + str(i) + '.png'
-          output_file = os.path.join(self.get_temp_dir(), img_name)
-          logging.info('Writing output image %d to %s', i, output_file)
-          image_pil = Image.fromarray(images_with_boxes_np[i, ...])
-          image_pil.save(output_file)
+      return images_with_boxes
+
+    # Write output images for visualization.
+    images_with_boxes_np = self.execute(graph_fn, [])
+    self.assertEqual(images_np.shape[0], images_with_boxes_np.shape[0])
+    self.assertEqual(images_np.shape[3], images_with_boxes_np.shape[3])
+    self.assertEqual(
+        tuple(original_image_shape[0]), images_with_boxes_np.shape[1:3])
+    for i in range(images_with_boxes_np.shape[0]):
+      img_name = 'image_' + str(i) + '.png'
+      output_file = os.path.join(self.get_temp_dir(), img_name)
+      logging.info('Writing output image %d to %s', i, output_file)
+      image_pil = Image.fromarray(images_with_boxes_np[i, ...])
+      image_pil.save(output_file)
 
   def test_draw_bounding_boxes_on_image_tensors_with_track_ids(self):
     """Tests that bounding box utility produces reasonable results."""
@@ -204,7 +214,7 @@ class VisualizationUtilsTest(tf.test.TestCase):
     images_np = np.stack((image_np, image_np), axis=0)
     original_image_shape = [[636, 512], [636, 512]]
 
-    with tf.Graph().as_default():
+    def graph_fn():
       images_tensor = tf.constant(value=images_np, dtype=tf.uint8)
       image_shape = tf.constant(original_image_shape, dtype=tf.int32)
       boxes = tf.constant([[[0.4, 0.25, 0.75, 0.75],
@@ -227,22 +237,20 @@ class VisualizationUtilsTest(tf.test.TestCase):
               true_image_shape=image_shape,
               track_ids=track_ids,
               min_score_thresh=0.2))
-
-      with self.test_session() as sess:
-        sess.run(tf.global_variables_initializer())
-
-        # Write output images for visualization.
-        images_with_boxes_np = sess.run(images_with_boxes)
-        self.assertEqual(images_np.shape[0], images_with_boxes_np.shape[0])
-        self.assertEqual(images_np.shape[3], images_with_boxes_np.shape[3])
-        self.assertEqual(
-            tuple(original_image_shape[0]), images_with_boxes_np.shape[1:3])
-        for i in range(images_with_boxes_np.shape[0]):
-          img_name = 'image_with_track_ids_' + str(i) + '.png'
-          output_file = os.path.join(self.get_temp_dir(), img_name)
-          logging.info('Writing output image %d to %s', i, output_file)
-          image_pil = Image.fromarray(images_with_boxes_np[i, ...])
-          image_pil.save(output_file)
+      return images_with_boxes
+
+    # Write output images for visualization.
+    images_with_boxes_np = self.execute(graph_fn, [])
+    self.assertEqual(images_np.shape[0], images_with_boxes_np.shape[0])
+    self.assertEqual(images_np.shape[3], images_with_boxes_np.shape[3])
+    self.assertEqual(
+        tuple(original_image_shape[0]), images_with_boxes_np.shape[1:3])
+    for i in range(images_with_boxes_np.shape[0]):
+      img_name = 'image_with_track_ids_' + str(i) + '.png'
+      output_file = os.path.join(self.get_temp_dir(), img_name)
+      logging.info('Writing output image %d to %s', i, output_file)
+      image_pil = Image.fromarray(images_with_boxes_np[i, ...])
+      image_pil.save(output_file)
 
   def test_draw_bounding_boxes_on_image_tensors_with_additional_channels(self):
     """Tests the case where input image tensor has more than 3 channels."""
@@ -250,7 +258,7 @@ class VisualizationUtilsTest(tf.test.TestCase):
     image_np = self.create_test_image_with_five_channels()
     images_np = np.stack((image_np, image_np), axis=0)
 
-    with tf.Graph().as_default():
+    def graph_fn():
       images_tensor = tf.constant(value=images_np, dtype=tf.uint8)
       boxes = tf.constant(0, dtype=tf.float32, shape=[2, 0, 4])
       classes = tf.constant(0, dtype=tf.int64, shape=[2, 0])
@@ -264,11 +272,10 @@ class VisualizationUtilsTest(tf.test.TestCase):
               category_index,
               min_score_thresh=0.2))
 
-      with self.test_session() as sess:
-        sess.run(tf.global_variables_initializer())
+      return images_with_boxes
 
-        final_images_np = sess.run(images_with_boxes)
-        self.assertEqual((2, 100, 200, 3), final_images_np.shape)
+    final_images_np = self.execute(graph_fn, [])
+    self.assertEqual((2, 100, 200, 3), final_images_np.shape)
 
   def test_draw_bounding_boxes_on_image_tensors_grayscale(self):
     """Tests the case where input image tensor has one channel."""
@@ -276,7 +283,7 @@ class VisualizationUtilsTest(tf.test.TestCase):
     image_np = self.create_test_grayscale_image()
     images_np = np.stack((image_np, image_np), axis=0)
 
-    with tf.Graph().as_default():
+    def graph_fn():
       images_tensor = tf.constant(value=images_np, dtype=tf.uint8)
       image_shape = tf.constant([[100, 200], [100, 200]], dtype=tf.int32)
       boxes = tf.constant(0, dtype=tf.float32, shape=[2, 0, 4])
@@ -293,11 +300,10 @@ class VisualizationUtilsTest(tf.test.TestCase):
               true_image_shape=image_shape,
               min_score_thresh=0.2))
 
-      with self.test_session() as sess:
-        sess.run(tf.global_variables_initializer())
+      return images_with_boxes
 
-        final_images_np = sess.run(images_with_boxes)
-        self.assertEqual((2, 100, 200, 3), final_images_np.shape)
+    final_images_np = self.execute(graph_fn, [])
+    self.assertEqual((2, 100, 200, 3), final_images_np.shape)
 
   def test_draw_keypoints_on_image(self):
     test_image = self.create_colorful_test_image()
@@ -407,7 +413,7 @@ class VisualizationUtilsTest(tf.test.TestCase):
     heatmap2 = np.asarray([[0, 1],
                            [1, 0]], dtype=np.float)
     heatmaps = np.stack([heatmap1, heatmap2], axis=0)
-    with tf.Graph().as_default():
+    def graph_fn():
       image_tensor = tf.constant(test_image, dtype=tf.uint8)
       image_tensor = tf.expand_dims(image_tensor, axis=0)
       heatmaps_tensor = tf.expand_dims(
@@ -417,34 +423,38 @@ class VisualizationUtilsTest(tf.test.TestCase):
           heatmaps=heatmaps_tensor,
           apply_sigmoid=False)
 
-      with self.test_session() as sess:
-        sess.run(tf.global_variables_initializer())
+      return output_image
 
-        output_image_np = sess.run(output_image)
-      self.assertAllEqual(
-          output_image_np,
-          np.expand_dims(
-              np.array([[[240, 248, 255], [127, 255, 0]],
-                        [[127, 255, 0], [240, 248, 255]]]),
-              axis=0))
+    output_image_np = self.execute(graph_fn, [])
+    self.assertAllEqual(
+        output_image_np,
+        np.expand_dims(
+            np.array([[[240, 248, 255], [127, 255, 0]],
+                      [[127, 255, 0], [240, 248, 255]]]),
+            axis=0))
 
   def test_add_cdf_image_summary(self):
-    values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50]
-    visualization_utils.add_cdf_image_summary(values, 'PositiveAnchorLoss')
-    cdf_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0]
-    with self.test_session():
-      cdf_image_summary.eval()
+    def graph_fn():
+      values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50]
+      visualization_utils.add_cdf_image_summary(values, 'PositiveAnchorLoss')
+      cdf_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0]
+      return cdf_image_summary
+    self.execute(graph_fn, [])
 
   def test_add_hist_image_summary(self):
-    values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50]
-    bins = [0.01 * i for i in range(101)]
-    visualization_utils.add_hist_image_summary(values, bins,
-                                               'ScoresDistribution')
-    hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0]
-    with self.test_session():
-      hist_image_summary.eval()
+    def graph_fn():
+      values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50]
+      bins = [0.01 * i for i in range(101)]
+      visualization_utils.add_hist_image_summary(values, bins,
+                                                 'ScoresDistribution')
+      hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0]
+      return hist_image_summary
+    self.execute(graph_fn, [])
 
   def test_eval_metric_ops(self):
+    if self.is_tf2():
+      self.skipTest('This test is only compatible with Tensorflow 1.X, '
+                    'estimator eval ops are not supported in Tensorflow 2.')
     category_index = {1: {'id': 1, 'name': 'dog'}, 2: {'id': 2, 'name': 'cat'}}
     max_examples_to_draw = 4
     metric_op_base = 'Detections_Left_Groundtruth_Right'

research/object_detection/utils/vrd_evaluation_test.py

@@ -19,7 +19,7 @@ from __future__ import division
 from __future__ import print_function
 
 import numpy as np
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 from object_detection.core import standard_fields
 from object_detection.utils import vrd_evaluation

research/slim/BUILD

@@ -37,8 +37,9 @@ sh_binary(
 py_binary(
     name = "build_imagenet_data",
     srcs = ["datasets/build_imagenet_data.py"],
-    python_version = "PY2",
+    python_version = "PY3",
     deps = [
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         "//third_party/py/six",
         # "//tensorflow",
@@ -59,8 +60,10 @@ py_library(
 py_library(
     name = "download_and_convert_flowers",
     srcs = ["datasets/download_and_convert_flowers.py"],
+    srcs_version = "PY2AND3",
     deps = [
         ":dataset_utils",
+        "//third_party/py/six",
         # "//tensorflow",
     ],
 )
@@ -79,10 +82,12 @@ py_library(
 py_library(
     name = "download_and_convert_visualwakewords_lib",
     srcs = ["datasets/download_and_convert_visualwakewords_lib.py"],
+    srcs_version = "PY2AND3",
     deps = [
         ":dataset_utils",
         "//third_party/py/PIL:pil",
         "//third_party/py/contextlib2",
+        "//third_party/py/six",
         # "//tensorflow",
     ],
 )
@@ -90,6 +95,7 @@ py_library(
 py_library(
     name = "download_and_convert_visualwakewords",
     srcs = ["datasets/download_and_convert_visualwakewords.py"],
+    srcs_version = "PY2AND3",
     deps = [
         ":download_and_convert_visualwakewords_lib",
         # "//tensorflow",
@@ -99,12 +105,13 @@ py_library(
 py_binary(
     name = "download_and_convert_data",
     srcs = ["download_and_convert_data.py"],
-    python_version = "PY2",
+    python_version = "PY3",
     deps = [
         ":download_and_convert_cifar10",
         ":download_and_convert_flowers",
         ":download_and_convert_mnist",
         ":download_and_convert_visualwakewords",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
     ],
 )
@@ -115,7 +122,7 @@ py_library(
     deps = [
         ":dataset_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -125,7 +132,7 @@ py_library(
     deps = [
         ":dataset_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -136,7 +143,7 @@ py_library(
         ":dataset_utils",
         "//third_party/py/six",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -146,7 +153,7 @@ py_library(
     deps = [
         ":dataset_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -156,7 +163,7 @@ py_library(
     deps = [
         ":dataset_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -177,22 +184,20 @@ py_library(
     srcs = ["deployment/model_deploy.py"],
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "model_deploy_test",
     srcs = ["deployment/model_deploy_test.py"],
-    python_version = "PY2",
     srcs_version = "PY2AND3",
     deps = [
         ":model_deploy",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/layers:layers_py",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -201,7 +206,7 @@ py_library(
     srcs = ["preprocessing/cifarnet_preprocessing.py"],
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -219,7 +224,7 @@ py_library(
     srcs = ["preprocessing/lenet_preprocessing.py"],
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -228,7 +233,7 @@ py_library(
     srcs = ["preprocessing/vgg_preprocessing.py"],
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -240,7 +245,7 @@ py_library(
         ":inception_preprocessing",
         ":lenet_preprocessing",
         ":vgg_preprocessing",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -273,20 +278,20 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "alexnet_test",
     size = "medium",
     srcs = ["nets/alexnet_test.py"],
-    python_version = "PY2",
     srcs_version = "PY2AND3",
     deps = [
         ":alexnet",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -295,7 +300,7 @@ py_library(
     srcs = ["nets/cifarnet.py"],
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -306,20 +311,19 @@ py_library(
         # "//numpy",
         "//third_party/py/six",
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/layers:layers_py",
-        # "//tensorflow/contrib/util:util_py",
+        "//third_party/py/tf_slim:slim",
+        # "//tensorflow/python:tensor_util",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "cyclegan_test",
     srcs = ["nets/cyclegan_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":cyclegan",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
     ],
 )
@@ -330,18 +334,18 @@ py_library(
     deps = [
         "//third_party/py/six",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "dcgan_test",
     srcs = ["nets/dcgan_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":dcgan",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         "//third_party/py/six",
         # "//tensorflow",
     ],
@@ -355,20 +359,22 @@ py_library(
         ":i3d_utils",
         ":s3dg",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "i3d_test",
     size = "large",
     srcs = ["nets/i3d_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":i3d",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
+        "//third_party/py/six",
         # "//tensorflow",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -379,8 +385,7 @@ py_library(
     deps = [
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/layers:layers_py",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -403,7 +408,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -414,7 +419,7 @@ py_library(
     deps = [
         ":inception_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -425,7 +430,7 @@ py_library(
     deps = [
         ":inception_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -436,7 +441,7 @@ py_library(
     deps = [
         ":inception_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -447,7 +452,7 @@ py_library(
     deps = [
         ":inception_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -457,22 +462,22 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "inception_v1_test",
     size = "large",
     srcs = ["nets/inception_v1_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":inception",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -484,52 +489,53 @@ py_test(  # py2and3_test
     srcs_version = "PY2AND3",
     deps = [
         ":inception",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "inception_v3_test",
     size = "large",
     srcs = ["nets/inception_v3_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":inception",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "inception_v4_test",
     size = "large",
     srcs = ["nets/inception_v4_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":inception",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "inception_resnet_v2_test",
     size = "large",
     srcs = ["nets/inception_resnet_v2_test.py"],
-    python_version = "PY2",
-    shard_count = 3,
+    shard_count = 4,
     srcs_version = "PY2AND3",
     deps = [
         ":inception",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -538,7 +544,7 @@ py_library(
     srcs = ["nets/lenet.py"],
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -548,8 +554,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/layers:layers_py",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -562,7 +567,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -573,8 +578,7 @@ py_library(
     deps = [
         ":mobilenet_common",
         # "//tensorflow",
-        # "//tensorflow/contrib/layers:layers_py",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -586,7 +590,7 @@ py_library(
         ":mobilenet_common",
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -597,18 +601,22 @@ py_test(  # py2and3_test
     deps = [
         ":mobilenet",
         ":mobilenet_common",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         "//third_party/py/six",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
 py_test(  # py2and3_test
     name = "mobilenet_v3_test",
     srcs = ["nets/mobilenet/mobilenet_v3_test.py"],
+    shard_count = 2,
     srcs_version = "PY2AND3",
     deps = [
         ":mobilenet",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
+        "//testing/pybase:parameterized",
         "//third_party/py/absl/testing:absltest",
         # "//tensorflow",
     ],
@@ -623,46 +631,49 @@ py_library(
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "mobilenet_v1_test",
     size = "large",
     srcs = ["nets/mobilenet_v1_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":mobilenet_v1",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
 py_binary(
     name = "mobilenet_v1_train",
     srcs = ["nets/mobilenet_v1_train.py"],
-    python_version = "PY2",
+    python_version = "PY3",
     deps = [
         ":dataset_factory",
         ":mobilenet_v1",
         ":preprocessing_factory",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
+        "//third_party/py/tf_slim:slim",
         # "//tensorflow/contrib/quantize:quantize_graph",
-        # "//tensorflow/contrib/slim",
     ],
 )
 
 py_binary(
     name = "mobilenet_v1_eval",
     srcs = ["nets/mobilenet_v1_eval.py"],
-    python_version = "PY2",
+    python_version = "PY3",
+    srcs_version = "PY3",
     deps = [
         ":dataset_factory",
         ":mobilenet_v1",
         ":preprocessing_factory",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
+        "//third_party/py/tf_slim:slim",
         # "//tensorflow/contrib/quantize:quantize_graph",
-        # "//tensorflow/contrib/slim",
     ],
 )
 
@@ -672,8 +683,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -684,36 +694,34 @@ py_library(
     deps = [
         ":nasnet_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/layers:layers_py",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
         # "//tensorflow/contrib/training:training_py",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "nasnet_utils_test",
     size = "medium",
     srcs = ["nets/nasnet/nasnet_utils_test.py"],
-    python_version = "PY2",
     srcs_version = "PY2AND3",
     deps = [
         ":nasnet_utils",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "nasnet_test",
     size = "large",
     srcs = ["nets/nasnet/nasnet_test.py"],
-    python_version = "PY2",
     shard_count = 10,
     srcs_version = "PY2AND3",
     deps = [
         ":nasnet",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -725,23 +733,22 @@ py_library(
         ":nasnet",
         ":nasnet_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
         # "//tensorflow/contrib/training:training_py",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "pnasnet_test",
     size = "large",
     srcs = ["nets/nasnet/pnasnet_test.py"],
-    python_version = "PY2",
     shard_count = 4,
     srcs_version = "PY2AND3",
     deps = [
         ":pnasnet",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -751,7 +758,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -762,8 +769,9 @@ py_test(  # py2and3_test
     srcs_version = "PY2AND3",
     deps = [
         ":overfeat",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -773,8 +781,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/layers:layers_py",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -784,8 +791,9 @@ py_test(  # py2and3_test
     srcs_version = "PY2AND3",
     deps = [
         ":pix2pix",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -795,7 +803,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -806,24 +814,24 @@ py_library(
     deps = [
         ":resnet_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "resnet_v1_test",
     size = "medium",
     timeout = "long",
     srcs = ["nets/resnet_v1_test.py"],
-    python_version = "PY2",
     shard_count = 2,
     srcs_version = "PY2AND3",
     deps = [
         ":resnet_utils",
         ":resnet_v1",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -834,23 +842,23 @@ py_library(
     deps = [
         ":resnet_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "resnet_v2_test",
     size = "medium",
     srcs = ["nets/resnet_v2_test.py"],
-    python_version = "PY2",
     shard_count = 2,
     srcs_version = "PY2AND3",
     deps = [
         ":resnet_utils",
         ":resnet_v2",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//numpy",
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -861,20 +869,20 @@ py_library(
     deps = [
         ":i3d_utils",
         # "//tensorflow",
-        # "//tensorflow/contrib/framework:framework_py",
-        # "//tensorflow/contrib/layers:layers_py",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "s3dg_test",
     size = "large",
     srcs = ["nets/s3dg_test.py"],
-    python_version = "PY2",
     shard_count = 3,
     srcs_version = "PY2AND3",
     deps = [
         ":s3dg",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
+        "//third_party/py/six",
         # "//tensorflow",
     ],
 )
@@ -885,7 +893,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -896,8 +904,9 @@ py_test(  # py2and3_test
     srcs_version = "PY2AND3",
     deps = [
         ":vgg",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -906,7 +915,7 @@ py_library(
     srcs = ["nets/nets_factory.py"],
     deps = [
         ":nets",
-        # "//tensorflow/contrib/slim",
+        "//third_party/py/tf_slim:slim",
     ],
 )
 
@@ -918,6 +927,7 @@ py_test(  # py2and3_test
     srcs_version = "PY2AND3",
     deps = [
         ":nets_factory",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
     ],
 )
@@ -929,6 +939,7 @@ pytype_strict_binary(
     deps = [
         ":nets_factory",
         ":preprocessing_factory",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         "//third_party/py/absl:app",
         "//third_party/py/absl/flags",
         # "//tensorflow",
@@ -946,8 +957,8 @@ py_library(
         ":nets_factory",
         ":preprocessing_factory",
         # "//tensorflow",
+        "//third_party/py/tf_slim:slim",
         # "//tensorflow/contrib/quantize:quantize_graph",
-        # "//tensorflow/contrib/slim",
     ],
 )
 
@@ -956,9 +967,10 @@ py_binary(
     srcs = ["train_image_classifier.py"],
     # WARNING: not supported in bazel; will be commented out by copybara.
     # paropts = ["--compress"],
-    python_version = "PY2",
+    python_version = "PY3",
     deps = [
         ":train_image_classifier_lib",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
     ],
 )
 
@@ -970,17 +982,18 @@ py_library(
         ":nets_factory",
         ":preprocessing_factory",
         # "//tensorflow",
+        "//third_party/py/tf_slim:slim",
         # "//tensorflow/contrib/quantize:quantize_graph",
-        # "//tensorflow/contrib/slim",
     ],
 )
 
 py_binary(
     name = "eval_image_classifier",
     srcs = ["eval_image_classifier.py"],
-    python_version = "PY2",
+    python_version = "PY3",
     deps = [
         ":eval_image_classifier_lib",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
     ],
 )
 
@@ -989,8 +1002,11 @@ py_binary(
     srcs = ["export_inference_graph.py"],
     # WARNING: not supported in bazel; will be commented out by copybara.
     # paropts = ["--compress"],
-    python_version = "PY2",
-    deps = [":export_inference_graph_lib"],
+    python_version = "PY3",
+    deps = [
+        ":export_inference_graph_lib",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
+    ],
 )
 
 py_library(
@@ -1001,22 +1017,22 @@ py_library(
         ":nets_factory",
         # "//tensorflow",
         # "//tensorflow/contrib/quantize:quantize_graph",
-        # "//tensorflow/contrib/slim",
         # "//tensorflow/python:platform",
     ],
 )
 
-py_test(
+py_test(  # py2and3_test
     name = "export_inference_graph_test",
     size = "medium",
     srcs = ["export_inference_graph_test.py"],
-    python_version = "PY2",
+    python_version = "PY3",
     srcs_version = "PY2AND3",
     tags = [
         "manual",
     ],
     deps = [
         ":export_inference_graph_lib",
+        "//learning/brain/public:disable_tf2",  # build_cleaner: keep; go/disable_tf2
         # "//tensorflow",
         # "//tensorflow/python:platform",
     ],

research/slim/README.md

-![TensorFlow Requirement: 1.x](https://img.shields.io/badge/TensorFlow%20Requirement-1.x-brightgreen)
-![TensorFlow 2 Not Supported](https://img.shields.io/badge/TensorFlow%202%20Not%20Supported-%E2%9C%95-red.svg)
-
 # TensorFlow-Slim image classification model library
-
-[TF-slim](https://github.com/tensorflow/models/tree/master/research/slim)
-is a new lightweight high-level API of TensorFlow (`tensorflow.contrib.slim`)
-for defining, training and evaluating complex
-models. This directory contains
-code for training and evaluating several widely used Convolutional Neural
-Network (CNN) image classification models using TF-slim.
-It contains scripts that will allow
+This directory contains code for training and evaluating several
+widely used Convolutional Neural Network (CNN) image classification
+models using
+[tf_slim](https://github.com/google-research/tf-slim/tree/master/tf_slim).
+It contains scripts that allow
 you to train models from scratch or fine-tune them from pre-trained network
 weights. It also contains code for downloading standard image datasets,
 converting them
@@ -18,15 +12,12 @@ data reading and queueing utilities. You can easily train any model on any of
 these datasets, as we demonstrate below. We've also included a
 [jupyter notebook](https://github.com/tensorflow/models/blob/master/research/slim/slim_walkthrough.ipynb),
 which provides working examples of how to use TF-Slim for image classification.
-For developing or modifying your own models, see also the [main TF-Slim page](https://github.com/tensorflow/models/tree/master/research/slim).
+For developing or modifying your own models, see also the [main TF-Slim page](https://github.com/google-research/tf-slim/tree/master/tf_slim).
 
 ## Contacts
 
 Maintainers of TF-slim:
-
-* Sergio Guadarrama, GitHub: [sguada](https://github.com/sguada)
-* Nathan Silberman,
-  GitHub: [nathansilberman](https://github.com/nathansilberman)
+* Sergio Guadarrama, github: [sguada](https://github.com/sguada)
 
 ## Citation
 "TensorFlow-Slim image classification model library"
@@ -52,12 +43,12 @@ prerequisite packages.
 
 ## Installing latest version of TF-slim
 
-TF-Slim is available as `tf.contrib.slim` via TensorFlow 1.0. To test that your
+TF-Slim is available as `tf_slim` package. To test that your
 installation is working, execute the following command; it should run without
 raising any errors.
 
 ```
-python -c "import tensorflow.contrib.slim as slim; eval = slim.evaluation.evaluate_once"
+python -c "import tf_slim as slim; eval = slim.evaluation.evaluate_once"
 ```
 
 ## Installing the TF-slim image models library
@@ -143,7 +134,7 @@ download can take several hours, and could use up to 500GB.
 ## Creating a TF-Slim Dataset Descriptor.
 
 Once the TFRecord files have been created, you can easily define a Slim
-[Dataset](https://github.com/tensorflow/tensorflow/blob/r0.10/tensorflow/contrib/slim/python/slim/data/dataset.py),
+[Dataset](https://github.com/google-research/tf-slim/master/tf_slim/data/dataset.py),
 which stores pointers to the data file, as well as various other pieces of
 metadata, such as the class labels, the train/test split, and how to parse the
 TFExample protos. We have included the TF-Slim Dataset descriptors
@@ -156,14 +147,15 @@ and
 [VisualWakeWords](https://github.com/tensorflow/models/blob/master/research/slim/datasets/visualwakewords.py),
 An example of how to load data using a TF-Slim dataset descriptor using a
 TF-Slim
-[DatasetDataProvider](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/slim/python/slim/data/dataset_data_provider.py)
+[DatasetDataProvider](https://github.com/google-research/tf-slim/tree/master/tf_slim/data/dataset_data_provider.py)
 is found below:
 
 ```python
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 from datasets import flowers
 
-slim = tf.contrib.slim
+
 
 # Selects the 'validation' dataset.
 dataset = flowers.get_split('validation', DATA_DIR)
@@ -205,10 +197,10 @@ you will not need to interact with the script again.
 DATA_DIR=$HOME/imagenet-data
 
 # build the preprocessing script.
-bazel build slim/download_and_preprocess_imagenet
+bazel build slim/download_and_convert_imagenet
 
 # run it
-bazel-bin/slim/download_and_preprocess_imagenet "${DATA_DIR}"
+bazel-bin/slim/download_and_convert_imagenet "${DATA_DIR}"
 ```
 
 The final line of the output script should read:
@@ -414,7 +406,7 @@ $ python eval_image_classifier.py \
     --model_name=inception_v3
 ```
 
-See the [evaluation module example](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim#evaluation-loop)
+See the [evaluation module example](https://github.com/google-research/tf-slim#evaluation-loop)
 for an example of how to evaluate a model at multiple checkpoints during or after the training.
 
 # Exporting the Inference Graph

research/slim/datasets/build_imagenet_data.py

@@ -94,7 +94,7 @@ import threading
 
 import numpy as np
 from six.moves import xrange  # pylint: disable=redefined-builtin
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 
 tf.app.flags.DEFINE_string('train_directory', '/tmp/',

research/slim/datasets/cifar10.py

@@ -23,13 +23,11 @@ from __future__ import division
 from __future__ import print_function
 
 import os
-import tensorflow as tf
-from tensorflow.contrib import slim as contrib_slim
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 
 from datasets import dataset_utils
 
-slim = contrib_slim
-
 _FILE_PATTERN = 'cifar10_%s.tfrecord'
 
 SPLITS_TO_SIZES = {'train': 50000, 'test': 10000}

research/slim/datasets/dataset_utils.py

@@ -23,7 +23,7 @@ import tarfile
 import zipfile
 
 from six.moves import urllib
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 LABELS_FILENAME = 'labels.txt'
 

research/slim/datasets/download_and_convert_cifar10.py

@@ -33,7 +33,7 @@ import tarfile
 import numpy as np
 from six.moves import cPickle
 from six.moves import urllib
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 from datasets import dataset_utils
 

research/slim/datasets/download_and_convert_flowers.py

@@ -32,7 +32,9 @@ import os
 import random
 import sys
 
-import tensorflow as tf
+from six.moves import range
+from six.moves import zip
+import tensorflow.compat.v1 as tf
 
 from datasets import dataset_utils
 
@@ -189,7 +191,8 @@ def run(dataset_dir):
 
   dataset_utils.download_and_uncompress_tarball(_DATA_URL, dataset_dir)
   photo_filenames, class_names = _get_filenames_and_classes(dataset_dir)
-  class_names_to_ids = dict(zip(class_names, range(len(class_names))))
+  class_names_to_ids = dict(
+      list(zip(class_names, list(range(len(class_names))))))
 
   # Divide into train and test:
   random.seed(_RANDOM_SEED)
@@ -204,7 +207,8 @@ def run(dataset_dir):
                    dataset_dir)
 
   # Finally, write the labels file:
-  labels_to_class_names = dict(zip(range(len(class_names)), class_names))
+  labels_to_class_names = dict(
+      list(zip(list(range(len(class_names))), class_names)))
   dataset_utils.write_label_file(labels_to_class_names, dataset_dir)
 
   _clean_up_temporary_files(dataset_dir)

research/slim/datasets/download_and_convert_mnist.py

@@ -32,7 +32,7 @@ import sys
 
 import numpy as np
 from six.moves import urllib
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 from datasets import dataset_utils
 

research/slim/datasets/download_and_convert_visualwakewords.py

@@ -77,17 +77,17 @@ from __future__ import division
 from __future__ import print_function
 
 import os
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 from datasets import download_and_convert_visualwakewords_lib
 
-tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.INFO)
+tf.logging.set_verbosity(tf.logging.INFO)
 
-tf.compat.v1.app.flags.DEFINE_string(
+tf.app.flags.DEFINE_string(
     'coco_dirname', 'coco_dataset',
     'A subdirectory in visualwakewords dataset directory'
     'containing the coco dataset')
 
-FLAGS = tf.compat.v1.app.flags.FLAGS
+FLAGS = tf.app.flags.FLAGS
 
 
 def run(dataset_dir, small_object_area_threshold, foreground_class_of_interest):

research/slim/datasets/download_and_convert_visualwakewords_lib.py

@@ -32,26 +32,27 @@ import contextlib2
 
 import PIL.Image
 
-import tensorflow as tf
+import six
+import tensorflow.compat.v1 as tf
 
 from datasets import dataset_utils
 
-tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.INFO)
+tf.logging.set_verbosity(tf.logging.INFO)
 
-tf.compat.v1.app.flags.DEFINE_string(
+tf.app.flags.DEFINE_string(
     'coco_train_url',
     'http://images.cocodataset.org/zips/train2014.zip',
     'Link to zip file containing coco training data')
-tf.compat.v1.app.flags.DEFINE_string(
+tf.app.flags.DEFINE_string(
     'coco_validation_url',
     'http://images.cocodataset.org/zips/val2014.zip',
     'Link to zip file containing coco validation data')
-tf.compat.v1.app.flags.DEFINE_string(
+tf.app.flags.DEFINE_string(
     'coco_annotations_url',
     'http://images.cocodataset.org/annotations/annotations_trainval2014.zip',
     'Link to zip file containing coco annotation data')
 
-FLAGS = tf.compat.v1.app.flags.FLAGS
+FLAGS = tf.app.flags.FLAGS
 
 
 def download_coco_dataset(dataset_dir):
@@ -201,7 +202,7 @@ def create_tf_record_for_visualwakewords_dataset(annotations_file, image_dir,
     groundtruth_data = json.load(fid)
     images = groundtruth_data['images']
     annotations_index = groundtruth_data['annotations']
-    annotations_index = {int(k): v for k, v in annotations_index.iteritems()}
+    annotations_index = {int(k): v for k, v in six.iteritems(annotations_index)}
     # convert 'unicode' key to 'int' key after we parse the json file
 
     for idx, image in enumerate(images):

research/slim/datasets/flowers.py

@@ -23,13 +23,11 @@ from __future__ import division
 from __future__ import print_function
 
 import os
-import tensorflow as tf
-from tensorflow.contrib import slim as contrib_slim
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 
 from datasets import dataset_utils
 
-slim = contrib_slim
-
 _FILE_PATTERN = 'flowers_%s_*.tfrecord'
 
 SPLITS_TO_SIZES = {'train': 3320, 'validation': 350}

research/slim/datasets/imagenet.py

@@ -34,13 +34,11 @@ from __future__ import print_function
 
 import os
 from six.moves import urllib
-import tensorflow as tf
-from tensorflow.contrib import slim as contrib_slim
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 
 from datasets import dataset_utils
 
-slim = contrib_slim
-
 # TODO(nsilberman): Add tfrecord file type once the script is updated.
 _FILE_PATTERN = '%s-*'
 

research/slim/datasets/mnist.py

@@ -23,13 +23,11 @@ from __future__ import division
 from __future__ import print_function
 
 import os
-import tensorflow as tf
-from tensorflow.contrib import slim as contrib_slim
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 
 from datasets import dataset_utils
 
-slim = contrib_slim
-
 _FILE_PATTERN = 'mnist_%s.tfrecord'
 
 _SPLITS_TO_SIZES = {'train': 60000, 'test': 10000}

research/slim/datasets/visualwakewords.py

@@ -28,14 +28,12 @@ from __future__ import division
 from __future__ import print_function
 
 import os
-import tensorflow as tf
-from tensorflow.contrib import slim as contrib_slim
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 
 from datasets import dataset_utils
 
 
-slim = contrib_slim
-
 _FILE_PATTERN = '%s.record-*'
 
 _SPLITS_TO_SIZES = {

research/slim/deployment/model_deploy.py

@@ -101,10 +101,8 @@ from __future__ import print_function
 
 import collections
 
-import tensorflow as tf
-from tensorflow.contrib import slim as contrib_slim
-
-slim = contrib_slim
+import tensorflow.compat.v1 as tf
+import tf_slim as slim
 
 
 __all__ = ['create_clones',

research/slim/deployment/model_deploy_test.py

@@ -19,14 +19,11 @@ from __future__ import division
 from __future__ import print_function
 
 import numpy as np
-import tensorflow as tf
-from tensorflow.contrib import framework as contrib_framework
-from tensorflow.contrib import layers as contrib_layers
-from tensorflow.contrib import slim as contrib_slim
+import tensorflow.compat.v1 as tf
 
-from deployment import model_deploy
+import tf_slim as slim
 
-slim = contrib_slim
+from deployment import model_deploy
 
 
 class DeploymentConfigTest(tf.test.TestCase):
@@ -511,9 +508,8 @@ class DeployTest(tf.test.TestCase):
 
       with tf.Session() as sess:
         sess.run(tf.global_variables_initializer())
-        moving_mean = contrib_framework.get_variables_by_name('moving_mean')[0]
-        moving_variance = contrib_framework.get_variables_by_name(
-            'moving_variance')[0]
+        moving_mean = slim.get_variables_by_name('moving_mean')[0]
+        moving_variance = slim.get_variables_by_name('moving_variance')[0]
         initial_loss = sess.run(model.total_loss)
         initial_mean, initial_variance = sess.run([moving_mean,
                                                    moving_variance])
@@ -539,8 +535,8 @@ class DeployTest(tf.test.TestCase):
       # clone function creates a fully_connected layer with a regularizer loss.
       def ModelFn():
         inputs = tf.constant(1.0, shape=(10, 20), dtype=tf.float32)
-        reg = contrib_layers.l2_regularizer(0.001)
-        contrib_layers.fully_connected(inputs, 30, weights_regularizer=reg)
+        reg = slim.l2_regularizer(0.001)
+        slim.fully_connected(inputs, 30, weights_regularizer=reg)
 
       model = model_deploy.deploy(
           deploy_config, ModelFn,
@@ -558,8 +554,8 @@ class DeployTest(tf.test.TestCase):
       # clone function creates a fully_connected layer with a regularizer loss.
       def ModelFn():
         inputs = tf.constant(1.0, shape=(10, 20), dtype=tf.float32)
-        reg = contrib_layers.l2_regularizer(0.001)
-        contrib_layers.fully_connected(inputs, 30, weights_regularizer=reg)
+        reg = slim.l2_regularizer(0.001)
+        slim.fully_connected(inputs, 30, weights_regularizer=reg)
 
       # No optimizer here, it's an eval.
       model = model_deploy.deploy(deploy_config, ModelFn)

research/slim/download_and_convert_data.py

@@ -39,22 +39,22 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 from datasets import download_and_convert_cifar10
 from datasets import download_and_convert_flowers
 from datasets import download_and_convert_mnist
 from datasets import download_and_convert_visualwakewords
 
-FLAGS = tf.compat.v1.app.flags.FLAGS
+FLAGS = tf.app.flags.FLAGS
 
-tf.compat.v1.app.flags.DEFINE_string(
+tf.app.flags.DEFINE_string(
     'dataset_name',
     None,
     'The name of the dataset to convert, one of "flowers", "cifar10", "mnist", "visualwakewords"'
     )
 
-tf.compat.v1.app.flags.DEFINE_string(
+tf.app.flags.DEFINE_string(
     'dataset_dir',
     None,
     'The directory where the output TFRecords and temporary files are saved.')
@@ -91,4 +91,4 @@ def main(_):
         'dataset_name [%s] was not recognized.' % FLAGS.dataset_name)
 
 if __name__ == '__main__':
-  tf.compat.v1.app.run()
+  tf.app.run()