Internal changes for slim (tensorflow#3448)

* Merged commit includes the following changes: 186565198 by Sergio Guadarrama: Applied random_hsv_in_yiq in inception_preprocessing. -- 186501039 by Sergio Guadarrama: Applied random_hsv_in_yiq in inception_preprocessing. -- 186013907 by Sergio Guadarrama: Internal change 185715309 by Sergio Guadarrama: Obviates the need for prepadding on mobilenet v1 and v2 for fully convolutional models. -- 184266252 by Sergio Guadarrama: Give build_nasnet_*() functions an optional flag use_aux_head, and add an internal-only arg scope to NasNetA*Cell._apply_drop_path(). -- 183865228 by Sergio Guadarrama: Internal change 179580924 by Sergio Guadarrama: Internal change 177320302 by Sergio Guadarrama: Internal change 177130184 by Sergio Guadarrama: Make slim nets tests faster by using smaller examples of oversized inputs. -- 176965289 by Sergio Guadarrama: Internal change 176585260 by Sergio Guadarrama: Internal change 176534973 by Sergio Guadarrama: Internal change 175526881 by Sergio Guadarrama: Internal change 174967704 by Sergio Guadarrama: Treat num_classes=0 same as None in a few slim nets overlooked by the recent change. -- 174443227 by Sergio Guadarrama: Internal change 174281864 by Sergio Guadarrama: Internal change 174249903 by Sergio Guadarrama: Fix nasnet image classification and object detection by moving the option to turn ON or OFF batch norm training into it's own arg_scope used only by detection -- 173954505 by Sergio Guadarrama: Merge pull request tensorflow#2651 from sguada/tmp1 Fixes imports Closes tensorflow#2636 ORIGINAL_AUTHOR=Jon Shlens <[email protected]> COPYBARA_INTEGRATE_REVIEW=tensorflow#2636 from tensorflow:sguada-patch-1 19ff570f52df5ab655c00fb439129b201c5f2dce -- 173928094 by Sergio Guadarrama: Remove pending imports -- PiperOrigin-RevId: 186565198 * Remove internal links.
so2jia · Feb 27, 2018 · 629adff · 629adff
1 parent 599521e
commit 629adff
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Showing 28 changed files with 343 additions and 106 deletions.
diff --git a/research/slim/BUILD b/research/slim/BUILD
@@ -216,7 +216,7 @@ py_library(
     srcs = ["nets/alexnet.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -296,7 +296,7 @@ py_library(
     srcs = ["nets/inception_utils.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -345,7 +345,7 @@ py_library(
     srcs = ["nets/inception_resnet_v2.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -425,7 +425,7 @@ py_library(
     srcs = ["nets/mobilenet_v1.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -511,7 +511,7 @@ py_library(
     srcs = ["nets/overfeat.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -531,7 +531,7 @@ py_library(
     srcs = ["nets/pix2pix.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -550,7 +550,7 @@ py_library(
     srcs = ["nets/resnet_utils.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -607,7 +607,7 @@ py_library(
     srcs = ["nets/vgg.py"],
     srcs_version = "PY2AND3",
     deps = [
-        # "//tensorflow"
+        # "//tensorflow",
     ],
 )
 
@@ -646,6 +646,7 @@ py_test(
 py_binary(
     name = "train_image_classifier",
     srcs = ["train_image_classifier.py"],
+    paropts = ["--compress"],
     deps = [
         ":dataset_factory",
         ":model_deploy",
@@ -669,6 +670,7 @@ py_binary(
 py_binary(
     name = "export_inference_graph",
     srcs = ["export_inference_graph.py"],
+    paropts = ["--compress"],
     deps = [
         ":dataset_factory",
         ":nets_factory",

diff --git a/research/slim/datasets/build_imagenet_data.py b/research/slim/datasets/build_imagenet_data.py
@@ -92,9 +92,7 @@
 import sys
 import threading
 
-import google3
 import numpy as np
-from six.moves import xrange
 import tensorflow as tf
 
 tf.app.flags.DEFINE_string('train_directory', '/tmp/',

diff --git a/research/slim/datasets/preprocess_imagenet_validation_data.py b/research/slim/datasets/preprocess_imagenet_validation_data.py
@@ -51,7 +51,6 @@
 import os
 import os.path
 import sys
-from six.moves import xrange
 
 
 if __name__ == '__main__':

diff --git a/research/slim/datasets/process_bounding_boxes.py b/research/slim/datasets/process_bounding_boxes.py
@@ -85,7 +85,6 @@
 import os.path
 import sys
 import xml.etree.ElementTree as ET
-from six.moves import xrange
 
 
 class BoundingBox(object):

diff --git a/research/slim/eval_image_classifier.py b/research/slim/eval_image_classifier.py
@@ -28,7 +28,7 @@
 slim = tf.contrib.slim
 
 tf.app.flags.DEFINE_integer(
-    'batch_size', 50, 'The number of samples in each batch.')
+    'batch_size', 100, 'The number of samples in each batch.')
 
 tf.app.flags.DEFINE_integer(
     'max_num_batches', None,

diff --git a/research/slim/nets/alexnet_test.py b/research/slim/nets/alexnet_test.py
@@ -50,7 +50,7 @@ def testFullyConvolutional(self):
 
   def testGlobalPool(self):
     batch_size = 1
-    height, width = 300, 400
+    height, width = 256, 256
     num_classes = 1000
     with self.test_session():
       inputs = tf.random_uniform((batch_size, height, width, 3))

diff --git a/research/slim/nets/cyclegan.py b/research/slim/nets/cyclegan.py
@@ -18,7 +18,7 @@
 from __future__ import print_function
 
 import numpy as np
-from six.moves import xrange
+
 import tensorflow as tf
 
 layers = tf.contrib.layers

diff --git a/research/slim/nets/dcgan.py b/research/slim/nets/dcgan.py
@@ -19,7 +19,6 @@
 
 from math import log
 
-from six.moves import xrange
 import tensorflow as tf
 slim = tf.contrib.slim
 

diff --git a/research/slim/nets/dcgan_test.py b/research/slim/nets/dcgan_test.py
@@ -18,7 +18,6 @@
 from __future__ import division
 from __future__ import print_function
 
-from six.moves import xrange
 import tensorflow as tf
 from nets import dcgan
 

diff --git a/research/slim/nets/inception_resnet_v2_test.py b/research/slim/nets/inception_resnet_v2_test.py
@@ -116,7 +116,7 @@ def testBuildOnlyUptoFinalEndpoint(self):
         if endpoint != 'PreAuxLogits':
           self.assertTrue(out_tensor.op.name.startswith(
               'InceptionResnetV2/' + endpoint))
-        self.assertItemsEqual(endpoints[:index+1], end_points)
+        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
 
   def testBuildAndCheckAllEndPointsUptoPreAuxLogits(self):
     batch_size = 5
@@ -227,8 +227,8 @@ def testHalfSizeImages(self):
                            [batch_size, 3, 3, 1536])
 
   def testGlobalPool(self):
-    batch_size = 2
-    height, width = 400, 600
+    batch_size = 1
+    height, width = 330, 400
     num_classes = 1000
     with self.test_session():
       inputs = tf.random_uniform((batch_size, height, width, 3))
@@ -238,11 +238,11 @@ def testGlobalPool(self):
                            [batch_size, num_classes])
       pre_pool = end_points['Conv2d_7b_1x1']
       self.assertListEqual(pre_pool.get_shape().as_list(),
-                           [batch_size, 11, 17, 1536])
+                           [batch_size, 8, 11, 1536])
 
   def testGlobalPoolUnknownImageShape(self):
-    batch_size = 2
-    height, width = 400, 600
+    batch_size = 1
+    height, width = 330, 400
     num_classes = 1000
     with self.test_session() as sess:
       inputs = tf.placeholder(tf.float32, (batch_size, None, None, 3))
@@ -257,7 +257,7 @@ def testGlobalPoolUnknownImageShape(self):
       logits_out, pre_pool_out = sess.run([logits, pre_pool],
                                           {inputs: images.eval()})
       self.assertTupleEqual(logits_out.shape, (batch_size, num_classes))
-      self.assertTupleEqual(pre_pool_out.shape, (batch_size, 11, 17, 1536))
+      self.assertTupleEqual(pre_pool_out.shape, (batch_size, 8, 11, 1536))
 
   def testUnknownBatchSize(self):
     batch_size = 1

diff --git a/research/slim/nets/inception_v1_test.py b/research/slim/nets/inception_v1_test.py
@@ -86,7 +86,7 @@ def testBuildOnlyUptoFinalEndpoint(self):
             inputs, final_endpoint=endpoint)
         self.assertTrue(out_tensor.op.name.startswith(
             'InceptionV1/' + endpoint))
-        self.assertItemsEqual(endpoints[:index+1], end_points)
+        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
 
   def testBuildAndCheckAllEndPointsUptoMixed5c(self):
     batch_size = 5
@@ -159,8 +159,8 @@ def testUnknownImageShape(self):
 
   def testGlobalPoolUnknownImageShape(self):
     tf.reset_default_graph()
-    batch_size = 2
-    height, width = 300, 400
+    batch_size = 1
+    height, width = 250, 300
     num_classes = 1000
     input_np = np.random.uniform(0, 1, (batch_size, height, width, 3))
     with self.test_session() as sess:
@@ -174,7 +174,7 @@ def testGlobalPoolUnknownImageShape(self):
       feed_dict = {inputs: input_np}
       tf.global_variables_initializer().run()
       pre_pool_out = sess.run(pre_pool, feed_dict=feed_dict)
-      self.assertListEqual(list(pre_pool_out.shape), [batch_size, 10, 13, 1024])
+      self.assertListEqual(list(pre_pool_out.shape), [batch_size, 8, 10, 1024])
 
   def testUnknowBatchSize(self):
     batch_size = 1

diff --git a/research/slim/nets/inception_v2_test.py b/research/slim/nets/inception_v2_test.py
@@ -85,7 +85,7 @@ def testBuildOnlyUptoFinalEndpoint(self):
             inputs, final_endpoint=endpoint)
         self.assertTrue(out_tensor.op.name.startswith(
             'InceptionV2/' + endpoint))
-        self.assertItemsEqual(endpoints[:index+1], end_points)
+        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
 
   def testBuildAndCheckAllEndPointsUptoMixed5c(self):
     batch_size = 5
@@ -273,8 +273,8 @@ def testUnknownImageShape(self):
 
   def testGlobalPoolUnknownImageShape(self):
     tf.reset_default_graph()
-    batch_size = 2
-    height, width = 300, 400
+    batch_size = 1
+    height, width = 250, 300
     num_classes = 1000
     input_np = np.random.uniform(0, 1, (batch_size, height, width, 3))
     with self.test_session() as sess:
@@ -288,7 +288,7 @@ def testGlobalPoolUnknownImageShape(self):
       feed_dict = {inputs: input_np}
       tf.global_variables_initializer().run()
       pre_pool_out = sess.run(pre_pool, feed_dict=feed_dict)
-      self.assertListEqual(list(pre_pool_out.shape), [batch_size, 10, 13, 1024])
+      self.assertListEqual(list(pre_pool_out.shape), [batch_size, 8, 10, 1024])
 
   def testUnknowBatchSize(self):
     batch_size = 1

diff --git a/research/slim/nets/inception_v3_test.py b/research/slim/nets/inception_v3_test.py
@@ -88,7 +88,7 @@ def testBuildOnlyUptoFinalEndpoint(self):
             inputs, final_endpoint=endpoint)
         self.assertTrue(out_tensor.op.name.startswith(
             'InceptionV3/' + endpoint))
-        self.assertItemsEqual(endpoints[:index+1], end_points)
+        self.assertItemsEqual(endpoints[:index+1], end_points.keys())
 
   def testBuildAndCheckAllEndPointsUptoMixed7c(self):
     batch_size = 5
@@ -240,8 +240,8 @@ def testUnknownImageShape(self):
 
   def testGlobalPoolUnknownImageShape(self):
     tf.reset_default_graph()
-    batch_size = 2
-    height, width = 400, 600
+    batch_size = 1
+    height, width = 330, 400
     num_classes = 1000
     input_np = np.random.uniform(0, 1, (batch_size, height, width, 3))
     with self.test_session() as sess:
@@ -254,7 +254,7 @@ def testGlobalPoolUnknownImageShape(self):
       feed_dict = {inputs: input_np}
       tf.global_variables_initializer().run()
       pre_pool_out = sess.run(pre_pool, feed_dict=feed_dict)
-      self.assertListEqual(list(pre_pool_out.shape), [batch_size, 11, 17, 2048])
+      self.assertListEqual(list(pre_pool_out.shape), [batch_size, 8, 11, 2048])
 
   def testUnknowBatchSize(self):
     batch_size = 1

diff --git a/research/slim/nets/inception_v4_test.py b/research/slim/nets/inception_v4_test.py
@@ -146,7 +146,7 @@ def testBuildOnlyUpToFinalEndpoint(self):
             inputs, final_endpoint=endpoint)
         self.assertTrue(out_tensor.op.name.startswith(
             'InceptionV4/' + endpoint))
-        self.assertItemsEqual(all_endpoints[:index+1], end_points)
+        self.assertItemsEqual(all_endpoints[:index+1], end_points.keys())
 
   def testVariablesSetDevice(self):
     batch_size = 5
@@ -177,8 +177,8 @@ def testHalfSizeImages(self):
                          [batch_size, 3, 3, 1536])
 
   def testGlobalPool(self):
-    batch_size = 2
-    height, width = 400, 600
+    batch_size = 1
+    height, width = 350, 400
     num_classes = 1000
     inputs = tf.random_uniform((batch_size, height, width, 3))
     logits, end_points = inception.inception_v4(inputs, num_classes)
@@ -187,11 +187,11 @@ def testGlobalPool(self):
                          [batch_size, num_classes])
     pre_pool = end_points['Mixed_7d']
     self.assertListEqual(pre_pool.get_shape().as_list(),
-                         [batch_size, 11, 17, 1536])
+                         [batch_size, 9, 11, 1536])
 
   def testGlobalPoolUnknownImageShape(self):
-    batch_size = 2
-    height, width = 400, 600
+    batch_size = 1
+    height, width = 350, 400
     num_classes = 1000
     with self.test_session() as sess:
       inputs = tf.placeholder(tf.float32, (batch_size, None, None, 3))
@@ -206,7 +206,7 @@ def testGlobalPoolUnknownImageShape(self):
       logits_out, pre_pool_out = sess.run([logits, pre_pool],
                                           {inputs: images.eval()})
       self.assertTupleEqual(logits_out.shape, (batch_size, num_classes))
-      self.assertTupleEqual(pre_pool_out.shape, (batch_size, 11, 17, 1536))
+      self.assertTupleEqual(pre_pool_out.shape, (batch_size, 9, 11, 1536))
 
   def testUnknownBatchSize(self):
     batch_size = 1