Remove so many more hourglass imports

Change: 143230429

5 files changed, 148 insertions, 70 deletions

diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD b/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD
index a9de4f181e..e62b2671eb 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD
@@ -22,7 +22,16 @@ py_test(
     srcs_version = "PY2AND3",
     deps = [
         ":model_analyzer",
-        "//tensorflow:tensorflow_py",
+        "//tensorflow/core:protos_all_py",
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:framework_for_generated_wrappers",
+        "//tensorflow/python:init_ops",
+        "//tensorflow/python:nn_ops",
+        "//tensorflow/python:platform",
+        "//tensorflow/python:variable_scope",
+        "//tensorflow/python:variables",
     ],
 )
 
@@ -32,6 +41,7 @@ py_library(
     srcs_version = "PY2AND3",
     deps = [
         "//tensorflow/python:framework_for_generated_wrappers",
+        "//tensorflow/python:platform",
         "//tensorflow/tools/tfprof:protos_all_py",
         "@six_archive//:six",
     ],
@@ -42,7 +52,13 @@ tf_py_test(
     srcs = ["tfprof_logger_test.py"],
     additional_deps = [
         ":tfprof_logger",
-        "//tensorflow:tensorflow_py",
+        "//tensorflow/contrib/copy_graph:copy_graph_py",
+        "//tensorflow/core:protos_all_py",
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:framework_for_generated_wrappers",
+        "//tensorflow/python:math_ops",
         "//tensorflow/tools/tfprof:protos_all_py",
     ],
 )
@@ -67,9 +83,15 @@ py_test(
     srcs_version = "PY2AND3",
     deps = [
         ":pywrap_tensorflow_print_model_analysis_lib",
-        "//tensorflow:tensorflow_py",
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:framework_for_generated_wrappers",
         "//tensorflow/python:framework_test_lib",
+        "//tensorflow/python:init_ops",
+        "//tensorflow/python:nn_ops",
         "//tensorflow/python:platform_test",
+        "//tensorflow/python:variable_scope",
         "//tensorflow/tools/tfprof:protos_all_py",
     ],
 )
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py
index 03f2e0df86..441c19b468 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py
@@ -12,67 +12,87 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
+
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
 import os
+import sys
+
+# TODO: #6568 Remove this hack that makes dlopen() not crash.
+if hasattr(sys, 'getdlopenflags') and hasattr(sys, 'setdlopenflags'):
+  import ctypes
+  sys.setdlopenflags(sys.getdlopenflags() | ctypes.RTLD_GLOBAL)
+
+from tensorflow.core.protobuf import config_pb2
+from tensorflow.python.client import session
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import init_ops
+from tensorflow.python.ops import nn_ops
+from tensorflow.python.ops import variable_scope
+from tensorflow.python.ops import variables
+from tensorflow.python.platform import gfile
+from tensorflow.python.platform import test
 
-import tensorflow as tf
+# XXX: this depends on pywrap_tensorflow and must come later
+from tensorflow.contrib.tfprof.python.tools.tfprof import model_analyzer
 
 
-class PrintModelAnalysisTest(tf.test.TestCase):
+class PrintModelAnalysisTest(test.TestCase):
 
   def _BuildSmallModel(self):
-    image = tf.zeros([2, 6, 6, 3])
-    kernel = tf.get_variable(
+    image = array_ops.zeros([2, 6, 6, 3])
+    kernel = variable_scope.get_variable(
         'DW', [3, 3, 3, 6],
-        tf.float32,
-        initializer=tf.random_normal_initializer(stddev=0.001))
-    x = tf.nn.conv2d(image, kernel, [1, 2, 2, 1], padding='SAME')
-    kernel = tf.get_variable(
+        dtypes.float32,
+        initializer=init_ops.random_normal_initializer(stddev=0.001))
+    x = nn_ops.conv2d(image, kernel, [1, 2, 2, 1], padding='SAME')
+    kernel = variable_scope.get_variable(
         'DW2', [2, 2, 6, 12],
-        tf.float32,
-        initializer=tf.random_normal_initializer(stddev=0.001))
-    x = tf.nn.conv2d(x, kernel, [1, 2, 2, 1], padding='SAME')
+        dtypes.float32,
+        initializer=init_ops.random_normal_initializer(stddev=0.001))
+    x = nn_ops.conv2d(x, kernel, [1, 2, 2, 1], padding='SAME')
     return x
 
   def testDumpToFile(self):
-    opts = tf.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS
-    opts['dump_to_file'] = os.path.join(tf.test.get_temp_dir(), 'dump')
+    opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS
+    opts['dump_to_file'] = os.path.join(test.get_temp_dir(), 'dump')
 
-    with tf.Session() as sess, tf.device('/cpu:0'):
+    with session.Session() as sess, ops.device('/cpu:0'):
       _ = self._BuildSmallModel()
-      tf.contrib.tfprof.model_analyzer.print_model_analysis(
-          sess.graph, tfprof_options=opts)
+      model_analyzer.print_model_analysis(sess.graph, tfprof_options=opts)
 
-      with tf.gfile.Open(opts['dump_to_file'], 'r') as f:
+      with gfile.Open(opts['dump_to_file'], 'r') as f:
         self.assertEqual(u'_TFProfRoot (--/450 params)\n'
                          '  DW (3x3x3x6, 162/162 params)\n'
                          '  DW2 (2x2x6x12, 288/288 params)\n',
                          f.read().decode('utf-8'))
 
   def testSelectEverything(self):
-    opts = tf.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS
-    opts['dump_to_file'] = os.path.join(tf.test.get_temp_dir(), 'dump')
+    opts = model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS
+    opts['dump_to_file'] = os.path.join(test.get_temp_dir(), 'dump')
     opts['account_type_regexes'] = ['.*']
     opts['select'] = [
         'bytes', 'params', 'float_ops', 'num_hidden_ops', 'device', 'op_types'
     ]
 
-    with tf.Session() as sess, tf.device('/cpu:0'):
+    with session.Session() as sess, ops.device('/cpu:0'):
       x = self._BuildSmallModel()
 
-      sess.run(tf.global_variables_initializer())
-      run_meta = tf.RunMetadata()
+      sess.run(variables.global_variables_initializer())
+      run_meta = config_pb2.RunMetadata()
       _ = sess.run(x,
-                   options=tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE),
+                   options=config_pb2.RunOptions(
+                       trace_level=config_pb2.RunOptions.FULL_TRACE),
                    run_metadata=run_meta)
 
-      tf.contrib.tfprof.model_analyzer.print_model_analysis(
+      model_analyzer.print_model_analysis(
           sess.graph, run_meta, tfprof_options=opts)
 
-      with tf.gfile.Open(opts['dump_to_file'], 'r') as f:
+      with gfile.Open(opts['dump_to_file'], 'r') as f:
         # pylint: disable=line-too-long
         self.assertEqual(
             '_TFProfRoot (0/450 params, 0/10.44k flops, 0B/5.28KB, _kTFScopeParent)\n  Conv2D (0/0 params, 5.83k/5.83k flops, 432B/432B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D)\n  Conv2D_1 (0/0 params, 4.61k/4.61k flops, 384B/384B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D)\n  DW (3x3x3x6, 162/162 params, 0/0 flops, 648B/1.30KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|VariableV2|_trainable_variables)\n    DW/Assign (0/0 params, 0/0 flops, 0B/0B, /device:CPU:0, /device:CPU:0|Assign)\n    DW/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n      DW/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n        DW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n        DW/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n        DW/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n        DW/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n        DW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n    DW/read (0/0 params, 0/0 flops, 648B/648B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity)\n  DW2 (2x2x6x12, 288/288 params, 0/0 flops, 1.15KB/2.30KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|VariableV2|_trainable_variables)\n    DW2/Assign (0/0 params, 0/0 flops, 0B/0B, /device:CPU:0, /device:CPU:0|Assign)\n    DW2/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n      DW2/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n        DW2/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n        DW2/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n        DW2/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n        DW2/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n        DW2/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n    DW2/read (0/0 params, 0/0 flops, 1.15KB/1.15KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity)\n  init (0/0 params, 0/0 flops, 0B/0B, /device:CPU:0, /device:CPU:0|NoOp)\n  zeros (0/0 params, 0/0 flops, 864B/864B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Const)\n',
@@ -81,4 +101,4 @@ class PrintModelAnalysisTest(tf.test.TestCase):
 
 
 if __name__ == '__main__':
-  tf.test.main()
+  test.main()
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py
index 46bdf2dcb2..07ed324d7c 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py
@@ -13,16 +13,34 @@
 # limitations under the License.
 # ==============================================================================
 """print_model_analysis test."""
+
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import tensorflow as tf
+import sys
+
+# TODO: #6568 Remove this hack that makes dlopen() not crash.
+if hasattr(sys, 'getdlopenflags') and hasattr(sys, 'setdlopenflags'):
+  import ctypes
+  sys.setdlopenflags(sys.getdlopenflags() | ctypes.RTLD_GLOBAL)
+
 from google.protobuf import text_format
-from tensorflow.contrib.tfprof.python.tools.tfprof import pywrap_tensorflow_print_model_analysis_lib as print_mdl
+
+from tensorflow.python.client import session
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import init_ops
+from tensorflow.python.ops import nn_ops
+from tensorflow.python.ops import variable_scope
+from tensorflow.python.platform import test
 from tensorflow.tools.tfprof import tfprof_options_pb2
 from tensorflow.tools.tfprof import tfprof_output_pb2
 
+# XXX: this depends on pywrap_tensorflow and must come later
+from tensorflow.contrib.tfprof.python.tools.tfprof import pywrap_tensorflow_print_model_analysis_lib as print_mdl
+
 # pylint: disable=bad-whitespace
 # pylint: disable=bad-continuation
 TEST_OPTIONS = {
@@ -47,15 +65,15 @@ TEST_OPTIONS = {
 # pylint: enable=bad-continuation
 
 
-class PrintModelAnalysisTest(tf.test.TestCase):
+class PrintModelAnalysisTest(test.TestCase):
 
   def _BuildSmallModel(self):
-    image = tf.zeros([2, 6, 6, 3])
-    kernel = tf.get_variable(
+    image = array_ops.zeros([2, 6, 6, 3])
+    kernel = variable_scope.get_variable(
         'DW', [6, 6, 3, 6],
-        tf.float32,
-        initializer=tf.random_normal_initializer(stddev=0.001))
-    x = tf.nn.conv2d(image, kernel, [1, 2, 2, 1], padding='SAME')
+        dtypes.float32,
+        initializer=init_ops.random_normal_initializer(stddev=0.001))
+    x = nn_ops.conv2d(image, kernel, [1, 2, 2, 1], padding='SAME')
     return x
 
   def testPrintModelAnalysis(self):
@@ -83,7 +101,7 @@ class PrintModelAnalysisTest(tf.test.TestCase):
       opts.select.append(p)
     opts.viz = TEST_OPTIONS['viz']
 
-    with tf.Session() as sess, tf.device('/cpu:0'):
+    with session.Session() as sess, ops.device('/cpu:0'):
       _ = self._BuildSmallModel()
       tfprof_pb = tfprof_output_pb2.TFProfNode()
       tfprof_pb.ParseFromString(
@@ -229,4 +247,4 @@ class PrintModelAnalysisTest(tf.test.TestCase):
 
 
 if __name__ == '__main__':
-  tf.test.main()
+  test.main()
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py b/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py
index 50ec954ff8..e8cf84b6c7 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py
@@ -24,8 +24,9 @@ import os
 import sys
 
 import six
-import tensorflow as tf
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_shape
+from tensorflow.python.platform import gfile
 from tensorflow.tools.tfprof import tfprof_log_pb2
 
 TRAINABLE_VARIABLES = '_trainable_variables'
@@ -50,7 +51,8 @@ def _fill_missing_graph_shape(graph, run_meta):
         if op.outputs[i].get_shape().is_fully_defined():
           continue
         node_stat_dims = node_stat_out.tensor_description.shape.dim
-        node_stat_shape = tf.TensorShape([d.size for d in node_stat_dims])
+        node_stat_shape = tensor_shape.TensorShape(
+            [d.size for d in node_stat_dims])
         try:
           op.outputs[i].set_shape(op.outputs[i].get_shape().merge_with(
               node_stat_shape))
@@ -91,7 +93,7 @@ def _get_logged_ops(graph, run_meta=None):
       entry.float_ops = int(stats.value)
       logged_ops[entry.name] = entry
 
-  for v in graph.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES):
+  for v in graph.get_collection(ops.GraphKeys.TRAINABLE_VARIABLES):
     if v.op.name not in logged_ops:
       entry = tfprof_log_pb2.OpLogEntry()
       entry.name = v.op.name
@@ -100,10 +102,9 @@ def _get_logged_ops(graph, run_meta=None):
     else:
       logged_ops[v.op.name].types.append(TRAINABLE_VARIABLES)
   if op_missing_shape > 0 and not run_meta:
-    sys.stderr.write(
-        '%d ops no flops stats due to incomplete shapes. '
-        'Consider passing run_meta to use run_time shapes.\n' %
-        op_missing_shape)
+    sys.stderr.write('%d ops no flops stats due to incomplete shapes. '
+                     'Consider passing run_meta to use run_time shapes.\n' %
+                     op_missing_shape)
   return logged_ops
 
 
@@ -156,5 +157,5 @@ def write_op_log(graph, log_dir, op_log=None, run_meta=None):
   """
   op_log = _merge_default_with_oplog(graph, op_log, run_meta)
 
-  with tf.gfile.Open(os.path.join(log_dir, 'tfprof_log'), 'w') as log:
+  with gfile.Open(os.path.join(log_dir, 'tfprof_log'), 'w') as log:
     log.write(op_log.SerializeToString())
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger_test.py
index 56a470e5f5..9a7fe9a887 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger_test.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger_test.py
@@ -12,61 +12,78 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
+
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import tensorflow as tf
+import sys
+
+# TODO: #6568 Remove this hack that makes dlopen() not crash.
+if hasattr(sys, 'getdlopenflags') and hasattr(sys, 'setdlopenflags'):
+  import ctypes
+  sys.setdlopenflags(sys.getdlopenflags() | ctypes.RTLD_GLOBAL)
+
+from tensorflow.contrib.copy_graph.python.util import copy_elements
+from tensorflow.contrib.tfprof.python.tools.tfprof import tfprof_logger
+from tensorflow.core.protobuf import config_pb2
+from tensorflow.python.client import session
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import math_ops
+from tensorflow.python.platform import test
 
 
-class TFProfLoggerTest(tf.test.TestCase):
+class TFProfLoggerTest(test.TestCase):
 
   def _BuildSmallPlaceholderlModel(self):
-    a = tf.placeholder(tf.int32, [2, 2])
-    b = tf.placeholder(tf.int32, [2, 2])
-    y = tf.matmul(a, b)
+    a = array_ops.placeholder(dtypes.int32, [2, 2])
+    b = array_ops.placeholder(dtypes.int32, [2, 2])
+    y = math_ops.matmul(a, b)
     return a, b, y
 
   def _BuildSmallModel(self):
-    a = tf.constant([[1, 2], [3, 4]])
-    b = tf.constant([[1, 2], [3, 4]])
-    return tf.matmul(a, b)
+    a = constant_op.constant([[1, 2], [3, 4]])
+    b = constant_op.constant([[1, 2], [3, 4]])
+    return math_ops.matmul(a, b)
 
   def testFillMissingShape(self):
     a, b, y = self._BuildSmallPlaceholderlModel()
-    run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
-    run_metadata = tf.RunMetadata()
-    sess = tf.Session()
+    run_options = config_pb2.RunOptions(
+        trace_level=config_pb2.RunOptions.FULL_TRACE)
+    run_metadata = config_pb2.RunMetadata()
+    sess = session.Session()
     sess.run(y,
              options=run_options,
              run_metadata=run_metadata,
              feed_dict={a: [[1, 2], [2, 3]],
                         b: [[1, 2], [2, 3]]})
 
-    graph2 = tf.Graph()
+    graph2 = ops.Graph()
     # Use copy_op_to_graph to remove shape information.
-    y2 = tf.contrib.copy_graph.copy_op_to_graph(y, graph2, [])
+    y2 = copy_elements.copy_op_to_graph(y, graph2, [])
     self.assertEquals('<unknown>', str(y2.get_shape()))
 
-    tf.contrib.tfprof.tfprof_logger._fill_missing_graph_shape(graph2,
-                                                              run_metadata)
+    tfprof_logger._fill_missing_graph_shape(graph2, run_metadata)
     self.assertEquals('(2, 2)', str(y2.get_shape()))
 
   def testFailedFillMissingShape(self):
     y = self._BuildSmallModel()
-    run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
-    run_metadata = tf.RunMetadata()
-    sess = tf.Session()
+    run_options = config_pb2.RunOptions(
+        trace_level=config_pb2.RunOptions.FULL_TRACE)
+    run_metadata = config_pb2.RunMetadata()
+    sess = session.Session()
     sess.run(y, options=run_options, run_metadata=run_metadata)
 
-    graph2 = tf.Graph()
-    y2 = tf.contrib.copy_graph.copy_op_to_graph(y, graph2, [])
+    graph2 = ops.Graph()
+    y2 = copy_elements.copy_op_to_graph(y, graph2, [])
     self.assertEquals('<unknown>', str(y2.get_shape()))
     # run_metadata has special name for MatMul, hence failed to fill shape.
-    tf.contrib.tfprof.tfprof_logger._fill_missing_graph_shape(graph2,
-                                                              run_metadata)
+    tfprof_logger._fill_missing_graph_shape(graph2, run_metadata)
     self.assertEquals('<unknown>', str(y2.get_shape()))
 
 
 if __name__ == '__main__':
-  tf.test.main()
+  test.main()