Rollback of "Adding histogram_ops module containing one Op: histogram_fixed_width, which updates a histogram Variable with new_values."

Change: 112800368

3 files changed, 0 insertions, 175 deletions

diff --git a/tensorflow/python/BUILD b/tensorflow/python/BUILD
index 5ade3d8c17..de7c6d2453 100644
--- a/tensorflow/python/BUILD
+++ b/tensorflow/python/BUILD
@@ -699,7 +699,6 @@ py_library(
         "ops/gen_string_ops.py",
         "ops/gen_summary_ops.py",
         "ops/gradients.py",
-        "ops/histogram_ops.py",
         "ops/image_grad.py",
         "ops/image_ops.py",
         "ops/init_ops.py",
diff --git a/tensorflow/python/ops/histogram_ops.py b/tensorflow/python/ops/histogram_ops.py
deleted file mode 100644
index f15d1c5cad..0000000000
--- a/tensorflow/python/ops/histogram_ops.py
+++ /dev/null
@@ -1,94 +0,0 @@
-# Copyright 2015 Google Inc. 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.
-# ==============================================================================
-"""Operations for histograms."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import ops
-from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import clip_ops
-from tensorflow.python.ops import math_ops
-from tensorflow.python.ops import state_ops
-
-
-def histogram_fixed_width(hist,
-                          new_values,
-                          value_range,
-                          use_locking=False,
-                          name='histogram_fixed_width'):
-  """Update histogram Variable with new values.
-
-  This Op fills histogram with counts of values falling within fixed-width,
-  half-open bins.
-
-  Args:
-    hist:  1-D mutable `Tensor`, e.g. a `Variable`.
-    new_values:  Numeric `Tensor`.
-    value_range:  Shape [2] `Tensor`.  new_values <= value_range[0] will be
-      mapped to hist[0], values >= value_range[1] will be mapped to hist[-1].
-      Must be same dtype as new_values.
-    use_locking:  Boolean.
-      If `True`, use locking during the operation (optional).
-    name:  A name for this operation (optional).
-
-  Returns:
-    An op that updates `hist` with `new_values` when evaluated.
-
-  Examples:
-  ```python
-  # Bins will be:  (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf)
-  nbins = 5
-  value_range = [0.0, 5.0]
-  new_values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]
-
-  with tf.default_session() as sess:
-    hist = variables.Variable(array_ops.zeros(nbins, dtype=tf.int32))
-    hist_update = histogram_ops.histogram_fixed_width(hist, new_values,
-                                                      value_range)
-    variables.initialize_all_variables().run()
-    sess.run(hist_update) => [2, 1, 1, 0, 2]
-  ```
-  """
-  with ops.op_scope([hist, new_values, value_range], name) as scope:
-    new_values = ops.convert_to_tensor(new_values, name='new_values')
-    value_range = ops.convert_to_tensor(value_range, name='value_range')
-    dtype = hist.dtype
-
-    # Map tensor values that fall within value_range to [0, 1].
-    scaled_values = math_ops.truediv(new_values - value_range[0],
-                                     value_range[1] - value_range[0],
-                                     name='scaled_values')
-    nbins = math_ops.cast(hist.get_shape()[0], scaled_values.dtype)
-
-    # map tensor values within the open interval value_range to {0,.., nbins-1},
-    # values outside the open interval will be zero or less, or nbins or more.
-    indices = math_ops.floor(nbins * scaled_values, name='indices')
-
-    # Clip edge cases (e.g. value = value_range[1]) or "outliers."
-    indices = math_ops.cast(
-        clip_ops.clip_by_value(indices, 0, nbins - 1), dtypes.int32)
-
-    # Dummy vector to scatter.
-    # TODO(langmore) Replace non-ideal creation of large dummy vector once an
-    # alternative to scatter is available.
-    updates = array_ops.ones(indices.get_shape()[0], dtype=dtype)
-    return state_ops.scatter_add(hist,
-                                 indices,
-                                 updates,
-                                 use_locking=use_locking,
-                                 name=scope)
diff --git a/tensorflow/python/ops/histogram_ops_test.py b/tensorflow/python/ops/histogram_ops_test.py
deleted file mode 100644
index 3b5ca3c748..0000000000
--- a/tensorflow/python/ops/histogram_ops_test.py
+++ /dev/null
@@ -1,80 +0,0 @@
-# Copyright 2015 Google Inc. 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.
-# ==============================================================================
-
-"""Tests for tensorflow.ops.histogram_ops."""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import test_util
-from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import histogram_ops
-from tensorflow.python.ops import variables
-from tensorflow.python.platform import googletest
-
-
-class HistogramFixedWidthTest(test_util.TensorFlowTestCase):
-
-  def test_one_update_on_constant_input(self):
-    # Bins will be:
-    #   (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf)
-    nbins = 5
-    value_range = [0.0, 5.0]
-    new_values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]
-    expected_bin_counts = [2, 1, 1, 0, 2]
-    with self.test_session() as sess:
-      hist = variables.Variable(array_ops.zeros(nbins, dtype=dtypes.int32))
-      hist_update = histogram_ops.histogram_fixed_width(hist, new_values,
-                                                        value_range)
-      variables.initialize_all_variables().run()
-      self.assertTrue(hist.dtype.is_compatible_with(hist_update.dtype))
-      updated_hist_array = sess.run(hist_update)
-
-      # The new updated_hist_array is returned by the updating op.
-      self.assertAllClose(expected_bin_counts, updated_hist_array)
-
-      # hist should contain updated values, but eval() should not change it.
-      self.assertAllClose(expected_bin_counts, hist.eval())
-      self.assertAllClose(expected_bin_counts, hist.eval())
-
-  def test_two_updates_on_constant_input(self):
-    # Bins will be:
-    #   (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf)
-    nbins = 5
-    value_range = [0.0, 5.0]
-    new_values_1 = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]
-    new_values_2 = [1.5, 4.5, 4.5, 4.5, 0.0, 0.0]
-    expected_bin_counts_1 = [2, 1, 1, 0, 2]
-    expected_bin_counts_2 = [4, 2, 1, 0, 5]
-    with self.test_session() as sess:
-      hist = variables.Variable(array_ops.zeros(nbins, dtype=dtypes.int32))
-      new_values = array_ops.placeholder(dtypes.float32, shape=[6])
-      hist_update = histogram_ops.histogram_fixed_width(hist, new_values,
-                                                        value_range)
-      variables.initialize_all_variables().run()
-      updated_hist_array = sess.run(hist_update,
-                                    feed_dict={new_values: new_values_1})
-      self.assertAllClose(expected_bin_counts_1, updated_hist_array)
-      self.assertAllClose(expected_bin_counts_1, hist.eval())
-
-      updated_hist_array = sess.run(hist_update,
-                                    feed_dict={new_values: new_values_2})
-      self.assertAllClose(expected_bin_counts_2, updated_hist_array)
-      self.assertAllClose(expected_bin_counts_2, hist.eval())
-
-
-if __name__ == '__main__':
-  googletest.main()