Allow numpy_input_fn to take an ndarray representing a single input feature.

PiperOrigin-RevId: 182397583

2 files changed, 0 insertions, 294 deletions

diff --git a/tensorflow/contrib/learn/BUILD b/tensorflow/contrib/learn/BUILD
index 0e87c36dcd..ee3611ca93 100644
--- a/tensorflow/contrib/learn/BUILD
+++ b/tensorflow/contrib/learn/BUILD
@@ -751,20 +751,6 @@ tf_py_test(
 )
 
 py_test(
-    name = "numpy_io_test",
-    size = "small",
-    srcs = ["python/learn/learn_io/numpy_io_test.py"],
-    srcs_version = "PY2AND3",
-    deps = [
-        ":learn",
-        "//tensorflow/python:client_testlib",
-        "//tensorflow/python:errors",
-        "//tensorflow/python:training",
-        "//third_party/py/numpy",
-    ],
-)
-
-py_test(
     name = "pandas_io_test",
     size = "small",
     srcs = ["python/learn/learn_io/pandas_io_test.py"],
diff --git a/tensorflow/contrib/learn/python/learn/learn_io/numpy_io_test.py b/tensorflow/contrib/learn/python/learn/learn_io/numpy_io_test.py
deleted file mode 100644
index 6fe8de8705..0000000000
--- a/tensorflow/contrib/learn/python/learn/learn_io/numpy_io_test.py
+++ /dev/null
@@ -1,280 +0,0 @@
-# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Tests for numpy_io."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-
-from tensorflow.contrib.learn.python.learn.learn_io import numpy_io
-from tensorflow.python.framework import errors
-from tensorflow.python.platform import test
-from tensorflow.python.training import coordinator
-from tensorflow.python.training import queue_runner_impl
-
-
-class NumpyIoTest(test.TestCase):
-
-  def testNumpyInputFn(self):
-    a = np.arange(4) * 1.0
-    b = np.arange(32, 36)
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -28)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=2, shuffle=False, num_epochs=1)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [0, 1])
-      self.assertAllEqual(res[0]['b'], [32, 33])
-      self.assertAllEqual(res[1], [-32, -31])
-
-      session.run([features, target])
-      with self.assertRaises(errors.OutOfRangeError):
-        session.run([features, target])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithVeryLargeBatchSizeAndMultipleEpochs(self):
-    a = np.arange(2) * 1.0
-    b = np.arange(32, 34)
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -30)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=128, shuffle=False, num_epochs=2)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [0, 1, 0, 1])
-      self.assertAllEqual(res[0]['b'], [32, 33, 32, 33])
-      self.assertAllEqual(res[1], [-32, -31, -32, -31])
-
-      with self.assertRaises(errors.OutOfRangeError):
-        session.run([features, target])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithZeroEpochs(self):
-    a = np.arange(4) * 1.0
-    b = np.arange(32, 36)
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -28)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=2, shuffle=False, num_epochs=0)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      with self.assertRaises(errors.OutOfRangeError):
-        session.run([features, target])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithBatchSizeNotDividedByDataSize(self):
-    batch_size = 2
-    a = np.arange(5) * 1.0
-    b = np.arange(32, 37)
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -27)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=batch_size, shuffle=False, num_epochs=1)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [0, 1])
-      self.assertAllEqual(res[0]['b'], [32, 33])
-      self.assertAllEqual(res[1], [-32, -31])
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [2, 3])
-      self.assertAllEqual(res[0]['b'], [34, 35])
-      self.assertAllEqual(res[1], [-30, -29])
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [4])
-      self.assertAllEqual(res[0]['b'], [36])
-      self.assertAllEqual(res[1], [-28])
-
-      with self.assertRaises(errors.OutOfRangeError):
-        session.run([features, target])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithBatchSizeNotDividedByDataSizeAndMultipleEpochs(self):
-    batch_size = 2
-    a = np.arange(3) * 1.0
-    b = np.arange(32, 35)
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -29)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=batch_size, shuffle=False, num_epochs=3)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [0, 1])
-      self.assertAllEqual(res[0]['b'], [32, 33])
-      self.assertAllEqual(res[1], [-32, -31])
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [2, 0])
-      self.assertAllEqual(res[0]['b'], [34, 32])
-      self.assertAllEqual(res[1], [-30, -32])
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [1, 2])
-      self.assertAllEqual(res[0]['b'], [33, 34])
-      self.assertAllEqual(res[1], [-31, -30])
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [0, 1])
-      self.assertAllEqual(res[0]['b'], [32, 33])
-      self.assertAllEqual(res[1], [-32, -31])
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [2])
-      self.assertAllEqual(res[0]['b'], [34])
-      self.assertAllEqual(res[1], [-30])
-
-      with self.assertRaises(errors.OutOfRangeError):
-        session.run([features, target])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithBatchSizeLargerThanDataSize(self):
-    batch_size = 10
-    a = np.arange(4) * 1.0
-    b = np.arange(32, 36)
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -28)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=batch_size, shuffle=False, num_epochs=1)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [0, 1, 2, 3])
-      self.assertAllEqual(res[0]['b'], [32, 33, 34, 35])
-      self.assertAllEqual(res[1], [-32, -31, -30, -29])
-
-      with self.assertRaises(errors.OutOfRangeError):
-        session.run([features, target])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithDifferentDimensionsOfFeatures(self):
-    a = np.array([[1, 2], [3, 4]])
-    b = np.array([5, 6])
-    x = {'a': a, 'b': b}
-    y = np.arange(-32, -30)
-
-    with self.test_session() as session:
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=2, shuffle=False, num_epochs=1)
-      features, target = input_fn()
-
-      coord = coordinator.Coordinator()
-      threads = queue_runner_impl.start_queue_runners(session, coord=coord)
-
-      res = session.run([features, target])
-      self.assertAllEqual(res[0]['a'], [[1, 2], [3, 4]])
-      self.assertAllEqual(res[0]['b'], [5, 6])
-      self.assertAllEqual(res[1], [-32, -31])
-
-      coord.request_stop()
-      coord.join(threads)
-
-  def testNumpyInputFnWithXAsNonDict(self):
-    x = np.arange(32, 36)
-    y = np.arange(4)
-    with self.test_session():
-      with self.assertRaisesRegexp(TypeError, 'x must be dict'):
-        failing_input_fn = numpy_io.numpy_input_fn(
-            x, y, batch_size=2, shuffle=False, num_epochs=1)
-        failing_input_fn()
-
-  def testNumpyInputFnWithTargetKeyAlreadyInX(self):
-    array = np.arange(32, 36)
-    x = {'__target_key__': array}
-    y = np.arange(4)
-
-    with self.test_session():
-      input_fn = numpy_io.numpy_input_fn(
-          x, y, batch_size=2, shuffle=False, num_epochs=1)
-      input_fn()
-      self.assertAllEqual(x['__target_key__'], array)
-      self.assertItemsEqual(x.keys(), ['__target_key__'])
-
-  def testNumpyInputFnWithMismatchLengthOfInputs(self):
-    a = np.arange(4) * 1.0
-    b = np.arange(32, 36)
-    x = {'a': a, 'b': b}
-    x_mismatch_length = {'a': np.arange(1), 'b': b}
-    y_longer_length = np.arange(10)
-
-    with self.test_session():
-      with self.assertRaisesRegexp(
-          ValueError, 'Length of tensors in x and y is mismatched.'):
-        failing_input_fn = numpy_io.numpy_input_fn(
-            x, y_longer_length, batch_size=2, shuffle=False, num_epochs=1)
-        failing_input_fn()
-
-      with self.assertRaisesRegexp(
-          ValueError, 'Length of tensors in x and y is mismatched.'):
-        failing_input_fn = numpy_io.numpy_input_fn(
-            x=x_mismatch_length,
-            y=None,
-            batch_size=2,
-            shuffle=False,
-            num_epochs=1)
-        failing_input_fn()
-
-
-if __name__ == '__main__':
-  test.main()