text: """Test AdaNet summary single graph implementation for TF 1.
  
  Copyright 2018 The AdaNet 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
  
      https://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.
  """
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import functools
  import os
  
  from absl.testing import parameterized
  from adanet import tf_compat
  from adanet.core import testing_utils as tu
  from adanet.core.summary import _ScopedSummary
  from adanet.core.summary import _TPUScopedSummary
  from adanet.core.summary import monkey_patched_summaries
  from six.moves import range
  import tensorflow as tf
  
  # pylint: disable=g-direct-tensorflow-import
  from tensorflow.python.ops import summary_ops_v2
  # pylint: enable=g-direct-tensorflow-import
  
  
  
  
  def decode(proto_str):
    """Decodes a proto string."""
  
    return proto_str.decode("utf-8")
  
  
  class ScopedSummaryTest(parameterized.TestCase, tf.test.TestCase):
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_scope(self, scope):
      scoped_summary = _ScopedSummary(scope)
      self.assertEqual(scope, scoped_summary.scope)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_scalar_summary(self, scope, skip_summary=False):
      scoped_summary = _ScopedSummary(scope, skip_summary)
      with self.test_session() as s:
        i = tf.constant(3)
        with tf.name_scope("outer"):
          im = scoped_summary.scalar("inner", i)
        summary_str = s.run(im)
      if skip_summary:
        self.assertEqual("", decode(summary_str))
        return
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      values = summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "outer/inner")
      self.assertEqual(values[0].simple_value, 3.0)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_scalar_summary_with_family(self, scope):
      scoped_summary = _ScopedSummary(scope)
      with self.test_session() as s:
        i = tf.constant(7)
        with tf.name_scope("outer"):
          im1 = scoped_summary.scalar("inner", i, family="family")
          im2 = scoped_summary.scalar("inner", i, family="family")
        sm1, sm2 = s.run([im1, im2])
      summary = tf.Summary()
  
      summary.ParseFromString(sm1)
      values = summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "family/outer/family/inner")
      self.assertEqual(values[0].simple_value, 7.0)
  
      summary.ParseFromString(sm2)
      values = summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "family/outer/family/inner_1")
      self.assertEqual(values[0].simple_value, 7.0)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_summarizing_variable(self, scope):
      scoped_summary = _ScopedSummary(scope)
      with self.test_session() as s:
        c = tf.constant(42.0)
        v = tf.Variable(c)
        ss = scoped_summary.scalar("summary", v)
        init = tf.global_variables_initializer()
        s.run(init)
        summ_str = s.run(ss)
      summary = tf.Summary()
      summary.ParseFromString(summ_str)
      self.assertLen(summary.value, 1)
      value = summary.value[0]
      self.assertEqual(value.tag, "summary")
      self.assertEqual(value.simple_value, 42.0)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_image_summary(self, scope, skip_summary=False):
      scoped_summary = _ScopedSummary(scope, skip_summary)
      with self.test_session() as s:
        i = tf.ones((5, 4, 4, 3))
        with tf.name_scope("outer"):
          im = scoped_summary.image("inner", i, max_outputs=3)
        summary_str = s.run(im)
      if skip_summary:
        self.assertEqual("", decode(summary_str))
        return
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      values = summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted("outer/inner/image/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_image_summary_with_family(self, scope):
      scoped_summary = _ScopedSummary(scope)
      with self.test_session() as s:
        i = tf.ones((5, 2, 3, 1))
        with tf.name_scope("outer"):
          im = scoped_summary.image("inner", i, max_outputs=3, family="family")
        summary_str = s.run(im)
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      values = summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted(
          "family/outer/family/inner/image/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_histogram_summary(self, scope, skip_summary=False):
      scoped_summary = _ScopedSummary(scope, skip_summary)
      with self.test_session() as s:
        i = tf.ones((5, 4, 4, 3))
        with tf.name_scope("outer"):
          summ_op = scoped_summary.histogram("inner", i)
        summary_str = s.run(summ_op)
      if skip_summary:
        self.assertEqual("", decode(summary_str))
        return
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      self.assertLen(summary.value, 1)
      self.assertEqual(summary.value[0].tag, "outer/inner")
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_histogram_summary_with_family(self, scope):
      scoped_summary = _ScopedSummary(scope)
      with self.test_session() as s:
        i = tf.ones((5, 4, 4, 3))
        with tf.name_scope("outer"):
          summ_op = scoped_summary.histogram("inner", i, family="family")
        summary_str = s.run(summ_op)
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      self.assertLen(summary.value, 1)
      self.assertEqual(summary.value[0].tag, "family/outer/family/inner")
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_audio_summary(self, scope, skip_summary=False):
      scoped_summary = _ScopedSummary(scope, skip_summary)
      with self.test_session() as s:
        i = tf.ones((5, 3, 4))
        with tf.name_scope("outer"):
          aud = scoped_summary.audio("inner", i, 0.2, max_outputs=3)
        summary_str = s.run(aud)
      if skip_summary:
        self.assertEqual("", decode(summary_str))
        return
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      values = summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted("outer/inner/audio/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_audio_summary_with_family(self, scope):
      scoped_summary = _ScopedSummary(scope)
      with self.test_session() as s:
        i = tf.ones((5, 3, 4))
        with tf.name_scope("outer"):
          aud = scoped_summary.audio(
              "inner", i, 0.2, max_outputs=3, family="family")
        summary_str = s.run(aud)
      summary = tf.Summary()
      summary.ParseFromString(summary_str)
      values = summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted(
          "family/outer/family/inner/audio/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_summary_name_conversion(self, scope):
      scoped_summary = _ScopedSummary(scope)
      c = tf.constant(3)
      summary = tf.Summary()
  
      with self.test_session() as sess:
        s = scoped_summary.scalar("name with spaces", c)
        summary.ParseFromString(sess.run(s))
        self.assertEqual(summary.value[0].tag, "name_with_spaces")
  
        s2 = scoped_summary.scalar("name with many $#illegal^: characters!", c)
        summary.ParseFromString(sess.run(s2))
        self.assertEqual(summary.value[0].tag,
                         "name_with_many___illegal___characters_")
  
        s3 = scoped_summary.scalar("/name/with/leading/slash", c)
        summary.ParseFromString(sess.run(s3))
        self.assertEqual(summary.value[0].tag, "name/with/leading/slash")
  
    @parameterized.named_parameters(
        {
            "testcase_name": "single_graph",
            "nest_graph": False,
        }, {
            "testcase_name": "nested_graph",
            "nest_graph": True,
        })
    @tf_compat.skip_for_tf2
    def test_merge_all(self, nest_graph):
      c0 = tf.constant(0)
      c1 = tf.constant(1)
  
      scoped_summary0 = _ScopedSummary()
      scoped_summary0.scalar("c0", c0)
      scoped_summary0.scalar("c1", c1)
  
      scoped_summary1 = _ScopedSummary("scope1")
      scoped_summary1.scalar("c0", c0)
      scoped_summary1.scalar("c1", c1)
  
      scoped_summary2 = _ScopedSummary("scope2")
      scoped_summary2.scalar("c0", c0)
      scoped_summary2.scalar("c1", c1)
  
      config = tf.ConfigProto(gpu_options=tf.GPUOptions(allow_growth=True))
  
      if nest_graph:
        with tf.Graph().as_default():
          scoped_summary2.scalar("c2", tf.constant(2))
          with tf.Session(config=config) as sess:
            summaries = scoped_summary2.merge_all()
            tf.logging.warn("summaries %s", summaries)
            summary = tf.Summary()
            summary.ParseFromString(sess.run(tf.summary.merge(summaries)))
            self.assertEqual(["c2"], [s.tag for s in summary.value])
            self.assertEqual([2], [s.simple_value for s in summary.value])
  
      with tf.Session(config=config) as sess:
        for scoped_summary in [scoped_summary0, scoped_summary1, scoped_summary2]:
          summaries = scoped_summary.merge_all()
          summary = tf.Summary()
          summary.ParseFromString(sess.run(tf.summary.merge(summaries)))
          self.assertEqual(["c0", "c1"], [s.tag for s in summary.value])
          self.assertEqual([0, 1], [s.simple_value for s in summary.value])
  
    @tf_compat.skip_for_tf2
    def test_summary_args(self):
      summary = _ScopedSummary()
      summary.scalar("scalar", 1, "family")
      summary.image("image", 1, 3, "family")
      summary.histogram("histogram", 1, "family")
      summary.audio("audio", 1, 3, 3, "family")
      self.assertLen(summary.merge_all(), 4)
  
    @tf_compat.skip_for_tf2
    def test_summary_kwargs(self):
      summary = _ScopedSummary()
      summary.scalar(name="scalar", tensor=1, family="family")
      summary.image(name="image", tensor=1, max_outputs=3, family="family")
      summary.histogram(name="histogram", values=1, family="family")
      summary.audio(
          name="audio", tensor=1, sample_rate=3, max_outputs=3, family="family")
      self.assertLen(summary.merge_all(), 4)
  
  
  class TPUScopedSummaryTest(tu.AdanetTestCase):
  
    def read_single_event_from_eventfile(self, summary):
      dir_ = self.test_subdirectory
      if summary.namespace:
        dir_ = os.path.join(dir_, summary.namespace)
      if summary.scope:
        dir_ = os.path.join(dir_, summary.scope)
      event_files = sorted(tf.gfile.Glob(os.path.join(dir_, "*.v2")))
      events = list(tf.train.summary_iterator(event_files[-1]))
      # Expect a boilerplate event for the file_version, then the summary one.
      self.assertGreaterEqual(len(events), 2)
      return events[1:]
  
    def write_summaries(self, summary):
      summary_ops = []
      writer = summary_ops_v2.create_file_writer(summary.logdir)
      with writer.as_default(), summary_ops_v2.always_record_summaries():
        for summary_fn, tensor in summary.summary_tuples():
          summary_ops.append(summary_fn(tensor, step=10))
  
      with self.test_session() as sess:
        sess.run(tf.global_variables_initializer())
        sess.run(summary_ops_v2.summary_writer_initializer_op())
        sess.run(summary_ops)
        sess.run(writer.flush())
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_scope(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      self.assertEqual(scope, scoped_summary.scope)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_scalar_summary(self, scope, skip_summary=False):
      scoped_summary = _TPUScopedSummary(
          self.test_subdirectory, scope=scope, skip_summary=skip_summary)
      i = tf.constant(3)
      with tf.name_scope("outer"):
        scoped_summary.scalar("inner", i)
      self.write_summaries(scoped_summary)
      if skip_summary:
        return
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "outer/inner")
      self.assertEqual(values[0].simple_value, 3.0)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_scalar_summary_with_family(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      i = tf.constant(7)
      with tf.name_scope("outer"):
        scoped_summary.scalar("inner", i, family="family")
        scoped_summary.scalar("inner", i, family="family")
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      self.assertLen(events[0].summary.value, 1)
      self.assertLen(events[1].summary.value, 1)
  
      self.assertEqual(
          {
              "family/outer/family/inner": 7.0,
              "family/outer/family/inner_1": 7.0
          }, {
              event.summary.value[0].tag: event.summary.value[0].simple_value
              for event in events
          })
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_summarizing_variable(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      c = tf.constant(42.0)
      v = tf.Variable(c)
      scoped_summary.scalar("summary", v)
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 1)
      value = values[0]
      self.assertEqual(value.tag, "summary")
      self.assertEqual(value.simple_value, 42.0)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_image_summary(self, scope, skip_summary=False):
      scoped_summary = _TPUScopedSummary(
          self.test_subdirectory, scope=scope, skip_summary=skip_summary)
      i = tf.ones((5, 4, 4, 3))
      with tf.name_scope("outer"):
        scoped_summary.image("inner", i, max_outputs=3)
      self.write_summaries(scoped_summary)
      if skip_summary:
        return
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted("outer/inner/image/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_image_summary_with_family(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      i = tf.ones((5, 2, 3, 1))
      with tf.name_scope("outer"):
        scoped_summary.image("inner", i, max_outputs=3, family="family")
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted(
          "family/outer/family/inner/image/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_histogram_summary(self, scope, skip_summary=False):
      scoped_summary = _TPUScopedSummary(
          self.test_subdirectory, scope=scope, skip_summary=skip_summary)
      i = tf.ones((5, 4, 4, 3))
      with tf.name_scope("outer"):
        scoped_summary.histogram("inner", i)
      self.write_summaries(scoped_summary)
      if skip_summary:
        return
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "outer/inner")
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_histogram_summary_with_family(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      i = tf.ones((5, 4, 4, 3))
      with tf.name_scope("outer"):
        scoped_summary.histogram("inner", i, family="family")
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "family/outer/family/inner")
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        }, {
            "testcase_name": "skip_summary",
            "scope": None,
            "skip_summary": True,
        })
    @tf_compat.skip_for_tf2
    def test_audio_summary(self, scope, skip_summary=False):
      scoped_summary = _TPUScopedSummary(
          self.test_subdirectory, scope=scope, skip_summary=skip_summary)
      i = tf.ones((5, 3, 4))
      with tf.name_scope("outer"):
        scoped_summary.audio("inner", i, 0.2, max_outputs=3)
      self.write_summaries(scoped_summary)
      if skip_summary:
        return
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted("outer/inner/audio/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_audio_summary_with_family(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      i = tf.ones((5, 3, 4))
      with tf.name_scope("outer"):
        scoped_summary.audio("inner", i, 0.2, max_outputs=3, family="family")
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 3)
      tags = sorted(v.tag for v in values)
      expected = sorted(
          "family/outer/family/inner/audio/{}".format(i) for i in range(3))
      self.assertEqual(tags, expected)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_summary_name_conversion(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      c = tf.constant(3)
      scoped_summary.scalar("name with spaces", c)
      scoped_summary.scalar("name with many $#illegal^: characters!", c)
      scoped_summary.scalar("/name/with/leading/slash", c)
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      self.assertLen(events, 3)
      tags = [event.summary.value[0].tag for event in events]
      self.assertIn("name_with_spaces", tags)
      self.assertIn("name_with_many___illegal___characters_", tags)
      self.assertIn("name/with/leading/slash", tags)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "without_scope",
            "scope": None,
        }, {
            "testcase_name": "with_scope",
            "scope": "with_scope",
        })
    @tf_compat.skip_for_tf2
    def test_current_scope(self, scope):
      scoped_summary = _TPUScopedSummary(self.test_subdirectory, scope=scope)
      i = tf.constant(3)
      with tf.variable_scope("outer1"):
        with tf.variable_scope("outer2"):
          with scoped_summary.current_scope():
            with tf.variable_scope("inner1"):
              scoped_summary.scalar("inner2/a/b/c", i)
      self.write_summaries(scoped_summary)
      events = self.read_single_event_from_eventfile(scoped_summary)
      values = events[0].summary.value
      self.assertLen(values, 1)
      self.assertEqual(values[0].tag, "inner1/inner2/a/b/c")
      self.assertEqual(values[0].simple_value, 3.0)
  
    @tf_compat.skip_for_tf2
    def test_summary_args(self):
      summary = _TPUScopedSummary(self.test_subdirectory)
      summary.scalar("scalar", 1, "family")
      summary.image("image", 1, 3, "family")
      summary.histogram("histogram", 1, "family")
      summary.audio("audio", 1, 3, 3, "family")
      self.assertLen(summary.summary_tuples(), 4)
  
    @tf_compat.skip_for_tf2
    def test_summary_kwargs(self):
      summary = _TPUScopedSummary(self.test_subdirectory)
      summary.scalar(name="scalar", tensor=1, family="family")
      summary.image(name="image", tensor=1, max_outputs=3, family="family")
      summary.histogram(name="histogram", values=1, family="family")
      summary.audio(
          name="audio", tensor=1, sample_rate=3, max_outputs=3, family="family")
      self.assertLen(summary.summary_tuples(), 4)
  
  
  def _summaries():
    """Returns all summary functions."""
  
    fns = [
        tf.summary.scalar, tf.summary.audio, tf.summary.histogram,
        tf.summary.image, tf_compat.v1.summary.scalar, tf_compat.v1.summary.audio,
        tf_compat.v1.summary.histogram, tf_compat.v1.summary.image,
        tf_compat.v2.summary.scalar, tf_compat.v2.summary.audio,
        tf_compat.v2.summary.histogram, tf_compat.v2.summary.image
    ]
    try:
      fns += [
          tf.contrib.summary.scalar, tf.contrib.summary.audio,
          tf.contrib.summary.histogram, tf.contrib.summary.image
      ]
    except (AttributeError, ImportError):
      # TF 2.0 eliminates tf.contrib.
      pass
    return fns
  
  
  class MonkeyPatchTest(parameterized.TestCase, tf.test.TestCase):
  
    def _get_summary_ops(self, summary):
      if isinstance(summary, _TPUScopedSummary):
        return [fn(arg, step=10) for fn, arg in summary.summary_tuples()]
      return summary.merge_all()
  
    @parameterized.named_parameters(
        {
            "testcase_name": "with_scoped_summary",
            "summary_maker": _ScopedSummary,
        }, {
            "testcase_name":
                "with_tpu_scoped_summary",
            "summary_maker":
                functools.partial(_TPUScopedSummary, logdir="/tmp/fakedir")
        })
    @tf_compat.skip_for_tf2
    def test_monkey_patched_summaries_args(self, summary_maker):
      summary = summary_maker()
      before = _summaries()
      with monkey_patched_summaries(summary):
        for want, got in zip(before, _summaries()):
          self.assertNotEqual(want, got)
        tf.summary.scalar("scalar", 1, ["collection"], "family")
        tf.summary.image("image", 1, 3, ["collection"], "family")
        tf.summary.histogram("histogram", 1, ["collection"], "family")
        tf.summary.audio("audio", 1, 3, 3, ["collection"], "family")
  
        want_summary_fn_count = 4
        try:
          tf.contrib.summary.scalar("scalar_v2", 1, "family", 10)
          tf.contrib.summary.image("image_v2", 1, True, 3, "family", 10)
          tf.contrib.summary.histogram("histogram_v2", 1, "family", 10)
          tf.contrib.summary.audio("audio_v2", 1, 3, 3, "family", 10)
          want_summary_fn_count += 4
        except (AttributeError, ImportError):
          # TF 2.0 eliminates tf.contrib.
          pass
      self.assertEqual(before, _summaries())
      self.assertLen(self._get_summary_ops(summary), want_summary_fn_count)
  
    @parameterized.named_parameters(
        {
            "testcase_name": "with_scoped_summary",
            "summary_maker": _ScopedSummary,
        }, {
            "testcase_name":
                "with_tpu_scoped_summary",
            "summary_maker":
                functools.partial(_TPUScopedSummary, logdir="/tmp/fakedir"),
        })
    @tf_compat.skip_for_tf2
    def test_monkey_patched_summaries_kwargs(self, summary_maker):
      summary = summary_maker()
      before = _summaries()
      with monkey_patched_summaries(summary):
        for want, got in zip(before, _summaries()):
          self.assertNotEqual(want, got)
        tf.summary.scalar(
            name="scalar", tensor=1, collections=["collection"], family="family")
        tf.summary.image(
            name="image",
            tensor=1,
            max_outputs=3,
            collections=["collection"],
            family="family")
        tf.summary.histogram(
            name="histogram",
            values=1,
            collections=["collection"],
            family="family")
        tf.summary.audio(
            name="audio",
            tensor=1,
            sample_rate=3,
            max_outputs=3,
            collections=["collection"],
            family="family")
  
        want_summary_fn_count = 4
        try:
          tf.contrib.summary.scalar(
              name="scalar_v2", tensor=1, family="family", step=10)
          tf.contrib.summary.image(
              name="image_v2",
              tensor=1,
              bad_color=True,
              max_images=3,
              family="family",
              step=10)
          tf.contrib.summary.histogram(
              name="histogram_v2", tensor=1, family="family", step=10)
          tf.contrib.summary.audio(
              name="audio_v2",
              tensor=1,
              sample_rate=3,
              max_outputs=3,
              family="family",
              step=10)
          want_summary_fn_count += 4
        except (AttributeError, ImportError):
          # TF 2.0 eliminates tf.contrib.
          pass
      self.assertEqual(before, _summaries())
      self.assertLen(self._get_summary_ops(summary), want_summary_fn_count)
  
  
  if __name__ == "__main__":
    tf.test.main()
  