def test_audio(self):
with tf.compat.v1.Graph().as_default():
audio = tf.reshape(tf.linspace(0.0, 100.0, 4 * 10 * 2), (4, 10, 2))
old_op = tf.compat.v1.summary.audio("k488", audio, 44100)
old_value = self._value_from_op(old_op)
assert old_value.HasField("audio"), old_value
new_value = data_compat.migrate_value(old_value)
self.assertEqual("k488/audio/0", new_value.tag)
expected_metadata = audio_metadata.create_summary_metadata(
display_name="k488/audio/0",
description="",
encoding=audio_metadata.Encoding.Value("WAV"),
converted_to_tensor=True,
)
# Check serialized submessages...
plugin_content = audio_metadata.parse_plugin_metadata(
new_value.metadata.plugin_data.content)
expected_content = audio_metadata.parse_plugin_metadata(
expected_metadata.plugin_data.content)
self.assertEqual(plugin_content, expected_content)
# ...then check full metadata except plugin content, since
# serialized forms need not be identical.
new_value.metadata.plugin_data.content = (
expected_metadata.plugin_data.content)
self.assertEqual(expected_metadata, new_value.metadata)
self.assertTrue(new_value.HasField("tensor"))
data = tensor_util.make_ndarray(new_value.tensor)
self.assertEqual((1, 2), data.shape)
self.assertEqual(
tf.compat.as_bytes(old_value.audio.encoded_audio_string),
data[0][0])
self.assertEqual(b"", data[0][1]) # empty label
def test_metadata(self):
data = np.array(1, np.float32, ndmin=3)
description = "Piano Concerto No. 23 (K488), in **A major.**"
pb = self.audio("k488", data, 44100, description=description)
self.assertEqual(len(pb.value), 1)
summary_metadata = pb.value[0].metadata
self.assertEqual(summary_metadata.summary_description, description)
plugin_data = summary_metadata.plugin_data
self.assertEqual(plugin_data.plugin_name, metadata.PLUGIN_NAME)
content = summary_metadata.plugin_data.content
parsed = metadata.parse_plugin_metadata(content)
self.assertEqual(parsed.encoding, metadata.Encoding.Value("WAV"))
def test_metadata(self):
pb = self.compute_and_check_summary_pb('k488', self.stereo)
self.assertEqual(len(pb.value), 1)
self.assertEqual(pb.value[0].tag, 'k488/audio_summary')
summary_metadata = pb.value[0].metadata
self.assertEqual(summary_metadata.display_name, 'k488')
self.assertEqual(summary_metadata.summary_description, '')
plugin_data = summary_metadata.plugin_data
self.assertEqual(plugin_data.plugin_name, metadata.PLUGIN_NAME)
content = summary_metadata.plugin_data.content
parsed = metadata.parse_plugin_metadata(content)
self.assertEqual(parsed.encoding, metadata.Encoding.Value('WAV'))
def test_metadata(self):
pb = self.compute_and_check_summary_pb('k488', self.stereo)
self.assertEqual(len(pb.value), 1)
self.assertEqual(pb.value[0].tag, 'k488/audio_summary')
summary_metadata = pb.value[0].metadata
self.assertEqual(summary_metadata.display_name, 'k488')
self.assertEqual(summary_metadata.summary_description, '')
plugin_data = summary_metadata.plugin_data
self.assertEqual(plugin_data.plugin_name, metadata.PLUGIN_NAME)
content = summary_metadata.plugin_data.content
parsed = metadata.parse_plugin_metadata(content)
self.assertEqual(parsed.encoding, metadata.Encoding.Value('WAV'))
def _get_mime_type(self, ctx, experiment, run, tag):
# TODO(@wchargin): Move this call from `/audio` (called many
# times) to `/tags` (called few times) to reduce data provider
# calls.
mapping = self._data_provider.list_blob_sequences(
ctx, experiment_id=experiment, plugin_name=metadata.PLUGIN_NAME,
)
time_series = mapping.get(run, {}).get(tag, None)
if time_series is None:
raise errors.NotFoundError(
"No audio data for run=%r, tag=%r" % (run, tag)
)
parsed = metadata.parse_plugin_metadata(time_series.plugin_content)
return _MIME_TYPES.get(parsed.encoding, _DEFAULT_MIME_TYPE)
def test_metadata_with_explicit_name_and_description(self):
display_name = 'Piano Concerto No. 23 (K488)'
description = 'In **A major.**'
pb = self.compute_and_check_summary_pb(
'k488', self.stereo, display_name=display_name, description=description)
self.assertEqual(len(pb.value), 1)
self.assertEqual(pb.value[0].tag, 'k488/audio_summary')
summary_metadata = pb.value[0].metadata
self.assertEqual(summary_metadata.display_name, display_name)
self.assertEqual(summary_metadata.summary_description, description)
plugin_data = summary_metadata.plugin_data
self.assertEqual(plugin_data.plugin_name, metadata.PLUGIN_NAME)
content = summary_metadata.plugin_data.content
parsed = metadata.parse_plugin_metadata(content)
self.assertEqual(parsed.encoding, metadata.Encoding.Value('WAV'))
def _index_impl(self, ctx, experiment):
"""Return information about the tags in each run.
Result is a dictionary of the form
{
"runName1": {
"tagName1": {
"displayName": "The first tag",
"description": "<p>Long ago there was just one tag...</p>",
"samples": 3
},
"tagName2": ...,
...
},
"runName2": ...,
...
}
For each tag, `samples` is the greatest number of audio clips that
appear at any particular step. (It's not related to "samples of a
waveform.") For example, if for tag `minibatch_input` there are
five audio clips at step 0 and ten audio clips at step 1, then the
dictionary for `"minibatch_input"` will contain `"samples": 10`.
"""
mapping = self._data_provider.list_blob_sequences(
ctx,
experiment_id=experiment,
plugin_name=metadata.PLUGIN_NAME,
)
result = {run: {} for run in mapping}
for (run, tag_to_time_series) in mapping.items():
for (tag, time_series) in tag_to_time_series.items():
md = metadata.parse_plugin_metadata(time_series.plugin_content)
if not self._version_checker.ok(md.version, run, tag):
continue
description = plugin_util.markdown_to_safe_html(
time_series.description
)
result[run][tag] = {
"displayName": time_series.display_name,
"description": description,
"samples": time_series.max_length,
}
return result
def _get_mime_type(self, run, tag):
content = self._multiplexer.SummaryMetadata(
run, tag
).plugin_data.content
parsed = metadata.parse_plugin_metadata(content)
return _MIME_TYPES.get(parsed.encoding, _DEFAULT_MIME_TYPE)
def _get_mime_type(self, run, tag): content = self._multiplexer.SummaryMetadata(run, tag).plugin_data.content parsed = metadata.parse_plugin_metadata(content) return _MIME_TYPES.get(parsed.encoding, _DEFAULT_MIME_TYPE)
