def testGetPluginAsset(self): epa = plugin_asset.get_plugin_asset(_ExamplePluginAsset) self.assertIsInstance(epa, _ExamplePluginAsset) epa2 = plugin_asset.get_plugin_asset(_ExamplePluginAsset) self.assertIs(epa, epa2) opa = plugin_asset.get_plugin_asset(_OtherExampleAsset) self.assertIsNot(epa, opa)
def testGetPluginAsset(self):
epa = plugin_asset.get_plugin_asset(_ExamplePluginAsset)
self.assertIsInstance(epa, _ExamplePluginAsset)
epa2 = plugin_asset.get_plugin_asset(_ExamplePluginAsset)
self.assertIs(epa, epa2)
opa = plugin_asset.get_plugin_asset(_OtherExampleAsset)
self.assertIsNot(epa, opa)
def testRespectsGraphArgument(self):
g1 = ops.Graph()
g2 = ops.Graph()
e1 = plugin_asset.get_plugin_asset(_ExamplePluginAsset, g1)
e2 = plugin_asset.get_plugin_asset(_ExamplePluginAsset, g2)
self.assertEqual(e1, plugin_asset.get_all_plugin_assets(g1)[0])
self.assertEqual(e2, plugin_asset.get_all_plugin_assets(g2)[0])
def testRespectsGraphArgument(self):
g1 = ops.Graph()
g2 = ops.Graph()
e1 = plugin_asset.get_plugin_asset(_ExamplePluginAsset, g1)
e2 = plugin_asset.get_plugin_asset(_ExamplePluginAsset, g2)
self.assertEqual(e1, plugin_asset.get_all_plugin_assets(g1)[0])
self.assertEqual(e2, plugin_asset.get_all_plugin_assets(g2)[0])
def testEndpointsNoAssets(self):
g = ops.Graph()
with g.as_default():
plugin_asset.get_plugin_asset(projector_plugin.ProjectorPluginAsset)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertEqual(run_json, [])
def testSimplePluginCase(self):
tempdir = self.get_temp_dir()
with ops.Graph().as_default() as g:
plugin_asset.get_plugin_asset(PluginAlpha)
fw = writer.FileWriter(tempdir)
fw.add_graph(g)
self.assertEqual(["Alpha"], plugin_asset_util.ListPlugins(tempdir))
assets = plugin_asset_util.ListAssets(tempdir, "Alpha")
self.assertEqual(["contents.txt"], assets)
contents = plugin_asset_util.RetrieveAsset(tempdir, "Alpha", "contents.txt")
self.assertEqual("hello world", contents)
def testSimplePluginCase(self):
tempdir = self.get_temp_dir()
with ops.Graph().as_default() as g:
plugin_asset.get_plugin_asset(PluginAlpha)
fw = writer.FileWriter(tempdir)
fw.add_graph(g)
self.assertEqual(["Alpha"], plugin_asset_util.ListPlugins(tempdir))
assets = plugin_asset_util.ListAssets(tempdir, "Alpha")
self.assertEqual(["contents.txt"], assets)
contents = plugin_asset_util.RetrieveAsset(tempdir, "Alpha", "contents.txt")
self.assertEqual("hello world", contents)
def testEndpointsNoAssets(self):
g = ops.Graph()
with g.as_default():
plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertEqual(run_json, [])
def testNoAssetsProperSerializationOnDisk(self):
logdir = self.get_temp_dir()
plugin_dir = os.path.join(logdir, writer._PLUGINS_DIR,
projector_plugin.ProjectorPluginAsset.plugin_name)
with ops.Graph().as_default() as g:
plugin_asset.get_plugin_asset(projector_plugin.ProjectorPluginAsset)
fw = writer.FileWriter(logdir)
fw.add_graph(g)
with gfile.Open(os.path.join(plugin_dir, 'projector_config.pbtxt')) as f:
content = f.read()
self.assertEqual(content, '')
def testNoAssetsProperSerializationOnDisk(self):
logdir = self.get_temp_dir()
plugin_dir = os.path.join(logdir, writer._PLUGINS_DIR,
projector_plugin.ProjectorPluginAsset.plugin_name)
with ops.Graph().as_default() as g:
plugin_asset.get_plugin_asset(projector_plugin.ProjectorPluginAsset)
fw = writer.FileWriter(logdir)
fw.add_graph(g)
with gfile.Open(os.path.join(plugin_dir, 'projector_config.pbtxt')) as f:
content = f.read()
self.assertEqual(content, '')
def testNoAssetsProperSerializationOnDisk(self):
logdir = self.get_temp_dir()
plugin_dir = os.path.join(
logdir, 'plugins',
projector_plugin.ProjectorPluginAsset.plugin_name)
with tf.Graph().as_default() as g:
plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
fw = tf.summary.FileWriter(logdir, graph=g)
fw.close()
with tf.gfile.Open(os.path.join(plugin_dir,
'projector_config.pbtxt')) as f:
content = f.read()
self.assertEqual(content, '')
def testEndpointsMetadataForVariableAssets(self):
self._GenerateProjectorTestData()
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertTrue(run_json)
run = run_json[0]
metedata_query = '/data/plugin/projector/metadata?run=%s&name=test' % run
metadata_tsv = self._Get(metedata_query).data
self.assertEqual(metadata_tsv, b'a\nb\nc\n')
unk_tensor_query = '/data/plugin/projector/tensor?run=%s&name=test' % run
response = self._Get(unk_tensor_query)
self.assertEqual(response.status_code, 400)
expected_tensor = np.array([[6, 6]], dtype=np.float32)
tensor_query = '/data/plugin/projector/tensor?run=%s&name=var1' % run
tensor_bytes = self._Get(tensor_query).data
self._AssertTensorResponse(tensor_bytes, expected_tensor)
def testEndpointsMetadataForVariableAssets(self):
self._GenerateProjectorTestData()
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertTrue(run_json)
run = run_json[0]
metedata_query = '/data/plugin/projector/metadata?run=%s&name=test' % run
metadata_tsv = self._Get(metedata_query).data
self.assertEqual(metadata_tsv, b'a\nb\nc\n')
unk_tensor_query = '/data/plugin/projector/tensor?run=%s&name=test' % run
response = self._Get(unk_tensor_query)
self.assertEqual(response.status_code, 400)
expected_tensor = np.array([[6, 6]], dtype=np.float32)
tensor_query = '/data/plugin/projector/tensor?run=%s&name=var1' % run
tensor_bytes = self._Get(tensor_query).data
self._AssertTensorResponse(tensor_bytes, expected_tensor)
def testAddEmbeddingWithTwoMetadataColumns(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'друг јазик'])
metadata.add_column('sizes', [10, 20, 30])
manager.add_embedding('test', np.array([[1], [2], [3]]), metadata)
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.tensor_shape.extend([3, 1])
embedding.tensor_path = 'test_values.tsv'
embedding.metadata_path = 'test_metadata.tsv'
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(
manager.assets(), {
'projector_config.pbtxt':
expected_config_pbtxt,
'test_values.tsv':
b'1\n2\n3\n',
'test_metadata.tsv':
'labels\tsizes\na\t10\nb\t20\nдруг јазик\t30\n'
})
def text_summary(name, tensor, collections=None):
"""Summarizes textual data.
Text data summarized via this plugin will be visible in the Text Dashboard
in TensorBoard. The standard TensorBoard Text Dashboard will render markdown
in the strings, and will automatically organize 1d and 2d tensors into tables.
If a tensor with more than 2 dimensions is provided, a 2d subarray will be
displayed along with a warning message. (Note that this behavior is not
intrinsic to the text summary api, but rather to the default TensorBoard text
plugin.)
Args:
name: A name for the generated node. Will also serve as a series name in
TensorBoard.
tensor: a string-type Tensor to summarize.
collections: Optional list of ops.GraphKeys. The collections to add the
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
Returns:
A TensorSummary op that is configured so that TensorBoard will recognize
that it contains textual data. The TensorSummary is a scalar `Tensor` of
type `string` which contains `Summary` protobufs.
Raises:
ValueError: If tensor has the wrong type.
"""
if tensor.dtype != dtypes.string:
raise ValueError("Expected tensor %s to have dtype string, got %s" %
(tensor.name, tensor.dtype))
t_summary = tensor_summary(name, tensor, collections=collections)
text_assets = plugin_asset.get_plugin_asset(TextSummaryPluginAsset)
text_assets.register_tensor(t_summary.op.name)
return t_summary
def testEndpointsComboTensorAssetsAndCheckpoint(self):
self._GenerateProjectorTestData()
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('var1', metadata)
new_tensor_values = np.array([[1, 2], [3, 4], [5, 6]])
manager.add_embedding('new_tensor', new_tensor_values)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertTrue(run_json)
run = run_json[0]
var1_values = np.array([[6, 6]], dtype=np.float32)
var1_tensor_query = '/data/plugin/projector/tensor?run=%s&name=var1' % run
tensor_bytes = self._Get(var1_tensor_query).data
self._AssertTensorResponse(tensor_bytes, var1_values)
metadata_query = '/data/plugin/projector/metadata?run=%s&name=var1' % run
metadata_tsv = self._Get(metadata_query).data
self.assertEqual(metadata_tsv, b'a\nb\nc\n')
tensor_query = '/data/plugin/projector/tensor?run=%s&name=new_tensor' % run
tensor_bytes = self._Get(tensor_query).data
self._AssertTensorResponse(tensor_bytes, new_tensor_values)
def testPluginAssetSerialized(self):
with ops.Graph().as_default() as g:
plugin_asset.get_plugin_asset(ExamplePluginAsset)
logdir = self.get_temp_dir()
fw = writer.FileWriter(logdir)
fw.add_graph(g)
plugin_dir = os.path.join(logdir, writer._PLUGINS_DIR, "example")
with gfile.Open(os.path.join(plugin_dir, "foo.txt"), "r") as f:
content = f.read()
self.assertEqual(content, "foo!")
with gfile.Open(os.path.join(plugin_dir, "bar.txt"), "r") as f:
content = f.read()
self.assertEqual(content, "bar!")
def text_summary(name, tensor, collections=None):
"""Summarizes textual data.
Text data summarized via this plugin will be visible in the Text Dashboard
in TensorBoard. The standard TensorBoard Text Dashboard will render markdown
in the strings, and will automatically organize 1d and 2d tensors into tables.
If a tensor with more than 2 dimensions is provided, a 2d subarray will be
displayed along with a warning message. (Note that this behavior is not
intrinsic to the text summary api, but rather to the default TensorBoard text
plugin.)
Args:
name: A name for the generated node. Will also serve as a series name in
TensorBoard.
tensor: a string-type Tensor to summarize.
collections: Optional list of ops.GraphKeys. The collections to add the
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
Returns:
A TensorSummary op that is configured so that TensorBoard will recognize
that it contains textual data. The TensorSummary is a scalar `Tensor` of
type `string` which contains `Summary` protobufs.
Raises:
ValueError: If tensor has the wrong type.
"""
if tensor.dtype != dtypes.string:
raise ValueError("Expected tensor %s to have dtype string, got %s" %
(tensor.name, tensor.dtype))
t_summary = tensor_summary(name, tensor, collections=collections)
text_assets = plugin_asset.get_plugin_asset(TextSummaryPluginAsset)
text_assets.register_tensor(t_summary.op.name)
return t_summary
def testAddEmbeddingThumbnailListEntriesNot3DTensors(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_embedding('test3', np.array([[1]]), thumbnails=[[1, 2, 3]],
thumbnail_dim=[1, 1])
def text_summary(name, tensor, collections=None):
"""Summarizes textual data.
Text data summarized via this plugin will be visible in the Text Dashboard
in TensorBoard.
Args:
name: A name for the generated node. Will also serve as a series name in
TensorBoard.
tensor: a scalar string-type Tensor to summarize.
collections: Optional list of ops.GraphKeys. The collections to add the
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
Returns:
A TensorSummary op that is configured so that TensorBoard will recognize
that it contains textual data. The TensorSummary is a scalar `Tensor` of
type `string` which contains `Summary` protobufs.
Raises:
ValueError: If tensor has the wrong shape or type.
"""
if tensor.dtype != dtypes.string:
raise ValueError("Expected tensor %s to have dtype string, got %s" %
(tensor.name, tensor.dtype))
if tensor.shape.ndims != 0:
raise ValueError("Expected tensor %s to be scalar, has shape %s" %
(tensor.name, tensor.shape))
t_summary = tensor_summary(name, tensor, collections=collections)
text_assets = plugin_asset.get_plugin_asset(TextSummaryPluginAsset)
text_assets.register_tensor(t_summary.op.name)
return t_summary
def testEndpointsComboTensorAssetsAndCheckpoint(self):
self._GenerateProjectorTestData()
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('var1', metadata)
new_tensor_values = np.array([[1, 2], [3, 4], [5, 6]])
manager.add_embedding('new_tensor', new_tensor_values)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertTrue(run_json)
run = run_json[0]
var1_values = np.array([[6, 6]], dtype=np.float32)
var1_tensor_query = '/data/plugin/projector/tensor?run=%s&name=var1' % run
tensor_bytes = self._Get(var1_tensor_query).data
self._AssertTensorResponse(tensor_bytes, var1_values)
metadata_query = '/data/plugin/projector/metadata?run=%s&name=var1' % run
metadata_tsv = self._Get(metadata_query).data
self.assertEqual(metadata_tsv, b'a\nb\nc\n')
tensor_query = '/data/plugin/projector/tensor?run=%s&name=new_tensor' % run
tensor_bytes = self._Get(tensor_query).data
self._AssertTensorResponse(tensor_bytes, new_tensor_values)
def testAddEmbeddingThumbnailListNotOfRank4(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_embedding('test2', np.array([[1]]),
thumbnails=np.array([[1]]), thumbnail_dim=[1, 1])
def text_summary(name, tensor, collections=None):
"""Summarizes textual data.
Text data summarized via this plugin will be visible in the Text Dashboard
in TensorBoard.
Args:
name: A name for the generated node. Will also serve as a series name in
TensorBoard.
tensor: a scalar string-type Tensor to summarize.
collections: Optional list of ops.GraphKeys. The collections to add the
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
Returns:
A TensorSummary op that is configured so that TensorBoard will recognize
that it contains textual data. The TensorSummary is a scalar `Tensor` of
type `string` which contains `Summary` protobufs.
Raises:
ValueError: If tensor has the wrong shape or type.
"""
if tensor.dtype != dtypes.string:
raise ValueError("Expected tensor %s to have dtype string, got %s" %
(tensor.name, tensor.dtype))
if tensor.shape.ndims != 0:
raise ValueError("Expected tensor %s to be scalar, has shape %s" %
(tensor.name, tensor.shape))
t_summary = tensor_summary(name, tensor, collections=collections)
text_assets = plugin_asset.get_plugin_asset(TextSummaryPluginAsset)
text_assets.register_tensor(t_summary.op.name)
return t_summary
def testPluginAssetSerialized(self):
with ops.Graph().as_default() as g:
plugin_asset.get_plugin_asset(ExamplePluginAsset)
logdir = self.get_temp_dir()
fw = writer.FileWriter(logdir)
fw.add_graph(g)
plugin_dir = os.path.join(logdir, writer._PLUGINS_DIR, "example")
with gfile.Open(os.path.join(plugin_dir, "foo.txt"), "r") as f:
content = f.read()
self.assertEqual(content, "foo!")
with gfile.Open(os.path.join(plugin_dir, "bar.txt"), "r") as f:
content = f.read()
self.assertEqual(content, "bar!")
def testAddEmbeddingWithSpriteImageButNoThumbnailDim(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
thumbnails = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]])
with self.assertRaises(ValueError):
manager.add_embedding(
'test', np.array([[1], [2], [3]]), thumbnails=thumbnails)
def testAddEmbeddingWithSpriteImageButNoThumbnailDim(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
thumbnails = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]])
with self.assertRaises(ValueError):
manager.add_embedding(
'test', np.array([[1], [2], [3]]), thumbnails=thumbnails)
def testAddEmbeddingThumbnailDimNotOfLength2(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
thumbnails = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]])
with self.assertRaises(ValueError):
manager.add_embedding(
'test', np.array([[1], [2], [3]]), thumbnails=thumbnails,
thumbnail_dim=[4])
def testAddEmbeddingThumbnailListNotOfRank4(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_embedding('test2',
np.array([[1]]),
thumbnails=np.array([[1]]),
thumbnail_dim=[1, 1])
def testAddEmbeddingThumbnailDimNotOfLength2(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
thumbnails = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]])
with self.assertRaises(ValueError):
manager.add_embedding(
'test', np.array([[1], [2], [3]]), thumbnails=thumbnails,
thumbnail_dim=[4])
def testAddEmbeddingThumbnailListEntriesNot3DTensors(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_embedding('test3',
np.array([[1]]),
thumbnails=[[1, 2, 3]],
thumbnail_dim=[1, 1])
def testEventMultiplexerIntegration(self):
tempdir = self.get_temp_dir()
with ops.Graph().as_default() as g:
plugin_instance = plugin_asset.get_plugin_asset(PluginAlpha)
plugin_instance.contents = "graph one"
plugin_asset.get_plugin_asset(PluginBeta)
fw = writer.FileWriter(os.path.join(tempdir, "one"))
fw.add_graph(g)
fw.close()
with ops.Graph().as_default() as g:
plugin_instance = plugin_asset.get_plugin_asset(PluginAlpha)
plugin_instance.contents = "graph two"
fw = writer.FileWriter(os.path.join(tempdir, "two"))
fw.add_graph(g)
fw.close()
multiplexer = event_multiplexer.EventMultiplexer()
multiplexer.AddRunsFromDirectory(tempdir)
self.assertEqual(multiplexer.PluginAssets("Alpha"), {
"one": ["contents.txt"],
"two": ["contents.txt"]
})
self.assertEqual(
multiplexer.RetrievePluginAsset("one", "Alpha", "contents.txt"),
"graph one")
self.assertEqual(
multiplexer.RetrievePluginAsset("one", "Beta", "contents.txt"),
"hello world")
self.assertEqual(
multiplexer.RetrievePluginAsset("two", "Alpha", "contents.txt"),
"graph two")
self.assertEqual(multiplexer.PluginAssets("Beta"), {
"one": ["contents.txt"],
"two": []
})
self.assertEqual(multiplexer.PluginAssets("Gamma"), {
"one": [],
"two": []
})
def testAddEmbeddingWithMetadataOfIncorrectLength(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
# values has length 2, while metadata has length 3.
values = np.array([[1], [2]])
with self.assertRaises(ValueError):
manager.add_embedding('test', values, metadata)
def testAddEmbeddingWithMetadataOfIncorrectLength(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
# values has length 2, while metadata has length 3.
values = np.array([[1], [2]])
with self.assertRaises(ValueError):
manager.add_embedding('test', values, metadata)
def testEndpointsTensorAndMetadataAssets(self):
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
expected_tensor = np.array([[1, 2], [3, 4], [5, 6]])
image1 = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
image2 = np.array([[[10, 20, 30], [40, 50, 60]],
[[70, 80, 90], [100, 110, 120]]])
manager.add_embedding('emb', expected_tensor, metadata,
[image1, image2], [2, 2])
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertTrue(run_json)
run = run_json[0]
metadata_query = '/data/plugin/projector/metadata?run=%s&name=emb' % run
metadata_tsv = self._Get(metadata_query).data
self.assertEqual(metadata_tsv, b'a\nb\nc\n')
unk_metadata_query = '/data/plugin/projector/metadata?run=%s&name=q' % run
response = self._Get(unk_metadata_query)
self.assertEqual(response.status_code, 400)
tensor_query = '/data/plugin/projector/tensor?run=%s&name=emb' % run
tensor_bytes = self._Get(tensor_query).data
self._AssertTensorResponse(tensor_bytes, expected_tensor)
unk_tensor_query = '/data/plugin/projector/tensor?run=%s&name=var1' % run
response = self._Get(unk_tensor_query)
self.assertEqual(response.status_code, 400)
image_query = '/data/plugin/projector/sprite_image?run=%s&name=emb' % run
image_bytes = self._Get(image_query).data
with ops.Graph().as_default():
s = session.Session()
image_array = image_ops.decode_png(image_bytes).eval(
session=s).tolist()
expected_sprite_image = [[[1, 2, 3], [4, 5, 6], [10, 20, 30],
[40, 50, 60]],
[[7, 8, 9], [10, 11, 12], [70, 80, 90],
[100, 110, 120]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]]
self.assertEqual(image_array, expected_sprite_image)
def testEndpointsTensorAndMetadataAssets(self):
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
expected_tensor = np.array([[1, 2], [3, 4], [5, 6]])
image1 = np.array([[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]])
image2 = np.array([[[10, 20, 30], [40, 50, 60]],
[[70, 80, 90], [100, 110, 120]]])
manager.add_embedding('emb', expected_tensor, metadata, [image1, image2],
[2, 2])
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertTrue(run_json)
run = run_json[0]
metadata_query = '/data/plugin/projector/metadata?run=%s&name=emb' % run
metadata_tsv = self._Get(metadata_query).data
self.assertEqual(metadata_tsv, b'a\nb\nc\n')
unk_metadata_query = '/data/plugin/projector/metadata?run=%s&name=q' % run
response = self._Get(unk_metadata_query)
self.assertEqual(response.status_code, 400)
tensor_query = '/data/plugin/projector/tensor?run=%s&name=emb' % run
tensor_bytes = self._Get(tensor_query).data
self._AssertTensorResponse(tensor_bytes, expected_tensor)
unk_tensor_query = '/data/plugin/projector/tensor?run=%s&name=var1' % run
response = self._Get(unk_tensor_query)
self.assertEqual(response.status_code, 400)
image_query = '/data/plugin/projector/sprite_image?run=%s&name=emb' % run
image_bytes = self._Get(image_query).data
with ops.Graph().as_default():
s = session.Session()
image_array = image_ops.decode_png(image_bytes).eval(session=s).tolist()
expected_sprite_image = [
[[1, 2, 3], [4, 5, 6], [10, 20, 30], [40, 50, 60]],
[[7, 8, 9], [10, 11, 12], [70, 80, 90], [100, 110, 120]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]
]
self.assertEqual(image_array, expected_sprite_image)
def testEventMultiplexerIntegration(self):
tempdir = self.get_temp_dir()
with ops.Graph().as_default() as g:
plugin_instance = plugin_asset.get_plugin_asset(PluginAlpha)
plugin_instance.contents = "graph one"
plugin_asset.get_plugin_asset(PluginBeta)
fw = writer.FileWriter(os.path.join(tempdir, "one"))
fw.add_graph(g)
fw.close()
with ops.Graph().as_default() as g:
plugin_instance = plugin_asset.get_plugin_asset(PluginAlpha)
plugin_instance.contents = "graph two"
fw = writer.FileWriter(os.path.join(tempdir, "two"))
fw.add_graph(g)
fw.close()
multiplexer = event_multiplexer.EventMultiplexer()
multiplexer.AddRunsFromDirectory(tempdir)
self.assertEqual(
multiplexer.PluginAssets("Alpha"),
{"one": ["contents.txt"], "two": ["contents.txt"]})
self.assertEqual(
multiplexer.RetrievePluginAsset("one", "Alpha", "contents.txt"),
"graph one")
self.assertEqual(
multiplexer.RetrievePluginAsset("one", "Beta", "contents.txt"),
"hello world")
self.assertEqual(
multiplexer.RetrievePluginAsset("two", "Alpha", "contents.txt"),
"graph two")
self.assertEqual(
multiplexer.PluginAssets("Beta"),
{"one": ["contents.txt"], "two": []})
self.assertEqual(multiplexer.PluginAssets("Gamma"), {"one": [], "two": []})
def testAddEmbeddingNoMetadata(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
manager.add_embedding('test', np.array([[1, 2, 3.1]]))
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.tensor_shape.extend([1, 3])
embedding.tensor_path = 'test_values.tsv'
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(manager.assets(), {
'projector_config.pbtxt': expected_config_pbtxt,
'test_values.tsv': b'1\t2\t3.1\n'
})
def testEndpointsMetadataForVariableAssetsButNoCheckpoint(self):
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertEqual(run_json, [])
def testEndpointsMetadataForVariableAssetsButNoCheckpoint(self):
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
run_json = self._GetJson('/data/plugin/projector/runs')
self.assertEqual(run_json, [])
def testAddEmbeddingNoMetadata(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
manager.add_embedding('test', np.array([[1, 2, 3.1]]))
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.tensor_shape.extend([1, 3])
embedding.tensor_path = 'test_values.tsv'
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(manager.assets(), {
'projector_config.pbtxt': expected_config_pbtxt,
'test_values.tsv': b'1\t2\t3.1\n'
})
def testAddMetadataForVariable(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('Labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.metadata_path = 'test_metadata.tsv'
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(manager.assets(), {
'projector_config.pbtxt': expected_config_pbtxt,
'test_metadata.tsv': 'a\nb\nc\n'
})
def testAddMetadataForVariable(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('Labels', ['a', 'b', 'c'])
manager.add_metadata_for_embedding_variable('test', metadata)
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.metadata_path = 'test_metadata.tsv'
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(manager.assets(), {
'projector_config.pbtxt': expected_config_pbtxt,
'test_metadata.tsv': 'a\nb\nc\n'
})
def testSpriteImageUnknownName(self):
self._GenerateProjectorTestData()
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
image1 = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
image2 = np.array([[[10, 20, 30], [40, 50, 60]],
[[70, 80, 90], [100, 110, 120]]])
manager.add_metadata_for_embedding_variable(
'var1', thumbnails=[image1, image2], thumbnail_dim=[2, 2])
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
q = '/data/plugin/projector/sprite_image?run=.&name=unknown'
response = self._Get(q)
self.assertEqual(response.status_code, 400)
def testSpriteImageUnknownName(self):
self._GenerateProjectorTestData()
g = ops.Graph()
with g.as_default():
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
image1 = np.array([[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]])
image2 = np.array([[[10, 20, 30], [40, 50, 60]],
[[70, 80, 90], [100, 110, 120]]])
manager.add_metadata_for_embedding_variable('var1',
thumbnails=[image1, image2],
thumbnail_dim=[2, 2])
fw = writer.FileWriter(self.log_dir, graph=g)
fw.close()
self._SetupWSGIApp()
q = '/data/plugin/projector/sprite_image?run=.&name=unknown'
response = self._Get(q)
self.assertEqual(response.status_code, 400)
def testAddEmbeddingWithOneMetadataColumn(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
metadata.add_column('labels', ['a', 'b', 'c'])
manager.add_embedding('test', np.array([[1], [2], [3]]), metadata)
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.tensor_shape.extend([3, 1])
embedding.tensor_path = 'test_values.tsv'
embedding.metadata_path = 'test_metadata.tsv'
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(manager.assets(), {
'projector_config.pbtxt': expected_config_pbtxt,
'test_values.tsv': b'1\n2\n3\n',
'test_metadata.tsv': 'a\nb\nc\n'
})
def testAddEmbeddingWithThumbnails(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
image1 = np.array([[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]])
image2 = np.array([[[10, 20, 30], [40, 50, 60]],
[[70, 80, 90], [100, 110, 120]]])
manager.add_embedding(
'test',
np.array([[1], [2], [3]]),
thumbnails=[image1, image2],
thumbnail_dim=[2, 2])
assets = manager.assets()
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.tensor_shape.extend([3, 1])
embedding.tensor_path = 'test_values.tsv'
embedding.sprite.image_path = 'test_sprite.png'
embedding.sprite.single_image_dim.extend([2, 2])
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(assets['projector_config.pbtxt'], expected_config_pbtxt)
self.assertEqual(assets['test_values.tsv'], b'1\n2\n3\n')
png_bytes = assets['test_sprite.png']
with ops.Graph().as_default():
s = session.Session()
image_array = image_ops.decode_png(png_bytes).eval(session=s).tolist()
expected_master_image = [
[[1, 2, 3], [4, 5, 6], [10, 20, 30], [40, 50, 60]],
[[7, 8, 9], [10, 11, 12], [70, 80, 90], [100, 110, 120]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]
]
self.assertEqual(image_array, expected_master_image)
def testAddEmbeddingWithThumbnails(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
image1 = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
image2 = np.array([[[10, 20, 30], [40, 50, 60]],
[[70, 80, 90], [100, 110, 120]]])
manager.add_embedding('test',
np.array([[1], [2], [3]]),
thumbnails=[image1, image2],
thumbnail_dim=[2, 2])
assets = manager.assets()
config = projector_config_pb2.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = 'test'
embedding.tensor_shape.extend([3, 1])
embedding.tensor_path = 'test_values.tsv'
embedding.sprite.image_path = 'test_sprite.png'
embedding.sprite.single_image_dim.extend([2, 2])
expected_config_pbtxt = text_format.MessageToString(config)
self.assertEqual(assets['projector_config.pbtxt'],
expected_config_pbtxt)
self.assertEqual(assets['test_values.tsv'], b'1\n2\n3\n')
png_bytes = assets['test_sprite.png']
with ops.Graph().as_default():
s = session.Session()
image_array = image_ops.decode_png(png_bytes).eval(
session=s).tolist()
expected_master_image = [[[1, 2, 3], [4, 5, 6], [10, 20, 30],
[40, 50, 60]],
[[7, 8, 9], [10, 11, 12], [70, 80, 90],
[100, 110, 120]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]]
self.assertEqual(image_array, expected_master_image)
def testAddEmbeddingIncorrectRank(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_embedding('test', np.array([1, 2, 3.1]))
def testAddMetadataForVariableButNoColumns(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
with self.assertRaises(ValueError):
manager.add_metadata_for_embedding_variable('test', metadata)
def testPluginCollisionDetected(self):
plugin_asset.get_plugin_asset(_ExamplePluginAsset)
with self.assertRaises(ValueError):
plugin_asset.get_plugin_asset(_ExamplePluginThatWillCauseCollision)
def testAddEmbeddingIncorrectRank(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_embedding('test', np.array([1, 2, 3.1]))
def testAddMetadataForVariableAtLeastOneParamIsRequired(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_metadata_for_embedding_variable('test')
def testNoAssets(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
self.assertEqual(manager.assets(), {'projector_config.pbtxt': ''})
def testGetAllPluginAssets(self):
epa = plugin_asset.get_plugin_asset(_ExamplePluginAsset)
opa = plugin_asset.get_plugin_asset(_OtherExampleAsset)
self.assertItemsEqual(plugin_asset.get_all_plugin_assets(), [epa, opa])
def testAddMetadataForVariableButNoColumns(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
metadata = projector_plugin.EmbeddingMetadata(3)
with self.assertRaises(ValueError):
manager.add_metadata_for_embedding_variable('test', metadata)
def testUnnamedPluginFails(self):
with self.assertRaises(ValueError):
plugin_asset.get_plugin_asset(_UnnamedPluginAsset)
def testAddMetadataForVariableAtLeastOneParamIsRequired(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
with self.assertRaises(ValueError):
manager.add_metadata_for_embedding_variable('test')
def testNoAssets(self):
manager = plugin_asset.get_plugin_asset(
projector_plugin.ProjectorPluginAsset)
self.assertEqual(manager.assets(), {'projector_config.pbtxt': ''})
def testGetAllPluginAssets(self): epa = plugin_asset.get_plugin_asset(_ExamplePluginAsset) opa = plugin_asset.get_plugin_asset(_OtherExampleAsset) self.assertItemsEqual(plugin_asset.get_all_plugin_assets(), [epa, opa])
def testPluginCollisionDetected(self):
plugin_asset.get_plugin_asset(_ExamplePluginAsset)
with self.assertRaises(ValueError):
plugin_asset.get_plugin_asset(_ExamplePluginThatWillCauseCollision)