def test_eq(self):
x1 = provider.TensorTimeSeries(77, 1234.5, b"\x12", "one", "two")
x2 = provider.TensorTimeSeries(77, 1234.5, b"\x12", "one", "two")
x3 = provider.TensorTimeSeries(66, 4321.0, b"\x7F", "hmm", "hum")
self.assertEqual(x1, x2)
self.assertNotEqual(x1, x3)
self.assertNotEqual(x1, object())
def test_list_tensors(self):
res = data_provider_pb2.ListTensorsResponse()
run1 = res.runs.add(run_name="val")
tag11 = run1.tags.add(tag_name="weights")
tag11.metadata.max_step = 7
tag11.metadata.max_wall_time = 7.77
tag11.metadata.summary_metadata.plugin_data.content = b"magic"
tag11.metadata.summary_metadata.summary_description = "hey"
tag12 = run1.tags.add(tag_name="other")
tag12.metadata.max_step = 8
tag12.metadata.max_wall_time = 8.88
run2 = res.runs.add(run_name="test")
tag21 = run2.tags.add(tag_name="weights")
tag21.metadata.max_step = 9
tag21.metadata.max_wall_time = 9.99
self.stub.ListTensors.return_value = res
actual = self.provider.list_tensors(
self.ctx,
experiment_id="123",
plugin_name="histograms",
run_tag_filter=provider.RunTagFilter(tags=["weights", "other"]),
)
expected = {
"val": {
"weights":
provider.TensorTimeSeries(
max_step=7,
max_wall_time=7.77,
plugin_content=b"magic",
description="hey",
display_name="",
),
"other":
provider.TensorTimeSeries(
max_step=8,
max_wall_time=8.88,
plugin_content=b"",
description="",
display_name="",
),
},
"test": {
"weights":
provider.TensorTimeSeries(
max_step=9,
max_wall_time=9.99,
plugin_content=b"",
description="",
display_name="",
),
},
}
self.assertEqual(actual, expected)
req = data_provider_pb2.ListTensorsRequest()
req.experiment_id = "123"
req.plugin_filter.plugin_name = "histograms"
req.run_tag_filter.tags.names.extend(["other", "weights"]) # sorted
self.stub.ListTensors.assert_called_once_with(req)
def test_hash(self):
x1 = provider.TensorTimeSeries(77, 1234.5, b"\x12", "one", "two")
x2 = provider.TensorTimeSeries(77, 1234.5, b"\x12", "one", "two")
x3 = provider.TensorTimeSeries(66, 4321.0, b"\x7F", "hmm", "hum")
self.assertEqual(hash(x1), hash(x2))
# The next check is technically not required by the `__hash__`
# contract, but _should_ pass; failure on this assertion would at
# least warrant some scrutiny.
self.assertNotEqual(hash(x1), hash(x3))
def list_tensors(self,
ctx,
*,
experiment_id,
plugin_name,
run_tag_filter=None):
with timing.log_latency("build request"):
req = data_provider_pb2.ListTensorsRequest()
req.experiment_id = experiment_id
req.plugin_filter.plugin_name = plugin_name
_populate_rtf(run_tag_filter, req.run_tag_filter)
with timing.log_latency("_stub.ListTensors"):
with _translate_grpc_error():
res = self._stub.ListTensors(req)
with timing.log_latency("build result"):
result = {}
for run_entry in res.runs:
tags = {}
result[run_entry.run_name] = tags
for tag_entry in run_entry.tags:
time_series = tag_entry.metadata
tags[tag_entry.tag_name] = provider.TensorTimeSeries(
max_step=time_series.max_step,
max_wall_time=time_series.max_wall_time,
plugin_content=time_series.summary_metadata.
plugin_data.content,
description=time_series.summary_metadata.
summary_description,
display_name=time_series.summary_metadata.display_name,
)
return result
def _tensor_time_series(self, max_step, max_wall_time, plugin_content,
description, display_name):
# Helper to use explicit kwargs.
return provider.TensorTimeSeries(
max_step=max_step,
max_wall_time=max_wall_time,
plugin_content=plugin_content,
description=description,
display_name=display_name,
)
def test_repr(self):
x = provider.TensorTimeSeries(
max_step=77,
max_wall_time=1234.5,
plugin_content=b"AB\xCD\xEF!\x00",
description="test test",
display_name="one two",
)
repr_ = repr(x)
self.assertIn(repr(x.max_step), repr_)
self.assertIn(repr(x.max_wall_time), repr_)
self.assertIn(repr(x.plugin_content), repr_)
self.assertIn(repr(x.description), repr_)
self.assertIn(repr(x.display_name), repr_)