def test_videos_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
video=V1EventVideo(path="test", content_type="mp4"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
video=V1EventVideo(height=1, width=1),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
video=V1EventVideo(height=10, width=10, colorspace=2),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="video",
data=os.path.abspath(
"tests/fixtures/polyboard/video/video_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_models_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
model=V1EventModel(framework="tensorflow", path="path1"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
model=V1EventModel(framework="pytorch", path="path2"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
model=V1EventModel(framework="onnx", path="path3"),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="model",
data=os.path.abspath("tests/fixtures/polyboard/model/model_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_histograms_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
histogram=V1EventHistogram(values=[10], counts=[1]),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
histogram=V1EventHistogram(values=[10, 1, 1], counts=[1, 1,
1]),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
histogram=V1EventHistogram(values=[10, 112, 12, 1],
counts=[12, 1, 1, 1]),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="histogram",
data=os.path.abspath(
"tests/fixtures/polyboard/histogram/histogram_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_video(self):
events = LoggedEventListSpec(
name="foo",
kind="video",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
video=V1EventVideo(height=1,
width=1,
colorspace=1,
path="path"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
video=V1EventVideo(height=10,
width=1,
colorspace=0,
path="path"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
video=V1EventVideo(height=1,
width=10,
colorspace=2,
path="path"),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_artifacts_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
artifact=V1EventArtifact(kind="dataframe", path="path1"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
artifact=V1EventArtifact(kind="tsv", path="path2"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
artifact=V1EventArtifact(kind="csv", path="path3"),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="artifact",
data=os.path.abspath(
"tests/fixtures/polyboard/artifact/artifact_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_charts_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
chart=V1EventChart(kind="plotly", figure={"foo": "bar"}),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
chart=V1EventChart(kind="vega", figure={"foo2": "bar2"}),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
chart=V1EventChart(kind="bokeh", figure={"foo3": "bar3"}),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="chart",
data=os.path.abspath(
"tests/fixtures/polyboard/chart/chart_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_dataframes_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
dataframe=V1EventDataframe(path="path1",
content_type="parquet"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
dataframe=V1EventDataframe(path="path2",
content_type="pickle"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
dataframe=V1EventDataframe(path="path3"),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="dataframe",
data=os.path.abspath(
"tests/fixtures/polyboard/dataframe/dataframe_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_dataframe(self):
events = LoggedEventListSpec(
name="foo",
kind="dataframe",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
dataframe=V1EventDataframe(path="path",
content_type="parquet"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
dataframe=V1EventDataframe(path="path",
content_type="pickle"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
dataframe=V1EventDataframe(path="path"),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_audios_read_yaml(self):
values = [
V1Event(
timestamp=parse_datetime("2018-12-11 10:24:57"),
audio=V1EventAudio(
sample_rate=1.1, num_channels=2, length_frames=2, path="test"
),
step=12,
),
V1Event(
timestamp=parse_datetime("2018-12-11 10:25:57"),
audio=V1EventAudio(
sample_rate=1.11,
num_channels=22,
length_frames=22,
path="test",
content_type="wav",
),
step=13,
),
V1Event(
timestamp=parse_datetime("2018-12-11 10:26:57"),
audio=V1EventAudio(path="testwave", content_type="wav"),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="audio",
data=os.path.abspath("tests/fixtures/polyboard/audio/audio_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_images_read_yaml(self):
values = [
V1Event(
timestamp=parse_datetime("2018-12-11 10:24:57"),
image=V1EventImage(path="test"),
step=12,
),
V1Event(
timestamp=parse_datetime("2018-12-11 10:25:57"),
image=V1EventImage(height=1, width=1),
step=13,
),
V1Event(
timestamp=parse_datetime("2018-12-11 10:26:57"),
image=V1EventImage(height=10, width=10, colorspace=2),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="image",
data=os.path.abspath("tests/fixtures/polyboard/image/image_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_htmls_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
html="<div>1</div>",
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
html="<div>2</div>",
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
html="<div>3</div>",
step=14,
),
]
events = V1Events.read(
name="foo",
kind="html",
data=os.path.abspath(
"tests/fixtures/polyboard/html/html_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_audio(self):
events = LoggedEventListSpec(
name="foo",
kind="audio",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
audio=V1EventAudio(sample_rate=1.1,
num_channels=2,
length_frames=2,
path="test"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
audio=V1EventAudio(sample_rate=1.1,
num_channels=2,
length_frames=2,
path="test"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
audio=V1EventAudio(sample_rate=1.12,
num_channels=22,
length_frames=22,
path="test"),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def log_artifact(self,
path,
name=None,
artifact_kind=None,
step=None,
timestamp=None):
name = name or os.path.basename(name)
ext = get_path_extension(filepath=path)
artifact_kind = artifact_kind or V1ArtifactKind.FILE
asset_path = get_asset_path(
run_path=self.artifacts_path,
kind=artifact_kind,
name=name,
step=step,
ext=ext,
)
artifact = events_processors.artifact_path(from_path=path,
asset_path=asset_path,
kind=artifact_kind)
logged_event = LoggedEventSpec(
name=name,
kind=artifact_kind,
event=V1Event(timestamp=timestamp, step=step, artifact=artifact),
)
self._event_logger.add_event(logged_event)
def log_model(self,
path,
name=None,
framework=None,
spec=None,
step=None,
timestamp=None):
name = name or os.path.basename(path)
ext = None
if os.path.isfile(path):
ext = get_path_extension(filepath=path)
asset_path = get_asset_path(
run_path=self.artifacts_path,
kind=V1ArtifactKind.MODEL,
name=name,
step=step,
ext=ext,
)
model = events_processors.model_path(from_path=path,
asset_path=asset_path,
framework=framework,
spec=spec)
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.MODEL,
event=V1Event(timestamp=timestamp, step=step, model=model),
)
self._event_logger.add_event(logged_event)
def log_html(self, name, html, step=None, timestamp=None):
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.HTML,
event=V1Event(timestamp=timestamp, step=step, html=html),
)
self._event_logger.add_event(logged_event)
def log_text(self, name, text, step=None, timestamp=None):
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.TEXT,
event=V1Event(timestamp=timestamp, step=step, text=text),
)
self._event_logger.add_event(logged_event)
def log_image_with_boxes(
self,
tensor_image,
tensor_boxes,
name=None,
step=None,
timestamp=None,
rescale=1,
dataformats="CHW",
):
name = name or "figure"
asset_path = get_asset_path(
run_path=self.artifacts_path,
kind=V1ArtifactKind.IMAGE,
name=name,
step=step,
)
event_value = events_processors.image_boxes(
asset_path=asset_path,
tensor_image=tensor_image,
tensor_boxes=tensor_boxes,
rescale=rescale,
dataformats=dataformats,
)
if event_value == UNKNOWN:
return
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.IMAGE,
event=V1Event(timestamp=timestamp, step=step, image=event_value),
)
self._event_logger.add_event(logged_event)
def log_dataframe(self,
path,
name=None,
content_type=None,
step=None,
timestamp=None):
name = name or os.path.basename(path)
ext = get_path_extension(filepath=path)
asset_path = get_asset_path(
run_path=self.artifacts_path,
kind=V1ArtifactKind.DATAFRAME,
name=name,
step=step,
ext=ext,
)
df = events_processors.dataframe_path(from_path=path,
asset_path=asset_path,
content_type=content_type)
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.DATAFRAME,
event=V1Event(timestamp=timestamp, step=step, dataframe=df),
)
self._event_logger.add_event(logged_event)
def test_log_line_has_iso_datetime(self):
parsed = V1Event.make(timestamp="2018-12-11T08:49:07.163495183Z",
step=12)
expected = V1Event(
timestamp=dt_parser.parse("2018-12-11T08:49:07.163495+00:00"),
step=12)
assert parsed == expected
def log_mpl_plotly_chart(self, name, figure, step=None, timestamp=None):
chart = events_processors.mpl_plotly_chart(figure=figure)
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.CHART,
event=V1Event(timestamp=timestamp, step=step, chart=chart),
)
self._event_logger.add_event(logged_event)
def test_metrics_read_yaml(self):
values = [
V1Event(
timestamp=parse_datetime("2018-12-11 10:24:57"), metric=0.1, step=12
),
V1Event(
timestamp=parse_datetime("2018-12-11 10:25:57"), metric=0.2, step=13
),
V1Event(
timestamp=parse_datetime("2018-12-11 10:26:57"), metric=0.3, step=14
),
]
events = V1Events.read(
name="metric_events",
kind="metric",
data=os.path.abspath("tests/fixtures/polyboard/metric/metric_events.plx"),
)
assert events.name == "metric_events"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def log_np_histogram(self, name, values, counts, step=None, timestamp=None):
event_value = events_processors.np_histogram(values=values, counts=counts)
if event_value == UNKNOWN:
return
logged_event = LoggedEventSpec(
name=name,
kind=V1ArtifactKind.HISTOGRAM,
event=V1Event(timestamp=timestamp, step=step, histogram=event_value),
)
self._event_logger.add_event(logged_event)
def test_curves_read_yaml(self):
values = [
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
curve=V1EventCurve(kind="roc",
x=[1.1, 3.1, 5.1],
y=[0.1, 0.3, 0.4],
annotation="0.1"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:25:57"),
curve=V1EventCurve(kind="pr",
x=[1.1, 3.1, 5.1],
y=[0.1, 0.3, 0.4],
annotation="0.21"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:26:57"),
curve=V1EventCurve(
kind="custom",
x=[1.1, 3.1, 5.1],
y=[0.1, 0.3, 0.4],
annotation="0.1",
),
step=14,
),
]
events = V1Events.read(
name="foo",
kind="curve",
data=os.path.abspath(
"tests/fixtures/polyboard/curve/curve_events.plx"),
)
assert events.name == "foo"
assert len(events.df.values) == 3
for i in range(3):
assert events.get_event_at(i).to_dict() == values[i].to_dict()
def test_curve(self):
events = LoggedEventListSpec(
name="foo",
kind="curve",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
curve=V1EventCurve(
kind="roc",
x=[1.1, 3.1, 5.1],
y=[0.1, 0.3, 0.4],
annotation="0.1",
),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
curve=V1EventCurve(
kind="pr",
x=[1.1, 3.1, 5.1],
y=[0.1, 0.3, 0.4],
annotation="0.21",
),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
curve=V1EventCurve(
kind="custom",
x=[1.1, 3.1, 5.1],
y=[0.1, 0.3, 0.4],
annotation="0.1",
),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_metrics(self):
events = LoggedEventListSpec(
name="foo",
kind="metric",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
metric=0.1,
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
metric=0.112,
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
metric=0.1,
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_model(self):
events = LoggedEventListSpec(
name="foo",
kind="model",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
model=V1EventModel(framework="tensorflow", path="path"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
model=V1EventModel(framework="pytorch", path="path"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
model=V1EventModel(framework="onnx", path="path"),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_artifact(self):
events = LoggedEventListSpec(
name="foo",
kind="artifact",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
artifact=V1EventArtifact(kind="dataframe", path="path"),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
artifact=V1EventArtifact(kind="tsv", path="path"),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
artifact=V1EventArtifact(kind="csv", path="path"),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_histogram(self):
events = LoggedEventListSpec(
name="foo",
kind="histogram",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
histogram=V1EventHistogram(values=[10], counts=[1]),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
histogram=V1EventHistogram(values=[10], counts=[1]),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
histogram=V1EventHistogram(values=[10], counts=[1]),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_chart(self):
events = LoggedEventListSpec(
name="foo",
kind="chart",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
chart=V1EventChart(kind="plotly", figure={"foo": "bar"}),
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
chart=V1EventChart(kind="vega", figure={"foo": "bar"}),
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
chart=V1EventChart(kind="bokeh", figure={"foo": "bar"}),
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()
def test_html(self):
events = LoggedEventListSpec(
name="foo",
kind="html",
events=[
V1Event(
timestamp=dt_parser.parse("2018-12-11 10:24:57"),
html="<div>1</div>",
step=12,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 11:24:57"),
html="<div>2</div>",
step=13,
),
V1Event(
timestamp=dt_parser.parse("2018-12-11 12:24:57"),
html="<div>3</div>",
step=14,
),
],
)
events_dict = events.to_dict()
assert events_dict == events.from_dict(events_dict).to_dict()