def _get_tensorboard_scalars(logdir: Union[str,
Path], metrics: Optional[List[str]],
step: str) -> Dict[str, List]:
summary_reader = SummaryReader(logdir, types=["scalar"])
items = defaultdict(list)
for item in summary_reader:
if step in item.tag and (metrics is None or any(m in item.tag
for m in metrics)):
items[item.tag].append(item)
return items
def test_summary_reader_iterate():
reader = SummaryReader("logs", types=["scalar", "image"])
_, data_raw = _get_test_data()
data_raw2 = 2 * [d for d in data_raw if d is not None]
items = list(reader)
assert len(items) == len(data_raw2)
for item, event_raw in zip(items, data_raw2):
assert item.step == event_raw["step"]
assert item.tag == event_raw["tag"]
assert item.type == event_raw["type"]
assert np.all(item.value == event_raw["value"])
def test_summary_reader_filter_scalars():
types = ["scalar"]
reader = SummaryReader("logs", types=types)
_, data_raw = _get_test_data()
data_raw2 = 2 * [
d for d in data_raw if d is not None and d["type"] in types
]
items = list(reader)
assert len(items) == len(data_raw2)
for item, event_raw in zip(items, data_raw2):
assert item.step == event_raw["step"]
assert item.tag == event_raw["tag"]
assert item.type == "scalar"
assert np.all(item.value == event_raw["value"])
def test_summary_reader_filter():
"""@TODO: Docs. Contribution is welcome."""
tags = ["x", "z"]
reader = SummaryReader("logs", tag_filter=tags, types=["scalar", "image"])
_, data_raw = _get_test_data()
data_raw2 = 2 * [d for d in data_raw if d is not None and d["tag"] in tags]
items = list(reader)
assert len(items) == len(data_raw2)
for item, event_raw in zip(items, data_raw2):
assert item.step == event_raw["step"]
assert item.tag == event_raw["tag"]
assert item.type == event_raw["type"]
assert item.tag in tags
assert np.all(item.value == event_raw["value"])
def test_summary_reader_invalid_type():
with pytest.raises(ValueError):
SummaryReader(".", types=["unknown-type"])
def test_summary_reader_invalid_type():
"""@TODO: Docs. Contribution is welcome."""
with pytest.raises(ValueError):
SummaryReader(".", types=["unknown-type"])
