def test_tensorboard_log_graph(tmpdir, example_input_array):
"""test that log graph works with both model.example_input_array and if array is passed externally."""
model = BoringModel()
if example_input_array is not None:
model.example_input_array = None
logger = TensorBoardLogger(tmpdir, log_graph=True)
logger.log_graph(model, example_input_array)
def test_tensorboard_log_graph(tmpdir, example_input_array):
""" test that log graph works with both model.example_input_array and
if array is passed externaly
"""
model = EvalModelTemplate()
if example_input_array is None:
model.example_input_array = None
logger = TensorBoardLogger(tmpdir)
logger.log_graph(model, example_input_array)
def test_tensorboard_log_graph_warning_no_example_input_array(tmpdir):
""" test that log graph throws warning if model.example_input_array is None """
model = BoringModel()
model.example_input_array = None
logger = TensorBoardLogger(tmpdir, log_graph=True)
with pytest.warns(
UserWarning,
match=
'Could not log computational graph since the `model.example_input_array`'
' attribute is not set or `input_array` was not given'):
logger.log_graph(model)
def test_tensorboard_graph_log(dataloaders_with_covariates, model, tmp_path):
d = next(iter(dataloaders_with_covariates["train"]))
logger = TensorBoardLogger("test", str(tmp_path), log_graph=True)
logger.log_graph(model, d[0])
