def test_data_logger_pred_user_proc(test_settings, live_mock_server):
with wandb.init(settings=test_settings) as run:
vd = ValidationDataLogger(
inputs=np.array([[i, i, i] for i in range(10)]),
targets=np.array([[i] for i in range(10)]),
indexes=None,
validation_row_processor=None,
prediction_row_processor=lambda ndx, row: {"oa": row["output"] + 1},
class_labels=None,
infer_missing_processors=False,
)
t = vd.log_predictions(vd.make_predictions(lambda inputs: inputs[:, 0]))
cols = ["val_row", "output", "oa"]
tcols = t.columns
assert set(tcols) == set(cols)
assert np.all([t.data[i] == [i, i, i + 1] for i in range(10)])
assert t._get_artifact_reference_entry() is not None
def test_data_logger_pred_inferred_proc_no_classes(test_settings,
live_mock_server):
with wandb.init(settings=test_settings) as run:
vd = ValidationDataLogger(
inputs=np.array([[i, i, i] for i in range(10)]),
targets=np.array([[i] for i in range(10)]),
indexes=None,
validation_row_processor=None,
prediction_row_processor=None,
class_labels=None,
infer_missing_processors=True,
)
t = vd.log_predictions(
vd.make_predictions(
lambda inputs: {
"simple": np.random.randint(5, size=(10)),
"wrapped": np.random.randint(5, size=(10, 1)),
"logits": np.random.randint(5, size=(10, 5)),
"nodes": np.random.randint(5, size=(10, 10)),
"2dimages": np.random.randint(255, size=(10, 5, 5)),
"3dimages": np.random.randint(255, size=(10, 5, 5, 3)),
"video": np.random.randint(255, size=(10, 5, 5, 3, 10)),
}))
cols = [
"val_row",
"simple",
"wrapped",
"logits",
"nodes",
"2dimages",
"3dimages",
"video",
"wrapped:val",
"logits:node",
"logits:argmax",
"logits:argmin",
"nodes:node",
"nodes:argmax",
"nodes:argmin",
]
if CAN_INFER_IMAGE_AND_VIDEO:
cols.append("2dimages:image")
cols.append("3dimages:image")
cols.append("video:video")
tcols = t.columns
row = t.data[0]
assert set(tcols) == set(cols)
assert isinstance(row[tcols.index("val_row")],
wandb.data_types._TableIndex)
assert isinstance(row[tcols.index("simple")].tolist(), int)
assert len(row[tcols.index("wrapped")]) == 1
assert len(row[tcols.index("logits")]) == 5
assert len(row[tcols.index("nodes")]) == 10
assert row[tcols.index("2dimages")].shape == (5, 5)
assert row[tcols.index("3dimages")].shape == (5, 5, 3)
assert row[tcols.index("video")].shape == (5, 5, 3, 10)
assert isinstance(row[tcols.index("wrapped:val")].tolist(), int)
# assert isinstance(row[tcols.index("logits:node")], dict)
assert isinstance(row[tcols.index("logits:node")], list)
assert isinstance(row[tcols.index("logits:argmax")].tolist(), int)
assert isinstance(row[tcols.index("logits:argmin")].tolist(), int)
# assert isinstance(row[tcols.index("nodes:node")], dict)
assert isinstance(row[tcols.index("nodes:node")], list)
assert isinstance(row[tcols.index("nodes:argmax")].tolist(), int)
assert isinstance(row[tcols.index("nodes:argmin")].tolist(), int)
if CAN_INFER_IMAGE_AND_VIDEO:
assert isinstance(row[tcols.index("2dimages:image")],
wandb.data_types.Image)
assert isinstance(row[tcols.index("3dimages:image")],
wandb.data_types.Image)
assert isinstance(row[tcols.index("video:video")],
wandb.data_types.Video)