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import hydra | ||
from pytorch_lightning import LightningDataModule | ||
from tests.conftest import make_default_hydra_cfg | ||
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from myria3d.models.model import Model | ||
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def test_model_get_batch_tensor_by_enumeration(): | ||
config = make_default_hydra_cfg( | ||
overrides=[ | ||
"predict.src_las=tests/data/toy_dataset_src/862000_6652000.classified_toy_dataset.100mx100m.las", | ||
"datamodule.epsg=2154", | ||
"work_dir=./../../..", | ||
"datamodule.subtile_width=1", | ||
"datamodule.hdf5_file_path=null", | ||
] | ||
) | ||
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datamodule: LightningDataModule = hydra.utils.instantiate(config.datamodule) | ||
datamodule._set_predict_data(config.predict.src_las) | ||
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model = Model( | ||
neural_net_class_name="PyGRandLANet", | ||
neural_net_hparams=dict(num_features=2, num_classes=7), | ||
) | ||
for batch in datamodule.predict_dataloader(): | ||
# Check that no error is raised ("TypeError: object of type 'numpy.int64' has no len()") | ||
_ = model._get_batch_tensor_by_enumeration(batch.idx_in_original_cloud) |
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