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Fix the bug of tensors not on the same device when running on CUDA device #59

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merged 10 commits into from
Apr 19, 2023
Merged

Fix the bug of tensors not on the same device when running on CUDA device #59

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dceebe2
feat: add --build into `pypots-cli dev`, and add check_arguments();
WenjieDu Apr 18, 2023
2cd0fa5
feat: use subprocess.run() to replace os.system();
WenjieDu Apr 18, 2023
4685884
feat: update the files that manage dependencies;
WenjieDu Apr 19, 2023
1a22fd8
fix: map data to the proper device in functions _assemble_input_for*;
WenjieDu Apr 19, 2023
108d297
fix: apply _assemble_input_for_testing in SAITS and Transformer's imp…
WenjieDu Apr 19, 2023
5355e30
feat: add tb_file_saving_path as a model attribute;
WenjieDu Apr 19, 2023
928d4f6
doc: modify the version from 0.0.10 to 0.0.11;
WenjieDu Apr 19, 2023
75e4ee0
feat: add arg `verbose` to enhance execute_command() in pypots-cli an…
WenjieDu Apr 19, 2023
707f094
fix: flake8 linting error `F401 'pypots.version.__version__' imported…
WenjieDu Apr 19, 2023
6e30021
Update documentation configurations and add readthedocs.yml for proce…
WenjieDu Apr 19, 2023
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fix: apply _assemble_input_for_testing in SAITS and Transformer's imp… 
…ute() to map data to the proper device;
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@WenjieDu
WenjieDu committed Apr 19, 2023
commit 108d297978d8d8f66b595d16eecc1f1eaffc7524
2 changes: 1 addition & 1 deletion pypots/imputation/saits.py
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Expand Up @@ -403,7 +403,7 @@ def impute(

with torch.no_grad():
for idx, data in enumerate(test_loader):
inputs = {"X": data[1], "missing_mask": data[2]}
inputs = self._assemble_input_for_testing(data)
imputed_data = self.model.impute(inputs)
imputation_collector.append(imputed_data)

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2 changes: 1 addition & 1 deletion pypots/imputation/transformer.py
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Expand Up @@ -511,7 +511,7 @@ def impute(self, X: Union[dict, str], file_type: str = "h5py") -> np.ndarray:

with torch.no_grad():
for idx, data in enumerate(test_loader):
inputs = {"X": data[1], "missing_mask": data[2]}
inputs = self._assemble_input_for_testing(data)
imputed_data = self.model.impute(inputs)
imputation_collector.append(imputed_data)

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