def _flush_metrics(self) -> None:
"""
Flush metrics files
"""
with open(self._get_file_name(True), 'w') as out:
json.dump(self._storage, out)
if self._final_metrics_file is not None:
res = dict_recursive_bypass(self._storage, lambda v: v[-1])
with open(self._final_metrics_file, 'w') as out:
json.dump(res, out)
def test_dict_recursive_bypass(self):
d = {
'data': np.array([1]),
'target': {
'a': np.array([1]),
'b': np.array([1])
}
}
d = dict_recursive_bypass(d, lambda v: torch.from_numpy(v))
self.assertTrue(isinstance(d['data'], Tensor))
self.assertTrue(isinstance(d['target']['a'], Tensor))
self.assertTrue(isinstance(d['target']['b'], Tensor))
def _pass_data_to_device(self, data) -> torch.Tensor or dict:
"""
Internal method, that pass data to specified device
:param data: data as any object type. If will passed to device if it's instance of :class:`torch.Tensor` or dict with key
``data``. Otherwise data will be doesn't changed
:return: processed on target device
"""
if isinstance(data, dict):
return dict_recursive_bypass(data, lambda v: v.to(self._device))
elif isinstance(data, torch.Tensor):
return data.to(self._device)
else:
return data