def _load_table_from_outputs(job_id, run_id, filename, client=None,
**table_kwargs):
"""Load a table from a run output directly into a ``DataFrame``"""
client = APIClient(resources='all') if client is None else client
file_id = cio.file_id_from_run_output(filename, job_id, run_id,
client=client, regex=True)
return cio.file_to_dataframe(file_id, client=client, **table_kwargs)
def training_metadata(self):
if self._train_metadata is None:
fid = cio.file_id_from_run_output('model_info.json',
self.train_job_id,
self.train_run_id,
client=self.client)
self._train_metadata = cio.file_to_json(fid, client=self.client)
return self._train_metadata
def validation_metadata(self):
if self._val_metadata is None:
fid = cio.file_id_from_run_output('metrics.json',
self.train_job_id,
self.train_run_id,
client=self.client)
self._val_metadata = cio.file_to_json(fid, client=self.client)
return self._val_metadata
def _retrieve_file(fname, job_id, run_id, local_dir, client=None):
"""Download a Civis file using a reference on a previous run"""
file_id = cio.file_id_from_run_output(fname, job_id, run_id, client=client)
fpath = os.path.join(local_dir, fname)
# fname may contain a path
output_dir = os.path.dirname(fpath)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
with open(fpath, 'wb') as down_file:
cio.civis_to_file(file_id, down_file, client=client)
return fpath
