line = line.strip()
try:
(key, value) = line.split(self.spec.key_value_delimiter)
- except Exception as e:
+ except Exception:
logger.debug(f"WARNING: bad line in file {filename} '{line}', skipped")
continue
y.pop()
if self.spec.delete_bad_inputs:
- msg = f"WARNING: {filename}: missing features or label. DELETING."
+ msg = f"WARNING: {filename}: missing features or label; expected {self.spec.feature_count} but saw {len(x)}. DELETING."
print(msg, file=sys.stderr)
logger.warning(msg)
os.remove(filename)
else:
- msg = f"WARNING: {filename}: missing features or label. Skipped."
+ msg = f"WARNING: {filename}: missing features or label; expected {self.spec.feature_count} but saw {len(x)}. Skipping."
print(msg, file=sys.stderr)
logger.warning(msg)
return (X, y)
import input_utils
import string_utils
+ now: datetime.datetime = datetime_utils.now_pacific()
+ info = f"""Timestamp: {datetime_utils.datetime_to_string(now)}
+Model params: {params}
+Training examples: {num_examples}
+Training set score: {training_score:.2f}%
+Testing set score: {test_score:.2f}%"""
+ print(f'\n{info}\n')
if (
(self.spec.persist_percentage_threshold is not None and
test_score > self.spec.persist_percentage_threshold)
print(msg)
logger.info(msg)
model_info_filename = f"{self.spec.basename}_model_info.txt"
- now: datetime.datetime = datetime_utils.now_pst()
- info = f"""Timestamp: {datetime_utils.datetime_to_string(now)}
-Model params: {params}
-Training examples: {num_examples}
-Training set score: {training_score:.2f}%
-Testing set score: {test_score:.2f}%"""
with open(model_info_filename, "w") as f:
f.write(info)
msg = f"Wrote {model_info_filename}:"