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提交 00bbb326 编写于 作者: P PyCaret
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removed logger from load_model

上级 fc9733ba
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Showing with 1 addition and 30 deletion
pycaret/anomaly.py
浏览文件 @ 00bbb326
...@@ -3184,9 +3184,6 @@ def load_model(model_name, ...@@ -3184,9 +3184,6 @@ def load_model(model_name,
""" """
import logging
logger.info("Initializing load_model()")
#ignore warnings #ignore warnings
import warnings import warnings
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')
...@@ -3201,8 +3198,6 @@ def load_model(model_name, ...@@ -3201,8 +3198,6 @@ def load_model(model_name,
#cloud provider #cloud provider
if platform == 'aws': if platform == 'aws':
logger.info("Importing model from AWS-S3")
import boto3 import boto3
bucketname = authentication.get('bucket') bucketname = authentication.get('bucket')
filename = str(model_name) + '.pkl' filename = str(model_name) + '.pkl'
...@@ -3214,15 +3209,13 @@ def load_model(model_name, ...@@ -3214,15 +3209,13 @@ def load_model(model_name,
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return model return model
import joblib import joblib
model_name = model_name + '.pkl' model_name = model_name + '.pkl'
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return joblib.load(model_name) return joblib.load(model_name)
def predict_model(model, def predict_model(model,
......
pycaret/classification.py
浏览文件 @ 00bbb326
...@@ -9938,9 +9938,6 @@ def load_model(model_name, ...@@ -9938,9 +9938,6 @@ def load_model(model_name,
""" """
import logging
logger.info("Initializing load_model()")
#ignore warnings #ignore warnings
import warnings import warnings
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')
...@@ -9955,8 +9952,6 @@ def load_model(model_name, ...@@ -9955,8 +9952,6 @@ def load_model(model_name,
#cloud provider #cloud provider
if platform == 'aws': if platform == 'aws':
logger.info("Importing model from AWS-S3")
import boto3 import boto3
bucketname = authentication.get('bucket') bucketname = authentication.get('bucket')
filename = str(model_name) + '.pkl' filename = str(model_name) + '.pkl'
...@@ -9968,14 +9963,12 @@ def load_model(model_name, ...@@ -9968,14 +9963,12 @@ def load_model(model_name,
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return model return model
import joblib import joblib
model_name = model_name + '.pkl' model_name = model_name + '.pkl'
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return joblib.load(model_name) return joblib.load(model_name)
def predict_model(estimator, def predict_model(estimator,
......
pycaret/clustering.py
浏览文件 @ 00bbb326
...@@ -3430,9 +3430,6 @@ def load_model(model_name, ...@@ -3430,9 +3430,6 @@ def load_model(model_name,
""" """
import logging
logger.info("Initializing load_model()")
#ignore warnings #ignore warnings
import warnings import warnings
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')
...@@ -3447,8 +3444,6 @@ def load_model(model_name, ...@@ -3447,8 +3444,6 @@ def load_model(model_name,
#cloud provider #cloud provider
if platform == 'aws': if platform == 'aws':
logger.info("Importing model from AWS-S3")
import boto3 import boto3
bucketname = authentication.get('bucket') bucketname = authentication.get('bucket')
filename = str(model_name) + '.pkl' filename = str(model_name) + '.pkl'
...@@ -3460,15 +3455,12 @@ def load_model(model_name, ...@@ -3460,15 +3455,12 @@ def load_model(model_name,
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return model return model
import joblib import joblib
model_name = model_name + '.pkl' model_name = model_name + '.pkl'
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return joblib.load(model_name) return joblib.load(model_name)
def predict_model(model, def predict_model(model,
......
pycaret/regression.py
浏览文件 @ 00bbb326
...@@ -8824,9 +8824,6 @@ def load_model(model_name, ...@@ -8824,9 +8824,6 @@ def load_model(model_name,
""" """
import logging
logger.info("Initializing load_model()")
#ignore warnings #ignore warnings
import warnings import warnings
warnings.filterwarnings('ignore') warnings.filterwarnings('ignore')
...@@ -8842,8 +8839,6 @@ def load_model(model_name, ...@@ -8842,8 +8839,6 @@ def load_model(model_name,
#cloud provider #cloud provider
if platform == 'aws': if platform == 'aws':
logger.info("Importing model from AWS-S3")
import boto3 import boto3
bucketname = authentication.get('bucket') bucketname = authentication.get('bucket')
filename = str(model_name) + '.pkl' filename = str(model_name) + '.pkl'
...@@ -8855,7 +8850,6 @@ def load_model(model_name, ...@@ -8855,7 +8850,6 @@ def load_model(model_name,
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return model return model
import joblib import joblib
...@@ -8863,7 +8857,6 @@ def load_model(model_name, ...@@ -8863,7 +8857,6 @@ def load_model(model_name,
if verbose: if verbose:
print('Transformation Pipeline and Model Sucessfully Loaded') print('Transformation Pipeline and Model Sucessfully Loaded')
logger.info("load_model() succesfully completed")
return joblib.load(model_name) return joblib.load(model_name)
def predict_model(estimator, def predict_model(estimator,
......
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