validation_error = validate_params(request)
if validation_error:
ret = {'error': validation_error}
elif request.args['input_type'] == 'rev_id':
ret = process_rev_id(request)
else:
ret = process_text(request)
return jsonify(ret)
@app.after_request
def after_request(response):
response.headers.add('Access-Control-Allow-Origin', '*')
response.headers.add('Access-Control-Allow-Headers',
'Content-Type,Authorization')
response.headers.add('Access-Control-Allow-Methods', 'GET,PUT,POST,DELETE')
return response
model_data = json.load(open("model_paths.json"))
for k, v in model_data.items():
model = load_pipeline('./models', v['name'])
v['model'] = model
print(model.predict_proba(['f**k']))
if __name__ == "__main__":
app.run(host='0.0.0.0')
parser.add_argument('--data_dir', default = '/tmp', help ='directory for saving training data')
parser.add_argument('--model_dir', default = '/tmp', help ='directory for saving model' )
parser.add_argument('--task', default = 'attack', help = 'either attack or aggression')
parser.add_argument('--model_type', default = 'linear', help = 'either linear or mlp')
parser.add_argument('--ngram_type', default = 'char', help = 'either word or char')
parser.add_argument('--label_type', default = 'oh' , help = 'either oh or ed')
args = vars(parser.parse_args())
print("Downloading Data")
#download_training_data(args['data_dir'])
print("Parsing Data")
X, y = parse_training_data(args['data_dir'], args['task'])
print("Training Model")
clf = train_model(X, y, args['model_type'], args['ngram_type'], args['label_type'])
print(clf.predict_proba(['f**k']))
print("Saving Model")
clf_name = "%s_%s_%s_%s" % (args['task'], args['model_type'], args['ngram_type'], args['label_type'])
save_pipeline(clf, args['model_dir'], clf_name)
print("Reloading Model")
clf = load_pipeline(args['model_dir'], clf_name)
print(clf.predict_proba(['f**k']))
default='attack',
help='either attack, recipient_attack, aggression or toxicity')
parser.add_argument('--model_type',
default='linear',
help='either linear or mlp')
parser.add_argument('--ngram_type',
default='char',
help='either word or char')
parser.add_argument('--label_type', default='oh', help='either oh or ed')
args = vars(parser.parse_args())
print("Downloading Data")
download_training_data(args['data_dir'], args['task'])
print("Parsing Data")
X, y = parse_training_data(args['data_dir'], args['task'])
print("Training Model")
clf = train_model(X, y, args['model_type'], args['ngram_type'],
args['label_type'])
print(clf.predict_proba(['f**k']))
print("Saving Model")
clf_name = "%s_%s_%s_%s" % (args['task'], args['model_type'],
args['ngram_type'], args['label_type'])
save_pipeline(clf, args['model_dir'], clf_name)
print("Reloading Model")
clf = load_pipeline(args['model_dir'], clf_name)
print(clf.predict_proba(['f**k']))
validation_error = validate_params(request)
if validation_error:
ret = {'error': validation_error}
elif request.args['input_type'] == 'rev_id':
ret = process_rev_id(request)
else:
ret = process_text(request)
return jsonify(ret)
@app.after_request
def after_request(response):
response.headers.add('Access-Control-Allow-Origin', '*')
response.headers.add('Access-Control-Allow-Headers', 'Content-Type,Authorization')
response.headers.add('Access-Control-Allow-Methods', 'GET,PUT,POST,DELETE')
return response
model_data = json.load(open("model_paths.json"))
for k, v in model_data.items():
model = load_pipeline('./models', v['name'])
v['model'] = model
print(model.predict_proba(['f**k']))
if __name__ == "__main__":
app.run(host='0.0.0.0')
