Keras flask API not giving me output - api

Question

I am very new to flask. I developed a document classification model using CNN model in Keras in Python3. Below is the code i am using for app.py file in windows machine.
I got the code example from here and improvised it to suit my needs
import os
from flask import jsonify
from flask import request
from flask import Flask
import numpy as np
from keras.models import model_from_json
from keras.models import load_model
from keras.preprocessing.text import Tokenizer, text_to_word_sequence
from keras.preprocessing.sequence import pad_sequences
#star Flask application
app = Flask(__name__)
path = 'C:/Users/user/Model/'
json_file = open(path+'/model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
keras_model_loaded = model_from_json(loaded_model_json)
keras_model_loaded.load_weights(path+'/model.h5')
print('Model loaded...')
def preprocess_text(text,num_max = 1000,max_review_length = 100):
tok = Tokenizer(num_words=num_max)
tok.fit_on_texts(texts)
cnn_texts_seq = tok.texts_to_sequences(texts)
cnn_texts_mat = sequence.pad_sequences(cnn_texts_seq,maxlen=max_review_length)
return cnn_texts_mat
# URL that we'll use to make predictions using get and post
#app.route('/predict',methods=['GET','POST'])
def predict():
try:
text = request.args.get('text')
x = preprocess_text(text)
y = int(np.round(keras_model_loaded.predict(x)))
#print(y)
return jsonify({'prediction': str(y)})
except:
response = jsonify({'error': 'problem predicting'})
response.status_code = 400
return response
if __name__ == "__main__":
port = int(os.environ.get('PORT', 5000))
# Run locally
app.run(host='0.0.0.0', port=port)
In my windows machine i navigate to the path in the console where i have saved app.py file and execute the command py -3.6 app.py
When i go the url http://localhost:5000/predict and type in browser
http://localhost:5000/predict?text=I've had my Fire HD 8 two weeks now and I love it. This tablet is a great value. We are Prime Members and that is where this tablet SHINES.
it does not give me any class as output, but instead i get this as output {"error":"problem predicting"}.
Any help on how to fix this?
Edit: I removed the try except block in the predict function. Below is how predict function looks like
def predict():
text = request.args.get('text')
x = preprocess_text(text)
y = int(np.round(keras_model_loaded.predict(x)))
return jsonify({'prediction': str(y)})
Now i am getting exception. error message is
[2018-05-28 18:33:59,008] ERROR in app: Exception on /predict [GET]
Traceback (most recent call last):
File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\flask\app.py", line 2292, in wsgi_app
response = self.full_dispatch_request()
File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\flask\app.py", line 1815, in full_dispatch_request
rv = self.handle_user_exception(e)
File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\flask\app.py", line 1718, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\flask\_compat.py", line 35, in reraise
raise value
File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\flask\app.py", line 1813, in full_dispatch_request
rv = self.dispatch_request()
File "C:\Users\User\AppData\Local\Programs\Python\Python36\lib\site-packages\flask\app.py", line 1799, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "app.py", line 59, in predict
x = preprocess_text(text)
File "app.py", line 37, in preprocess_text
tok.fit_on_texts(texts)
NameError: name 'texts' is not defined
127.0.0.1 - - [28/May/2018 18:33:59] "GET /predict?text=I%27ve%20had%20my%20Fire%20HD%208%20two%20weeks%20now%20and%20I%20love%20it.%20This%20tablet%20is%20a%20great%20value.%20We%20are%20Prime%20Members%20and%20that%20is%20where%20this%20tablet%20SHINES. HTTP/1.1" 500 -
Edit2: I have edited code to
def preprocess_text(texts,num_max = 1000,max_review_length = 100):
tok = Tokenizer(num_words=num_max)
tok.fit_on_texts(texts)
cnn_texts_seq = tok.texts_to_sequences(texts)
cnn_texts_mat = pad_sequences(cnn_texts_seq,maxlen=max_review_length)
return cnn_texts_mat
# URL that we'll use to make predictions using get and post
#app.route('/predict',methods=['GET','POST'])
def predict():
text = request.args.get('text')
x = preprocess_text(text)
y = keras_model_loaded.predict(x)
return jsonify({'prediction': str(y)})
and now the error message is
packages\tensorflow\python\framework\ops.py", line 3402, in _as_graph_element_locked
raise ValueError("Tensor %s is not an element of this graph." % obj)
ValueError: Tensor Tensor("output/Sigmoid:0", shape=(?, 1), dtype=float32) is not an element of this graph.
127.0.0.1 - - [28/May/2018 19:39:11] "GET /predict?text=I%27ve%20had%20my%20Fire%20HD%208%20two%20weeks%20now%20and%20I%20love%20it.%20This%20tablet%20is%20a%20great%20value.%20We%20are%20Prime%20Members%20and%20that%20is%20where%20this%20tablet%20SHINES. HTTP/1.1" 500 -
I am unable to understand and debug this error. Not sure what this means. Can anyone help me understand this error and suggest a solution for this?
Also, i am unable to post the entire error message in stackoverflow as most of the chunk in my question appears to be code.
Thanks!!

Answer 1

Now it is what I guessed. There is a problem when using cross-threads with Flask and Tensorflow. Here is a fix for it:
import tensorflow as tf
# ...
graph = tf.get_default_graph()
def predict():
text = request.args.get('text')
x = preprocess_text(text)
with graph.as_default():
y = int(np.round(keras_model_loaded.predict(x)))
return jsonify({'prediction': str(y)})
by wrapping the prediction to forcefully use the default graph.