I made a chatbot using tensorflow. But every time I run the chatbot freshly, tensorflow warnings keeps showing a I have to wait until it finishes. I want to ignore all the warnings. I have tried some methods that's listed below but in vain. Here's the whole code, the logs and also the methods I have tried.
import nltk
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()
import numpy
import tflearn
import tensorflow
import random
import json
import pickle
import warnings
with open("intents.json") as file:
data = json.load(file)
try:
with open("data.pickle", "rb") as f:
words, labels, training, output = pickle.load(f)
except Exception as e:
words = []
labels = []
docs_x = []
docs_y = []
for intent in data["intents"]:
for pattern in intent["patterns"]:
wrds = nltk.word_tokenize(pattern)
words.extend(wrds)
docs_x.append(wrds)
docs_y.append(intent["tag"])
if intent["tag"] not in labels:
labels.append(intent["tag"])
words = [stemmer.stem(w.lower()) for w in words if w != "?"]
words = sorted(list(set(words)))
labels = sorted(labels)
training = []
output = []
out_empty = [0 for _ in range(len(labels))]
for x, doc in enumerate(docs_x):
bag = []
wrds = [stemmer.stem(w) for w in doc]
for w in words:
if w in wrds:
bag.append(1)
else:
bag.append(0)
output_row = out_empty[:]
output_row[labels.index(docs_y[x])] = 1
training.append(bag)
output.append(output_row)
with open("data.pickle", "wb") as f:
pickle.dump((words, labels, training, output), f)
training = numpy.array(training)
output = numpy.array(output)
tensorflow.compat.v1.reset_default_graph()
net = tflearn.input_data(shape=[None, len(training[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
net = tflearn.regression(net)
model = tflearn.DNN(net)
try:
model.load("model.tflearn")
except Exception as e:
model.fit(training, output, n_epoch=2500, batch_size=8, show_metric=True)
model.save("model.tflearn")
def bag_of_words(s, words):
bag = [0 for _ in range(len(words))]
s_words = nltk.word_tokenize(s)
s_words = [stemmer.stem(word.lower()) for word in s_words]
for se in s_words:
for i, w in enumerate(words):
if w == se:
bag[i] = 1
return numpy.array(bag)
def get_output(inp):
inp = str(inp)
responses = ""
results = model.predict([bag_of_words(inp, words)])[0]
results_index = numpy.argmax(results)
tag = labels[results_index]
if results[results_index] > 0.7:
for tg in data["intents"]:
if tg['tag'] == tag:
responses = tg['responses']
responses = str(random.choice(responses))
else:
responses = "I didn't get that"
return responses
if __name__ == "__main__":
inp = input(">> ")
get_out = get_output(inp)
print(get_out)
python version 3.10 - tensorflow version 2.9.1
logs:
2022-09-26 00:49:10.472563: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-09-26 00:49:10.485966: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
WARNING:tensorflow:From C:\Python 310\lib\site-packages\tensorflow\python\compat\v2_compat.py:107: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term
curses is not supported on this machine (please install/reinstall curses for an optimal experience)
2.9.1
2022-09-26 00:50:40.291595: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-09-26 00:50:40.305928: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
WARNING:tensorflow:From C:\Python 310\lib\site-packages\tensorflow\python\compat\v2_compat.py:107: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term
curses is not supported on this machine (please install/reinstall curses for an optimal experience)
WARNING:tensorflow:From C:\Python 310\lib\site-packages\tflearn\initializations.py:164: calling TruncatedNormal.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
2022-09-26 00:50:48.663462: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-09-26 00:50:48.677293: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
2022-09-26 00:50:48.692157: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found
2022-09-26 00:50:48.707790: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2022-09-26 00:50:48.723267: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
2022-09-26 00:50:48.738537: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusolver64_11.dll'; dlerror: cusolver64_11.dll not found
2022-09-26 00:50:48.754577: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found
2022-09-26 00:50:48.770482: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2022-09-26 00:50:48.784207: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1850] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2022-09-26 00:50:48.817031: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the
following CPU instructions in performance-critical operations: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-09-26 00:50:49.258725: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:354] MLIR V1 optimization pass is not enabled
tried everthing like:
import logging
import warnings
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow
tensorflow.get_logger().setLevel('INFO')
tensorflow.compat.v1.logging.set_verbosity(tensorflow.compat.v1.logging.ERROR)
logging.getLogger('tensorflow').setLevel(logging.FATAL)
warnings.filterwarnings(action="ignore")