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I have the following code saved as main.py
import nltk
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()
import numpy
import tflearn
import tensorflow
import random
import json
import pickle
try:
nltk.download('punkt')
except:
pass
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:
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.lower()) 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)
training = numpy.array(training)
output = numpy.array(output)
with open("data.pickle", "wb") as f:
pickle.dump((words, labels, training, output), f)
tensorflow.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:
model.fit(training, output, n_epoch=1000, 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 chat():
print("Comece a falar com o Bot! (Escreva sair para parar o Bot)")
while True:
inp = input("Você:")
if inp.lower() == "sair":
break
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']
print(random.choice(responses))
else:
print("Não entendi, tente repetir a pergunta ou me diga outra coisa.")
chat()
When I run it I get the following error
C:\Users\Viana\AppData\Local\Programs\Python\Python37\python.exe C:/Users/Viana/Desktop/Projetos/Curso/Python/Jessie/Codigo/main.py
C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
curses is not supported on this machine (please install/reinstall curses for an optimal experience)
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\helpers\summarizer.py:9: The name tf.summary.merge is deprecated. Please use tf.compat.v1.summary.merge instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\helpers\trainer.py:25: The name tf.summary.FileWriter is deprecated. Please use tf.compat.v1.summary.FileWriter instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\collections.py:13: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\config.py:123: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
Scipy not supported!
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\config.py:129: The name tf.add_to_collection is deprecated. Please use tf.compat.v1.add_to_collection instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\config.py:131: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
[nltk_data] Downloading package punkt to
[nltk_data] C:\Users\Viana\AppData\Roaming\nltk_data...
[nltk_data] Package punkt is already up-to-date!
WARNING:tensorflow:From C:/Users/Viana/Desktop/Projetos/Curso/Python/Jessie/Codigo/main.py:71: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\initializations.py:174: 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
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\optimizers.py:238: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\objectives.py:66: calling reduce_sum_v1 (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
2019-09-25 19:25:50.808762: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\summaries.py:46: The name tf.summary.scalar is deprecated. Please use tf.compat.v1.summary.scalar instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\ops\math_grad.py:1250: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\helpers\trainer.py:134: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
WARNING:tensorflow:From C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\training\saver.py:1276: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.
Instructions for updating:
Use standard file APIs to check for files with this prefix.
---------------------------------
Run id: QAZDGH
Log directory: /tmp/tflearn_logs/
Traceback (most recent call last):
File "C:/Users/Viana/Desktop/Projetos/Curso/Python/Jessie/Codigo/main.py", line 81, in <module>
model.load("model.tflearn")
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\models\dnn.py", line 308, in load
self.trainer.restore(model_file, weights_only, **optargs)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\helpers\trainer.py", line 490, in restore
self.restorer.restore(self.session, model_file)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\training\saver.py", line 1278, in restore
compat.as_text(save_path))
ValueError: The passed save_path is not a valid checkpoint: C:\Users\Viana\Desktop\Projetos\Curso\Python\Jessie\Codigo\model.tflearn
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/Viana/Desktop/Projetos/Curso/Python/Jessie/Codigo/main.py", line 83, in <module>
model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\models\dnn.py", line 216, in fit
callbacks=callbacks)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\helpers\trainer.py", line 339, in fit
show_metric)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\helpers\trainer.py", line 816, in _train
tflearn.is_training(True, session=self.session)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tflearn\config.py", line 95, in is_training
tf.get_collection('is_training_ops')[0].eval(session=session)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\ops.py", line 731, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\framework\ops.py", line 5579, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "C:\Users\Viana\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\client\session.py", line 1096, in _run
---------------------------------
Training samples: 12
Validation samples: 0
--
raise RuntimeError('Attempted to use a closed Session.')
RuntimeError: Attempted to use a closed Session.
Process finished with exit code 1
I already reinstalled all the frameworks I use in the project and still the error continues. I don’t know what’s going on and I don’t have the knowledge to solve it, I would like you to help me solve it. Thank you
I found a solution for model error in this part of the code:
try:
 model.load("model.tflearn")
except:
 model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
 model.save("model.tflearn")Just remove Try: and except: and leave only the last two lines, the code in that part will look like this:model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
 model.save("model.tflearn")– GvianaM