Fixed Previous Error
Browse filesThere was an error saying ChatbotTrainer was None, It's now fixed.
- runCorpus.py +5 -9
runCorpus.py
CHANGED
@@ -1,7 +1,8 @@
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# runMovieCorpus.py
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import os
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from playsound3 import playsound
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import tensorflow
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import time
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import random
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import pdb
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@@ -10,12 +11,10 @@ import matplotlib.pyplot as plt
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# Personal files
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from preprocessed_dialogs import dialog_data
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from chatbotTrainer import ChatbotTrainer
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class CorpusTrainer:
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def __init__(self):
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self.chatbot_trainer = None
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self.running_trouble = None
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self.choices_yes = ["yes", "ya", "yeah", "yessir", "yesir", "y", "ye", "yah"]
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self.exit_commands = ["exit", "quit", "stop", "x", "q", ""]
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@@ -61,6 +60,7 @@ class CorpusTrainer:
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# Initialize the corpus (Needed for convo-kit to initialize) Only needed when reading/creating the dialogs
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self.corpus_path = '/root/.convokit/saved-corpora/movie-corpus'
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self.chatbot_trainer.load_corpus(self.corpus_path)
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def main(self, chatbot_trainer, user_choice, dialog_data, topConvo=0, top_num=0, play_notification=0):
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@@ -340,12 +340,8 @@ class CorpusTrainer:
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if __name__ == "__main__":
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while True:
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# Initialize the corpus (Needed for convo-kit to initialize) Only needed when reading/creating the dialogs
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corpus_path = '/root/.convokit/saved-corpora/movie-corpus'
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chatbot_trainer = ChatbotTrainer()
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chatbot_trainer.load_corpus(corpus_path)
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app = CorpusTrainer()
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user_choice = input(f"Run Supervised?({chatbot_trainer.model_filename})\n>")
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play_notification = input(f"Would you like to play a notification after each training?\nHelps with manual stopping before max_vocabulary reached... \n>")
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app.main(chatbot_trainer=chatbot_trainer, user_choice=user_choice, dialog_data=dialog_data, play_notification=play_notification)
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# self.runMovieCorpus.py
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import os
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from playsound3 import playsound
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import tensorflow
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from chatbotTrainer import ChatbotTrainer
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import time
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import random
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import pdb
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# Personal files
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from preprocessed_dialogs import dialog_data
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class CorpusTrainer:
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def __init__(self):
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self.running_trouble = None
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self.choices_yes = ["yes", "ya", "yeah", "yessir", "yesir", "y", "ye", "yah"]
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self.exit_commands = ["exit", "quit", "stop", "x", "q", ""]
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# Initialize the corpus (Needed for convo-kit to initialize) Only needed when reading/creating the dialogs
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self.corpus_path = '/root/.convokit/saved-corpora/movie-corpus'
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self.chatbot_trainer = ChatbotTrainer()
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self.chatbot_trainer.load_corpus(self.corpus_path)
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def main(self, chatbot_trainer, user_choice, dialog_data, topConvo=0, top_num=0, play_notification=0):
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if __name__ == "__main__":
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while True:
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app = CorpusTrainer()
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user_choice = input(f"Run Supervised?({app.chatbot_trainer.model_filename})\n>")
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play_notification = input(f"Would you like to play a notification after each training?\nHelps with manual stopping before max_vocabulary reached... \n>")
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app.main(chatbot_trainer=app.chatbot_trainer, user_choice=user_choice, dialog_data=dialog_data, play_notification=play_notification)
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