Text_Generation_LSTM_1.1v.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyPixGn+Orwzszy85Jpb/47C"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"CC8ZawYG0adm","executionInfo":{"status":"ok","timestamp":1691874522585,"user_tz":-330,"elapsed":32229,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"6ec4601c-bbdd-4c23-be98-bffdb00fcb78"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive/\n"]}],"source":["# mounting the drive to read the data\n","from google.colab import drive\n","drive.mount('/content/drive/')"]},{"cell_type":"code","source":["import tensorflow as tf\n","import pandas as pd\n","import numpy as np\n","from tensorflow.keras.callbacks import ModelCheckpoint\n","from tensorflow import keras"],"metadata":{"id":"SDjJORRb0hVd"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# reading the data from local google drive\n","with open('/content/drive/MyDrive/Colab_Notebooks/directory/Txt_the_enemy_3.txt') as story:\n","  story_data = story.read()"],"metadata":{"id":"6y1GJZDl0ote"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["print(story_data)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"w9D2iv8R3sZi","executionInfo":{"status":"ok","timestamp":1691874528723,"user_tz":-330,"elapsed":100,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"bac7959c-0a8a-4b07-98eb-32c970f65e31"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Dr. Sadao Hoki's house was built on a spot off the Japanese coast. As a little boy he had often played there. His low\n","\n","square stone house was built above the narrowbeach. His father had taken him often to the islands not far from the\n","\n","shore. He would say to the serious little boy at his side.\n","\n","\"Those islands out there are the stepping-stones to the future of Japan.\"\n","\n","\"Where shall we step from them?\" Sadao had asked.\n","\n","\"Who knows?\" his father had answered. \"Who can limit our future? It depends on what we make it.\"\n","\n","Sadao had paid attention to this as he did everything his father said. His father never joked or played with him. However,\n","\n","he gave all his attention to his only son. Sadao knew that his education\" was the most important thing in the world to his\n","\n","father. For this reason he had been sent at twenty-two to America to learn all that could be learned of surgery and\n","\n","medicine. He had come back at thirty. Before his father died, he had seen Sadao become famous not only as a surgeon\n","\n","but as a scientist. Sadao was now working on an important medical discovery, so he had not been sent abroad with the\n","\n","troops. He also knew there was a chance the old General might need an operation. This was another reason why Sadao\n","\n","was being kept in Japan.\n","\n","The weather had been surprisingly warm for the past few days. There was heavy fog at night.\n","\n","The door opened and Hana looked out. She was wearing a dark-blue kimono'. She came to him affectionately. She put\n","\n","her arm through his, smiled, and said nothing. He had met Hana in America, but he had waited to fall in love with her until\n","\n","he was sure she believed in traditional Japanese values Otherwise, his father would never have received her. He thought\n","\n","about how lucky he was that he had found her by chance really\", at an American professor's house.\n","\n","The professor and his wife had been kind people. They wanted to do something for their few foreign students\". The\n","\n","students, though bored Sadao had often told Hana that he had almost not gone to Professor Harley's house that night.\n","\n","But he had gone and there he had found Hana, a new student. They had not married carelessly in America. They had\n","\n","finished their studies and had come home to Japan. After his father had seen her. the marriage was arranged in the old\n","\n","Japanese way, although Sadao and Hana had talked everything over before. The were perfectly happy.\n","\n","She laid her cheek -against his arm. It was at this moment that both of them saw something black come out of the mists\".\n","\n","It was a man. He was thr0u.n out of the ocean by a wave''. He staggered a few steps. his arms above his head. Then the\n","\n","mists hid him again.\n","\n","\"Who is that?\" Hana cried. She dropped Sadao's arm and they both leaned over the railing' of the Now they saw him\n","\n","again. The man was on his hands and knees crawling\". Then they saw him fall on his face and lie there.\n","\n","\"A fisherman perhaps.\" Sadao said, \"washed from his boat.\" He ran quickly down the steps. Behind him Hana came,\n","\n","her wide sleeves flying. A mile or two away on either side, there were fishing villages.\n","\n","Somehow the man had managed to go through the rocks. He must be badly hurt. They saw that the sand on one side of\n","\n","him was red.\n","\n","\"He is wounded-.\" Sadao exclaimed. He hurried to the man. ,ho lay there without moving. his face in the sand. An old\n","\n","cap stuck to his head. His clothes were wet rags.\n","\n","Sadao stoopedh. Hana at his side, and turned the man's head. 'hey saw the face.\n","\n","\"A white man!\" Hana whispered.\n","\n","Yes, it was a white man. His wet yellow hair, long, as though had not been cut for many weeks . On his young and\n","\n","tortured- he had a  rough yellow beard. He was unconscious. Sadao remembered the wound and with his expert fingers\n","\n","began to search for it. Blood flowed freshly\" at his touch. On the right side of his lower back Sadao saw that a gun wound\n","\n","had been reopened. The flesh was black. Sometime not many days ago, the man had been shot and had not been\n","\n","saved. It his bad luck now that a rock had struck his wound.\n","\n","\"Oh, how he is bleeding!\" Hana whispered again. The mists lid them completely now. At this time of day no one came\n","\n","by. The fishermen had gone home.\n","\n","\"What shall are do with this man?\" Sadao said.\n","\n","But his hands seemed to have a will of their own. They worked to stop the bleeding. The man moaned with pain but he\n","\n","did not awaken\".\n","\n","\"The best thing that we could do would be to put him back in the sea,\" Sadao said, answering himself.\n","\n","Now that the bleeding was stopped for the moment, he stood up and dusted the sand from his hands\"'.\n","\n","\"Yes. that would be best,\" Hana said. But she continued to look at the man.\n","\n","\"lf we sheltered\" a white man in our house we would be arrested. But if we turned him in as a prisoner, he would certainly\n","\n","die,\" Sadao said.\n","\n","\"The kindest thing would be to put him back into the sea,\" Hana said. But neither of them moved.\n","\n","\"What is he?\" Hana whispered. \"There is something about him that looks American,\" Sadao said. He picked up the cap.\n","\n","\"A sailor,\" he said, \"from an American warship.\" He spelled it out: \"U.S. Navy.\" The man was a prisoner of war! \"He has\n","\n","escaped,\"Hana cried softly, \"and that is why he was shot.\" \"In the back,\" Sadao agreed. They hesitated, looking at each\n","\n","other. Then Hana said, \"Are we able to put him back into the sea?\" \"If I am able, are you?\" Sadao asked. \"So.\" Hana\n","\n","said. \"But if you can do it alone ...\" Sadao hesitated again.\n","\n","\"The strange thing is,\" he said, \"that if the man were whole6 I could turn him over to the police without difficulty. I care\n","\n","nothing for him. He is my enemy. All Americans are my enemy. -And he is only a common fellow. You see how foolish his\n","\n","face is. But since he is wounded ...\"\n","\n","\"You also cannot throw him back to the sea,\" Hana said. \"Then there is only one thing to do. We must carry him into the\n","\n","house.\"\n","\n","\"But the servants\"?\" Sadao asked.\n","\n","\"We must simply tell them that we plan to give him to the police. And we must, Sadao. We must think of the children and\n","\n","of our position1. It woiild endanger all of us if we did not give this man over as a prisoner of war.\"\n","\n","\"Certainly,\" Sadao agreed. \"I would not think of doing anything else.\"\n","\n","Together they lifted the man. He was very light. They carried him up the steps and into an empty bedroom. It bad been\n","\n","the bedroom of Sadao's father. Since his death it had not been used. They laid the man\" on the floor mat. Everything\n","\n","here had been Japanese-to please the old man. Sadao's father would never in his own home sit on a chair or sleep in a\n","\n","foreign bed Hana went to the wall cupboards and slid back a door) and took out a soft quilt. She hesitateds. The quilt\n","\n","was covered with flowered silk.\n","\n","\"He is so dirty,\" she whispered.\n","\n","\"Yes, he had better be washed,\" Sadao agreed. If you will bring hot water I will wash him.\"\n","\n","\"I cannot bear for you to touch him,\" she said. \"We shall have to tell the servants he is here. 1 will tell Yumi now. She can\n","\n","leave the children for a few minutes and she can wash him.\"\n","\n","Sadao thought a moment. \"Yes,\" he agreed. \"You tell Yumi and I will tell the others.\"\n","\n","The whitenessS of the man's face moved Sadao to feel his pulse. It was faint\" but it was there. He put his hand against\n","\n","the man's cold chest\". The heart too was still alive.\n","\n","\"He will die unless he is operated on,\" Sadao said. \"The question is whether he will not die anyway.\"\n","\n","Hana cried out in fear. \"Don't try to save him! What if he should live?\"\n","\n","\"What if he should die?\" Sadao replied. He looked at the motionless man. This man must be very healthy or he would\n","\n","have been dead by now. He looked so very young.\n","\n","\"You mean die from the operation?\" Hana asked.\n","\n","\"Yes,\" Sadao said.\n","\n","Hana thought about this and when she did not answer, Sadao turned away.\n","\n","\"In any case something must be done with him,\" he said, \"and first he must be washed.\"\n","\n","He went quickly out of the room and Hana came behind him. She did not wish to be left alone with the\n","\n","white man. He was the first she had seen since she left America. He seemed to have nothing to do with\n","\n","those whom she had known there. Here he was her enemy, a threatI5, living or dead.\n","\n","She turned to the nursery and called, \"Yumi!\"\n","\n","The children heard her voice. She had to go in for a moment and smile at them and play with the baby,\n","\n","now nearly three months old.\n","\n","To Yumi she said, \"Come with me!\"\n","\n","\"I will put the baby to bed,\" Yumi said. \"He is ready.\"\n","\n","She went with Yumi into the bedroom next to the nursery. She stood with the boy in her arms while\n","\n","Yumi spread the sleeping quilts on the floor and laid the baby between them.\n","\n","Then Hana led the way quickly to the kitchen. The two servants were frightened at what their master\n","\n","had just told them.\n","\n","\"The master ought not to heal the wounds of this white man,\"\n","\n","The old gardener said to Hana. \"The white man ought to die. First he was shot. Then the sea caught\n","\n","him and wounded him, with her rocks. If the master heals what the gun did and what the\n","\n","sea did, they will take revenge on us.\"\n","\n","\"I will tell him what you say,\" Hana answered politely. But she herself was also frightened, although she\n","\n","was not superstitious as the old man was. Could it ever be right to help an enemy?\n","\n","Nevertheless, she told Yumi to bring the hot water to - the room where the white man was.\n","\n","She went ahead and slid back the partitions\". Sadao was not, there yet. Yumi, following, put down her\n","\n","wooden bucket\". Then she went over to the white man.\n","\n","\"I have never washed a white man,\" she said, \"and I will not wash one so dirty now.\"\n","\n","Hana cried, \"You will do what your master commands you!\"\n","\n","\"My master ought not to command me to wash the enemy,\" Yumi said stubbornly.\n","\n","The look upon Yumi's round dull face made Hana feel afraid.\n","\n","What if she should report\" something that was not as it happened?\n","\n","\"Very well,\" she said with dignity. \"You understand we only want to bring him to his senses so that we\n","\n","can turn him over as a prisoner?\"\n","\n","\"I will have nothing to do with it,\" Yumi said. \"I am a poor person and it is not my business.\"\n","\n","\"Then please,\" Hana said gently, \"return to your own work.\"\n","\n","Yumi left the room. But this left Hana alone with the white man. She might have been too afraid to stay,\n","\n","but her anger at Yumi gave her courage\".\n","\n","\"Stupid Yumi!\" she said. \"Is this anything but a man? A wounded helpless man!\"\n","\n","She untied the rags that covered the white man. She dipped a small clean towel into the steaming hot\n","\n","water and washed his face carefully. She kept on washing him until his upper body was quite clean. But\n","\n","she dared not turn him over.\n","\n","Where was Sadao? Now her anger was disappearing and she was anxiousg again. She got up and\n","\n","wiped her hands. She then put the quilt over him so he wouldn't be cold.\n","\n","Sadao!\" she called softly.\n","\n","He had been about to come in when she called. She saw that he had brought his surgeon's emergency\n"]}]},{"cell_type":"code","source":["# data cleaning process\n","import re                                # Regular expressions to use sub function for replacing the useless text from the data\n","\n","def clean_text(text):\n","  text = re.sub(r',', '', text)\n","  text = re.sub(r'\\'', '',  text)\n","  text = re.sub(r'\\\"', '', text)\n","  text = re.sub(r'\\(', '', text)\n","  text = re.sub(r'\\)', '', text)\n","  text = re.sub(r'\\n', '', text)\n","  text = re.sub(r'“', '', text)\n","  text = re.sub(r'”', '', text)\n","  text = re.sub(r'’', '', text)\n","  text = re.sub(r'\\.', '', text)\n","  text = re.sub(r';', '', text)\n","  text = re.sub(r':', '', text)\n","  text = re.sub(r'\\-', '', text)\n","\n","  return text"],"metadata":{"id":"8v44_46A3t-D"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# cleaning the data\n","lower_data = story_data.lower()           # Converting the string to lower case to get uniformity\n","\n","split_data = lower_data.splitlines()      # Splitting the data to get every line seperately but this will give the list of uncleaned data\n","\n","print(split_data)\n","\n","final = ''                                # initiating a argument with blank string to hold the values of final cleaned data\n","\n","for line in split_data:\n","  line = clean_text(line)\n","  final += '\\n' + line\n","\n","print(final)\n","\n","final_data = final.split('\\n')       # splitting again to get list of cleaned and splitted data ready to be processed\n","print(final_data)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"tHU1FSmx30Ri","executionInfo":{"status":"ok","timestamp":1691874528724,"user_tz":-330,"elapsed":96,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"c2c21881-711c-4e54-9842-54a65ec90d3e"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["[\"dr. sadao hoki's house was built on a spot off the japanese coast. as a little boy he had often played there. his low\", '', 'square stone house was built above the narrowbeach. his father had taken him often to the islands not far from the', '', 'shore. he would say to the serious little boy at his side.', '', '\"those islands out there are the stepping-stones to the future of japan.\"', '', '\"where shall we step from them?\" sadao had asked.', '', '\"who knows?\" his father had answered. \"who can limit our future? it depends on what we make it.\"', '', 'sadao had paid attention to this as he did everything his father said. his father never joked or played with him. however,', '', 'he gave all his attention to his only son. sadao knew that his education\" was the most important thing in the world to his', '', 'father. for this reason he had been sent at twenty-two to america to learn all that could be learned of surgery and', '', 'medicine. he had come back at thirty. before his father died, he had seen sadao become famous not only as a surgeon', '', 'but as a scientist. sadao was now working on an important medical discovery, so he had not been sent abroad with the', '', 'troops. he also knew there was a chance the old general might need an operation. this was another reason why sadao', '', 'was being kept in japan.', '', 'the weather had been surprisingly warm for the past few days. there was heavy fog at night.', '', \"the door opened and hana looked out. she was wearing a dark-blue kimono'. she came to him affectionately. she put\", '', 'her arm through his, smiled, and said nothing. he had met hana in america, but he had waited to fall in love with her until', '', 'he was sure she believed in traditional japanese values otherwise, his father would never have received her. he thought', '', 'about how lucky he was that he had found her by chance really\", at an american professor\\'s house.', '', 'the professor and his wife had been kind people. they wanted to do something for their few foreign students\". the', '', \"students, though bored sadao had often told hana that he had almost not gone to professor harley's house that night.\", '', 'but he had gone and there he had found hana, a new student. they had not married carelessly in america. they had', '', 'finished their studies and had come home to japan. after his father had seen her. the marriage was arranged in the old', '', 'japanese way, although sadao and hana had talked everything over before. the were perfectly happy.', '', 'she laid her cheek -against his arm. it was at this moment that both of them saw something black come out of the mists\".', '', \"it was a man. he was thr0u.n out of the ocean by a wave''. he staggered a few steps. his arms above his head. then the\", '', 'mists hid him again.', '', '\"who is that?\" hana cried. she dropped sadao\\'s arm and they both leaned over the railing\\' of the now they saw him', '', 'again. the man was on his hands and knees crawling\". then they saw him fall on his face and lie there.', '', '\"a fisherman perhaps.\" sadao said, \"washed from his boat.\" he ran quickly down the steps. behind him hana came,', '', 'her wide sleeves flying. a mile or two away on either side, there were fishing villages.', '', 'somehow the man had managed to go through the rocks. he must be badly hurt. they saw that the sand on one side of', '', 'him was red.', '', '\"he is wounded-.\" sadao exclaimed. he hurried to the man. ,ho lay there without moving. his face in the sand. an old', '', 'cap stuck to his head. his clothes were wet rags.', '', \"sadao stoopedh. hana at his side, and turned the man's head. 'hey saw the face.\", '', '\"a white man!\" hana whispered.', '', 'yes, it was a white man. his wet yellow hair, long, as though had not been cut for many weeks . on his young and', '', 'tortured- he had a  rough yellow beard. he was unconscious. sadao remembered the wound and with his expert fingers', '', 'began to search for it. blood flowed freshly\" at his touch. on the right side of his lower back sadao saw that a gun wound', '', 'had been reopened. the flesh was black. sometime not many days ago, the man had been shot and had not been', '', 'saved. it his bad luck now that a rock had struck his wound.', '', '\"oh, how he is bleeding!\" hana whispered again. the mists lid them completely now. at this time of day no one came', '', 'by. the fishermen had gone home.', '', '\"what shall are do with this man?\" sadao said.', '', 'but his hands seemed to have a will of their own. they worked to stop the bleeding. the man moaned with pain but he', '', 'did not awaken\".', '', '\"the best thing that we could do would be to put him back in the sea,\" sadao said, answering himself.', '', 'now that the bleeding was stopped for the moment, he stood up and dusted the sand from his hands\"\\'.', '', '\"yes. that would be best,\" hana said. but she continued to look at the man.', '', '\"lf we sheltered\" a white man in our house we would be arrested. but if we turned him in as a prisoner, he would certainly', '', 'die,\" sadao said.', '', '\"the kindest thing would be to put him back into the sea,\" hana said. but neither of them moved.', '', '\"what is he?\" hana whispered. \"there is something about him that looks american,\" sadao said. he picked up the cap.', '', '\"a sailor,\" he said, \"from an american warship.\" he spelled it out: \"u.s. navy.\" the man was a prisoner of war! \"he has', '', 'escaped,\"hana cried softly, \"and that is why he was shot.\" \"in the back,\" sadao agreed. they hesitated, looking at each', '', 'other. then hana said, \"are we able to put him back into the sea?\" \"if i am able, are you?\" sadao asked. \"so.\" hana', '', 'said. \"but if you can do it alone ...\" sadao hesitated again.', '', '\"the strange thing is,\" he said, \"that if the man were whole6 i could turn him over to the police without difficulty. i care', '', 'nothing for him. he is my enemy. all americans are my enemy. -and he is only a common fellow. you see how foolish his', '', 'face is. but since he is wounded ...\"', '', '\"you also cannot throw him back to the sea,\" hana said. \"then there is only one thing to do. we must carry him into the', '', 'house.\"', '', '\"but the servants\"?\" sadao asked.', '', '\"we must simply tell them that we plan to give him to the police. and we must, sadao. we must think of the children and', '', 'of our position1. it woiild endanger all of us if we did not give this man over as a prisoner of war.\"', '', '\"certainly,\" sadao agreed. \"i would not think of doing anything else.\"', '', 'together they lifted the man. he was very light. they carried him up the steps and into an empty bedroom. it bad been', '', 'the bedroom of sadao\\'s father. since his death it had not been used. they laid the man\" on the floor mat. everything', '', \"here had been japanese-to please the old man. sadao's father would never in his own home sit on a chair or sleep in a\", '', 'foreign bed hana went to the wall cupboards and slid back a door) and took out a soft quilt. she hesitateds. the quilt', '', 'was covered with flowered silk.', '', '\"he is so dirty,\" she whispered.', '', '\"yes, he had better be washed,\" sadao agreed. if you will bring hot water i will wash him.\"', '', '\"i cannot bear for you to touch him,\" she said. \"we shall have to tell the servants he is here. 1 will tell yumi now. she can', '', 'leave the children for a few minutes and she can wash him.\"', '', 'sadao thought a moment. \"yes,\" he agreed. \"you tell yumi and i will tell the others.\"', '', 'the whitenesss of the man\\'s face moved sadao to feel his pulse. it was faint\" but it was there. he put his hand against', '', 'the man\\'s cold chest\". the heart too was still alive.', '', '\"he will die unless he is operated on,\" sadao said. \"the question is whether he will not die anyway.\"', '', 'hana cried out in fear. \"don\\'t try to save him! what if he should live?\"', '', '\"what if he should die?\" sadao replied. he looked at the motionless man. this man must be very healthy or he would', '', 'have been dead by now. he looked so very young.', '', '\"you mean die from the operation?\" hana asked.', '', '\"yes,\" sadao said.', '', 'hana thought about this and when she did not answer, sadao turned away.', '', '\"in any case something must be done with him,\" he said, \"and first he must be washed.\"', '', 'he went quickly out of the room and hana came behind him. she did not wish to be left alone with the', '', 'white man. he was the first she had seen since she left america. he seemed to have nothing to do with', '', 'those whom she had known there. here he was her enemy, a threati5, living or dead.', '', 'she turned to the nursery and called, \"yumi!\"', '', 'the children heard her voice. she had to go in for a moment and smile at them and play with the baby,', '', 'now nearly three months old.', '', 'to yumi she said, \"come with me!\"', '', '\"i will put the baby to bed,\" yumi said. \"he is ready.\"', '', 'she went with yumi into the bedroom next to the nursery. she stood with the boy in her arms while', '', 'yumi spread the sleeping quilts on the floor and laid the baby between them.', '', 'then hana led the way quickly to the kitchen. the two servants were frightened at what their master', '', 'had just told them.', '', '\"the master ought not to heal the wounds of this white man,\"', '', 'the old gardener said to hana. \"the white man ought to die. first he was shot. then the sea caught', '', 'him and wounded him, with her rocks. if the master heals what the gun did and what the', '', 'sea did, they will take revenge on us.\"', '', '\"i will tell him what you say,\" hana answered politely. but she herself was also frightened, although she', '', 'was not superstitious as the old man was. could it ever be right to help an enemy?', '', 'nevertheless, she told yumi to bring the hot water to - the room where the white man was.', '', 'she went ahead and slid back the partitions\". sadao was not, there yet. yumi, following, put down her', '', 'wooden bucket\". then she went over to the white man.', '', '\"i have never washed a white man,\" she said, \"and i will not wash one so dirty now.\"', '', 'hana cried, \"you will do what your master commands you!\"', '', '\"my master ought not to command me to wash the enemy,\" yumi said stubbornly.', '', \"the look upon yumi's round dull face made hana feel afraid.\", '', 'what if she should report\" something that was not as it happened?', '', '\"very well,\" she said with dignity. \"you understand we only want to bring him to his senses so that we', '', 'can turn him over as a prisoner?\"', '', '\"i will have nothing to do with it,\" yumi said. \"i am a poor person and it is not my business.\"', '', '\"then please,\" hana said gently, \"return to your own work.\"', '', 'yumi left the room. but this left hana alone with the white man. she might have been too afraid to stay,', '', 'but her anger at yumi gave her courage\".', '', '\"stupid yumi!\" she said. \"is this anything but a man? a wounded helpless man!\"', '', 'she untied the rags that covered the white man. she dipped a small clean towel into the steaming hot', '', 'water and washed his face carefully. she kept on washing him until his upper body was quite clean. but', '', 'she dared not turn him over.', '', 'where was sadao? now her anger was disappearing and she was anxiousg again. she got up and', '', \"wiped her hands. she then put the quilt over him so he wouldn't be cold.\", '', 'sadao!\" she called softly.', '', \"he had been about to come in when she called. she saw that he had brought his surgeon's emergency\"]\n","\n","dr sadao hokis house was built on a spot off the japanese coast as a little boy he had often played there his low\n","\n","square stone house was built above the narrowbeach his father had taken him often to the islands not far from the\n","\n","shore he would say to the serious little boy at his side\n","\n","those islands out there are the steppingstones to the future of japan\n","\n","where shall we step from them? sadao had asked\n","\n","who knows? his father had answered who can limit our future? it depends on what we make it\n","\n","sadao had paid attention to this as he did everything his father said his father never joked or played with him however\n","\n","he gave all his attention to his only son sadao knew that his education was the most important thing in the world to his\n","\n","father for this reason he had been sent at twentytwo to america to learn all that could be learned of surgery and\n","\n","medicine he had come back at thirty before his father died he had seen sadao become famous not only as a surgeon\n","\n","but as a scientist sadao was now working on an important medical discovery so he had not been sent abroad with the\n","\n","troops he also knew there was a chance the old general might need an operation this was another reason why sadao\n","\n","was being kept in japan\n","\n","the weather had been surprisingly warm for the past few days there was heavy fog at night\n","\n","the door opened and hana looked out she was wearing a darkblue kimono she came to him affectionately she put\n","\n","her arm through his smiled and said nothing he had met hana in america but he had waited to fall in love with her until\n","\n","he was sure she believed in traditional japanese values otherwise his father would never have received her he thought\n","\n","about how lucky he was that he had found her by chance really at an american professors house\n","\n","the professor and his wife had been kind people they wanted to do something for their few foreign students the\n","\n","students though bored sadao had often told hana that he had almost not gone to professor harleys house that night\n","\n","but he had gone and there he had found hana a new student they had not married carelessly in america they had\n","\n","finished their studies and had come home to japan after his father had seen her the marriage was arranged in the old\n","\n","japanese way although sadao and hana had talked everything over before the were perfectly happy\n","\n","she laid her cheek against his arm it was at this moment that both of them saw something black come out of the mists\n","\n","it was a man he was thr0un out of the ocean by a wave he staggered a few steps his arms above his head then the\n","\n","mists hid him again\n","\n","who is that? hana cried she dropped sadaos arm and they both leaned over the railing of the now they saw him\n","\n","again the man was on his hands and knees crawling then they saw him fall on his face and lie there\n","\n","a fisherman perhaps sadao said washed from his boat he ran quickly down the steps behind him hana came\n","\n","her wide sleeves flying a mile or two away on either side there were fishing villages\n","\n","somehow the man had managed to go through the rocks he must be badly hurt they saw that the sand on one side of\n","\n","him was red\n","\n","he is wounded sadao exclaimed he hurried to the man ho lay there without moving his face in the sand an old\n","\n","cap stuck to his head his clothes were wet rags\n","\n","sadao stoopedh hana at his side and turned the mans head hey saw the face\n","\n","a white man! hana whispered\n","\n","yes it was a white man his wet yellow hair long as though had not been cut for many weeks  on his young and\n","\n","tortured he had a  rough yellow beard he was unconscious sadao remembered the wound and with his expert fingers\n","\n","began to search for it blood flowed freshly at his touch on the right side of his lower back sadao saw that a gun wound\n","\n","had been reopened the flesh was black sometime not many days ago the man had been shot and had not been\n","\n","saved it his bad luck now that a rock had struck his wound\n","\n","oh how he is bleeding! hana whispered again the mists lid them completely now at this time of day no one came\n","\n","by the fishermen had gone home\n","\n","what shall are do with this man? sadao said\n","\n","but his hands seemed to have a will of their own they worked to stop the bleeding the man moaned with pain but he\n","\n","did not awaken\n","\n","the best thing that we could do would be to put him back in the sea sadao said answering himself\n","\n","now that the bleeding was stopped for the moment he stood up and dusted the sand from his hands\n","\n","yes that would be best hana said but she continued to look at the man\n","\n","lf we sheltered a white man in our house we would be arrested but if we turned him in as a prisoner he would certainly\n","\n","die sadao said\n","\n","the kindest thing would be to put him back into the sea hana said but neither of them moved\n","\n","what is he? hana whispered there is something about him that looks american sadao said he picked up the cap\n","\n","a sailor he said from an american warship he spelled it out us navy the man was a prisoner of war! he has\n","\n","escapedhana cried softly and that is why he was shot in the back sadao agreed they hesitated looking at each\n","\n","other then hana said are we able to put him back into the sea? if i am able are you? sadao asked so hana\n","\n","said but if you can do it alone  sadao hesitated again\n","\n","the strange thing is he said that if the man were whole6 i could turn him over to the police without difficulty i care\n","\n","nothing for him he is my enemy all americans are my enemy and he is only a common fellow you see how foolish his\n","\n","face is but since he is wounded \n","\n","you also cannot throw him back to the sea hana said then there is only one thing to do we must carry him into the\n","\n","house\n","\n","but the servants? sadao asked\n","\n","we must simply tell them that we plan to give him to the police and we must sadao we must think of the children and\n","\n","of our position1 it woiild endanger all of us if we did not give this man over as a prisoner of war\n","\n","certainly sadao agreed i would not think of doing anything else\n","\n","together they lifted the man he was very light they carried him up the steps and into an empty bedroom it bad been\n","\n","the bedroom of sadaos father since his death it had not been used they laid the man on the floor mat everything\n","\n","here had been japaneseto please the old man sadaos father would never in his own home sit on a chair or sleep in a\n","\n","foreign bed hana went to the wall cupboards and slid back a door and took out a soft quilt she hesitateds the quilt\n","\n","was covered with flowered silk\n","\n","he is so dirty she whispered\n","\n","yes he had better be washed sadao agreed if you will bring hot water i will wash him\n","\n","i cannot bear for you to touch him she said we shall have to tell the servants he is here 1 will tell yumi now she can\n","\n","leave the children for a few minutes and she can wash him\n","\n","sadao thought a moment yes he agreed you tell yumi and i will tell the others\n","\n","the whitenesss of the mans face moved sadao to feel his pulse it was faint but it was there he put his hand against\n","\n","the mans cold chest the heart too was still alive\n","\n","he will die unless he is operated on sadao said the question is whether he will not die anyway\n","\n","hana cried out in fear dont try to save him! what if he should live?\n","\n","what if he should die? sadao replied he looked at the motionless man this man must be very healthy or he would\n","\n","have been dead by now he looked so very young\n","\n","you mean die from the operation? hana asked\n","\n","yes sadao said\n","\n","hana thought about this and when she did not answer sadao turned away\n","\n","in any case something must be done with him he said and first he must be washed\n","\n","he went quickly out of the room and hana came behind him she did not wish to be left alone with the\n","\n","white man he was the first she had seen since she left america he seemed to have nothing to do with\n","\n","those whom she had known there here he was her enemy a threati5 living or dead\n","\n","she turned to the nursery and called yumi!\n","\n","the children heard her voice she had to go in for a moment and smile at them and play with the baby\n","\n","now nearly three months old\n","\n","to yumi she said come with me!\n","\n","i will put the baby to bed yumi said he is ready\n","\n","she went with yumi into the bedroom next to the nursery she stood with the boy in her arms while\n","\n","yumi spread the sleeping quilts on the floor and laid the baby between them\n","\n","then hana led the way quickly to the kitchen the two servants were frightened at what their master\n","\n","had just told them\n","\n","the master ought not to heal the wounds of this white man\n","\n","the old gardener said to hana the white man ought to die first he was shot then the sea caught\n","\n","him and wounded him with her rocks if the master heals what the gun did and what the\n","\n","sea did they will take revenge on us\n","\n","i will tell him what you say hana answered politely but she herself was also frightened although she\n","\n","was not superstitious as the old man was could it ever be right to help an enemy?\n","\n","nevertheless she told yumi to bring the hot water to  the room where the white man was\n","\n","she went ahead and slid back the partitions sadao was not there yet yumi following put down her\n","\n","wooden bucket then she went over to the white man\n","\n","i have never washed a white man she said and i will not wash one so dirty now\n","\n","hana cried you will do what your master commands you!\n","\n","my master ought not to command me to wash the enemy yumi said stubbornly\n","\n","the look upon yumis round dull face made hana feel afraid\n","\n","what if she should report something that was not as it happened?\n","\n","very well she said with dignity you understand we only want to bring him to his senses so that we\n","\n","can turn him over as a prisoner?\n","\n","i will have nothing to do with it yumi said i am a poor person and it is not my business\n","\n","then please hana said gently return to your own work\n","\n","yumi left the room but this left hana alone with the white man she might have been too afraid to stay\n","\n","but her anger at yumi gave her courage\n","\n","stupid yumi! she said is this anything but a man? a wounded helpless man!\n","\n","she untied the rags that covered the white man she dipped a small clean towel into the steaming hot\n","\n","water and washed his face carefully she kept on washing him until his upper body was quite clean but\n","\n","she dared not turn him over\n","\n","where was sadao? now her anger was disappearing and she was anxiousg again she got up and\n","\n","wiped her hands she then put the quilt over him so he wouldnt be cold\n","\n","sadao! she called softly\n","\n","he had been about to come in when she called she saw that he had brought his surgeons emergency\n","['', 'dr sadao hokis house was built on a spot off the japanese coast as a little boy he had often played there his low', '', 'square stone house was built above the narrowbeach his father had taken him often to the islands not far from the', '', 'shore he would say to the serious little boy at his side', '', 'those islands out there are the steppingstones to the future of japan', '', 'where shall we step from them? sadao had asked', '', 'who knows? his father had answered who can limit our future? it depends on what we make it', '', 'sadao had paid attention to this as he did everything his father said his father never joked or played with him however', '', 'he gave all his attention to his only son sadao knew that his education was the most important thing in the world to his', '', 'father for this reason he had been sent at twentytwo to america to learn all that could be learned of surgery and', '', 'medicine he had come back at thirty before his father died he had seen sadao become famous not only as a surgeon', '', 'but as a scientist sadao was now working on an important medical discovery so he had not been sent abroad with the', '', 'troops he also knew there was a chance the old general might need an operation this was another reason why sadao', '', 'was being kept in japan', '', 'the weather had been surprisingly warm for the past few days there was heavy fog at night', '', 'the door opened and hana looked out she was wearing a darkblue kimono she came to him affectionately she put', '', 'her arm through his smiled and said nothing he had met hana in america but he had waited to fall in love with her until', '', 'he was sure she believed in traditional japanese values otherwise his father would never have received her he thought', '', 'about how lucky he was that he had found her by chance really at an american professors house', '', 'the professor and his wife had been kind people they wanted to do something for their few foreign students the', '', 'students though bored sadao had often told hana that he had almost not gone to professor harleys house that night', '', 'but he had gone and there he had found hana a new student they had not married carelessly in america they had', '', 'finished their studies and had come home to japan after his father had seen her the marriage was arranged in the old', '', 'japanese way although sadao and hana had talked everything over before the were perfectly happy', '', 'she laid her cheek against his arm it was at this moment that both of them saw something black come out of the mists', '', 'it was a man he was thr0un out of the ocean by a wave he staggered a few steps his arms above his head then the', '', 'mists hid him again', '', 'who is that? hana cried she dropped sadaos arm and they both leaned over the railing of the now they saw him', '', 'again the man was on his hands and knees crawling then they saw him fall on his face and lie there', '', 'a fisherman perhaps sadao said washed from his boat he ran quickly down the steps behind him hana came', '', 'her wide sleeves flying a mile or two away on either side there were fishing villages', '', 'somehow the man had managed to go through the rocks he must be badly hurt they saw that the sand on one side of', '', 'him was red', '', 'he is wounded sadao exclaimed he hurried to the man ho lay there without moving his face in the sand an old', '', 'cap stuck to his head his clothes were wet rags', '', 'sadao stoopedh hana at his side and turned the mans head hey saw the face', '', 'a white man! hana whispered', '', 'yes it was a white man his wet yellow hair long as though had not been cut for many weeks  on his young and', '', 'tortured he had a  rough yellow beard he was unconscious sadao remembered the wound and with his expert fingers', '', 'began to search for it blood flowed freshly at his touch on the right side of his lower back sadao saw that a gun wound', '', 'had been reopened the flesh was black sometime not many days ago the man had been shot and had not been', '', 'saved it his bad luck now that a rock had struck his wound', '', 'oh how he is bleeding! hana whispered again the mists lid them completely now at this time of day no one came', '', 'by the fishermen had gone home', '', 'what shall are do with this man? sadao said', '', 'but his hands seemed to have a will of their own they worked to stop the bleeding the man moaned with pain but he', '', 'did not awaken', '', 'the best thing that we could do would be to put him back in the sea sadao said answering himself', '', 'now that the bleeding was stopped for the moment he stood up and dusted the sand from his hands', '', 'yes that would be best hana said but she continued to look at the man', '', 'lf we sheltered a white man in our house we would be arrested but if we turned him in as a prisoner he would certainly', '', 'die sadao said', '', 'the kindest thing would be to put him back into the sea hana said but neither of them moved', '', 'what is he? hana whispered there is something about him that looks american sadao said he picked up the cap', '', 'a sailor he said from an american warship he spelled it out us navy the man was a prisoner of war! he has', '', 'escapedhana cried softly and that is why he was shot in the back sadao agreed they hesitated looking at each', '', 'other then hana said are we able to put him back into the sea? if i am able are you? sadao asked so hana', '', 'said but if you can do it alone  sadao hesitated again', '', 'the strange thing is he said that if the man were whole6 i could turn him over to the police without difficulty i care', '', 'nothing for him he is my enemy all americans are my enemy and he is only a common fellow you see how foolish his', '', 'face is but since he is wounded ', '', 'you also cannot throw him back to the sea hana said then there is only one thing to do we must carry him into the', '', 'house', '', 'but the servants? sadao asked', '', 'we must simply tell them that we plan to give him to the police and we must sadao we must think of the children and', '', 'of our position1 it woiild endanger all of us if we did not give this man over as a prisoner of war', '', 'certainly sadao agreed i would not think of doing anything else', '', 'together they lifted the man he was very light they carried him up the steps and into an empty bedroom it bad been', '', 'the bedroom of sadaos father since his death it had not been used they laid the man on the floor mat everything', '', 'here had been japaneseto please the old man sadaos father would never in his own home sit on a chair or sleep in a', '', 'foreign bed hana went to the wall cupboards and slid back a door and took out a soft quilt she hesitateds the quilt', '', 'was covered with flowered silk', '', 'he is so dirty she whispered', '', 'yes he had better be washed sadao agreed if you will bring hot water i will wash him', '', 'i cannot bear for you to touch him she said we shall have to tell the servants he is here 1 will tell yumi now she can', '', 'leave the children for a few minutes and she can wash him', '', 'sadao thought a moment yes he agreed you tell yumi and i will tell the others', '', 'the whitenesss of the mans face moved sadao to feel his pulse it was faint but it was there he put his hand against', '', 'the mans cold chest the heart too was still alive', '', 'he will die unless he is operated on sadao said the question is whether he will not die anyway', '', 'hana cried out in fear dont try to save him! what if he should live?', '', 'what if he should die? sadao replied he looked at the motionless man this man must be very healthy or he would', '', 'have been dead by now he looked so very young', '', 'you mean die from the operation? hana asked', '', 'yes sadao said', '', 'hana thought about this and when she did not answer sadao turned away', '', 'in any case something must be done with him he said and first he must be washed', '', 'he went quickly out of the room and hana came behind him she did not wish to be left alone with the', '', 'white man he was the first she had seen since she left america he seemed to have nothing to do with', '', 'those whom she had known there here he was her enemy a threati5 living or dead', '', 'she turned to the nursery and called yumi!', '', 'the children heard her voice she had to go in for a moment and smile at them and play with the baby', '', 'now nearly three months old', '', 'to yumi she said come with me!', '', 'i will put the baby to bed yumi said he is ready', '', 'she went with yumi into the bedroom next to the nursery she stood with the boy in her arms while', '', 'yumi spread the sleeping quilts on the floor and laid the baby between them', '', 'then hana led the way quickly to the kitchen the two servants were frightened at what their master', '', 'had just told them', '', 'the master ought not to heal the wounds of this white man', '', 'the old gardener said to hana the white man ought to die first he was shot then the sea caught', '', 'him and wounded him with her rocks if the master heals what the gun did and what the', '', 'sea did they will take revenge on us', '', 'i will tell him what you say hana answered politely but she herself was also frightened although she', '', 'was not superstitious as the old man was could it ever be right to help an enemy?', '', 'nevertheless she told yumi to bring the hot water to  the room where the white man was', '', 'she went ahead and slid back the partitions sadao was not there yet yumi following put down her', '', 'wooden bucket then she went over to the white man', '', 'i have never washed a white man she said and i will not wash one so dirty now', '', 'hana cried you will do what your master commands you!', '', 'my master ought not to command me to wash the enemy yumi said stubbornly', '', 'the look upon yumis round dull face made hana feel afraid', '', 'what if she should report something that was not as it happened?', '', 'very well she said with dignity you understand we only want to bring him to his senses so that we', '', 'can turn him over as a prisoner?', '', 'i will have nothing to do with it yumi said i am a poor person and it is not my business', '', 'then please hana said gently return to your own work', '', 'yumi left the room but this left hana alone with the white man she might have been too afraid to stay', '', 'but her anger at yumi gave her courage', '', 'stupid yumi! she said is this anything but a man? a wounded helpless man!', '', 'she untied the rags that covered the white man she dipped a small clean towel into the steaming hot', '', 'water and washed his face carefully she kept on washing him until his upper body was quite clean but', '', 'she dared not turn him over', '', 'where was sadao? now her anger was disappearing and she was anxiousg again she got up and', '', 'wiped her hands she then put the quilt over him so he wouldnt be cold', '', 'sadao! she called softly', '', 'he had been about to come in when she called she saw that he had brought his surgeons emergency']\n"]}]},{"cell_type":"code","source":["from tensorflow.keras.preprocessing.text import Tokenizer\n","from tensorflow.keras.preprocessing.sequence import pad_sequences\n","\n","# Instantiating the Tokenizer\n","max_vocab = 1000000\n","tokenizer = Tokenizer(num_words=max_vocab)\n","tokenizer.fit_on_texts(final_data)\n","\n","# Getting the total number of words of the data.\n","word2idx = tokenizer.word_index\n","print(len(word2idx))\n","print(word2idx)\n","vocab_size = len(word2idx) + 1        # Adding 1 to the vocab_size because the index starts from 1 not 0. This will make it uniform when using it further\n","print(vocab_size)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Py510WGU3-P2","executionInfo":{"status":"ok","timestamp":1691874528724,"user_tz":-330,"elapsed":51,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"232dbf84-231c-43ee-db4f-fdfc59ce3371"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["580\n","{'the': 1, 'he': 2, 'to': 3, 'his': 4, 'she': 5, 'was': 6, 'had': 7, 'and': 8, 'a': 9, 'sadao': 10, 'him': 11, 'man': 12, 'hana': 13, 'said': 14, 'not': 15, 'of': 16, 'that': 17, 'in': 18, 'is': 19, 'it': 20, 'with': 21, 'but': 22, 'we': 23, 'her': 24, 'on': 25, 'at': 26, 'been': 27, 'yumi': 28, 'there': 29, 'be': 30, 'they': 31, 'will': 32, 'i': 33, 'this': 34, 'you': 35, 'what': 36, 'white': 37, 'as': 38, 'father': 39, 'would': 40, 'for': 41, 'now': 42, 'if': 43, 'back': 44, 'then': 45, 'out': 46, 'them': 47, 'put': 48, 'have': 49, 'do': 50, 'over': 51, 'must': 52, 'did': 53, 'an': 54, 'so': 55, 'old': 56, 'saw': 57, 'face': 58, 'house': 59, 'from': 60, 'sea': 61, 'die': 62, 'into': 63, 'tell': 64, 'side': 65, 'are': 66, 'can': 67, 'or': 68, 'only': 69, 'thing': 70, 'come': 71, 'something': 72, 'were': 73, 'again': 74, 'washed': 75, 'yes': 76, 'enemy': 77, 'went': 78, 'master': 79, 'asked': 80, 'never': 81, 'all': 82, 'america': 83, 'could': 84, 'few': 85, 'came': 86, 'nothing': 87, 'about': 88, 'by': 89, 'their': 90, 'moment': 91, 'cried': 92, 'hands': 93, 'one': 94, 'wounded': 95, 'turned': 96, 'whispered': 97, 'up': 98, 'prisoner': 99, 'agreed': 100, 'my': 101, 'very': 102, 'wash': 103, 'left': 104, 'japanese': 105, 'boy': 106, 'often': 107, 'japan': 108, 'where': 109, 'shall': 110, 'who': 111, 'our': 112, 'everything': 113, 'seen': 114, 'also': 115, 'looked': 116, 'arm': 117, 'thought': 118, 'how': 119, 'american': 120, 'told': 121, 'gone': 122, 'home': 123, 'laid': 124, 'mists': 125, 'steps': 126, 'head': 127, 'sadaos': 128, 'quickly': 129, 'sand': 130, 'mans': 131, 'wound': 132, 'shot': 133, 'bleeding': 134, 'own': 135, 'us': 136, 'alone': 137, 'turn': 138, 'since': 139, 'servants': 140, 'children': 141, 'bedroom': 142, 'here': 143, 'quilt': 144, 'bring': 145, 'hot': 146, 'water': 147, 'should': 148, 'first': 149, 'room': 150, 'called': 151, 'baby': 152, 'ought': 153, 'built': 154, 'little': 155, 'played': 156, 'above': 157, 'islands': 158, 'say': 159, 'those': 160, 'future': 161, 'answered': 162, 'attention': 163, 'gave': 164, 'knew': 165, 'important': 166, 'reason': 167, 'sent': 168, 'before': 169, 'chance': 170, 'might': 171, 'operation': 172, 'why': 173, 'kept': 174, 'days': 175, 'night': 176, 'door': 177, 'through': 178, 'fall': 179, 'until': 180, 'found': 181, 'professor': 182, 'foreign': 183, 'students': 184, 'though': 185, 'way': 186, 'although': 187, 'against': 188, 'both': 189, 'black': 190, 'arms': 191, 'down': 192, 'behind': 193, 'two': 194, 'away': 195, 'go': 196, 'rocks': 197, 'without': 198, 'cap': 199, 'wet': 200, 'rags': 201, 'yellow': 202, 'many': 203, 'young': 204, 'touch': 205, 'right': 206, 'gun': 207, 'bad': 208, 'seemed': 209, 'best': 210, 'stood': 211, 'look': 212, 'certainly': 213, 'moved': 214, 'war': 215, 'softly': 216, 'hesitated': 217, 'able': 218, 'am': 219, 'police': 220, 'cannot': 221, 'give': 222, 'think': 223, 'anything': 224, 'floor': 225, 'please': 226, 'bed': 227, 'slid': 228, 'covered': 229, 'dirty': 230, 'feel': 231, 'cold': 232, 'too': 233, 'dead': 234, 'when': 235, 'nursery': 236, 'me': 237, 'frightened': 238, 'your': 239, 'afraid': 240, 'anger': 241, 'clean': 242, 'dr': 243, 'hokis': 244, 'spot': 245, 'off': 246, 'coast': 247, 'low': 248, 'square': 249, 'stone': 250, 'narrowbeach': 251, 'taken': 252, 'far': 253, 'shore': 254, 'serious': 255, 'steppingstones': 256, 'step': 257, 'knows': 258, 'limit': 259, 'depends': 260, 'make': 261, 'paid': 262, 'joked': 263, 'however': 264, 'son': 265, 'education': 266, 'most': 267, 'world': 268, 'twentytwo': 269, 'learn': 270, 'learned': 271, 'surgery': 272, 'medicine': 273, 'thirty': 274, 'died': 275, 'become': 276, 'famous': 277, 'surgeon': 278, 'scientist': 279, 'working': 280, 'medical': 281, 'discovery': 282, 'abroad': 283, 'troops': 284, 'general': 285, 'need': 286, 'another': 287, 'being': 288, 'weather': 289, 'surprisingly': 290, 'warm': 291, 'past': 292, 'heavy': 293, 'fog': 294, 'opened': 295, 'wearing': 296, 'darkblue': 297, 'kimono': 298, 'affectionately': 299, 'smiled': 300, 'met': 301, 'waited': 302, 'love': 303, 'sure': 304, 'believed': 305, 'traditional': 306, 'values': 307, 'otherwise': 308, 'received': 309, 'lucky': 310, 'really': 311, 'professors': 312, 'wife': 313, 'kind': 314, 'people': 315, 'wanted': 316, 'bored': 317, 'almost': 318, 'harleys': 319, 'new': 320, 'student': 321, 'married': 322, 'carelessly': 323, 'finished': 324, 'studies': 325, 'after': 326, 'marriage': 327, 'arranged': 328, 'talked': 329, 'perfectly': 330, 'happy': 331, 'cheek': 332, 'thr0un': 333, 'ocean': 334, 'wave': 335, 'staggered': 336, 'hid': 337, 'dropped': 338, 'leaned': 339, 'railing': 340, 'knees': 341, 'crawling': 342, 'lie': 343, 'fisherman': 344, 'perhaps': 345, 'boat': 346, 'ran': 347, 'wide': 348, 'sleeves': 349, 'flying': 350, 'mile': 351, 'either': 352, 'fishing': 353, 'villages': 354, 'somehow': 355, 'managed': 356, 'badly': 357, 'hurt': 358, 'red': 359, 'exclaimed': 360, 'hurried': 361, 'ho': 362, 'lay': 363, 'moving': 364, 'stuck': 365, 'clothes': 366, 'stoopedh': 367, 'hey': 368, 'hair': 369, 'long': 370, 'cut': 371, 'weeks': 372, 'tortured': 373, 'rough': 374, 'beard': 375, 'unconscious': 376, 'remembered': 377, 'expert': 378, 'fingers': 379, 'began': 380, 'search': 381, 'blood': 382, 'flowed': 383, 'freshly': 384, 'lower': 385, 'reopened': 386, 'flesh': 387, 'sometime': 388, 'ago': 389, 'saved': 390, 'luck': 391, 'rock': 392, 'struck': 393, 'oh': 394, 'lid': 395, 'completely': 396, 'time': 397, 'day': 398, 'no': 399, 'fishermen': 400, 'worked': 401, 'stop': 402, 'moaned': 403, 'pain': 404, 'awaken': 405, 'answering': 406, 'himself': 407, 'stopped': 408, 'dusted': 409, 'continued': 410, 'lf': 411, 'sheltered': 412, 'arrested': 413, 'kindest': 414, 'neither': 415, 'looks': 416, 'picked': 417, 'sailor': 418, 'warship': 419, 'spelled': 420, 'navy': 421, 'has': 422, 'escapedhana': 423, 'looking': 424, 'each': 425, 'other': 426, 'strange': 427, 'whole6': 428, 'difficulty': 429, 'care': 430, 'americans': 431, 'common': 432, 'fellow': 433, 'see': 434, 'foolish': 435, 'throw': 436, 'carry': 437, 'simply': 438, 'plan': 439, 'position1': 440, 'woiild': 441, 'endanger': 442, 'doing': 443, 'else': 444, 'together': 445, 'lifted': 446, 'light': 447, 'carried': 448, 'empty': 449, 'death': 450, 'used': 451, 'mat': 452, 'japaneseto': 453, 'sit': 454, 'chair': 455, 'sleep': 456, 'wall': 457, 'cupboards': 458, 'took': 459, 'soft': 460, 'hesitateds': 461, 'flowered': 462, 'silk': 463, 'better': 464, 'bear': 465, '1': 466, 'leave': 467, 'minutes': 468, 'others': 469, 'whitenesss': 470, 'pulse': 471, 'faint': 472, 'hand': 473, 'chest': 474, 'heart': 475, 'still': 476, 'alive': 477, 'unless': 478, 'operated': 479, 'question': 480, 'whether': 481, 'anyway': 482, 'fear': 483, 'dont': 484, 'try': 485, 'save': 486, 'live': 487, 'replied': 488, 'motionless': 489, 'healthy': 490, 'mean': 491, 'answer': 492, 'any': 493, 'case': 494, 'done': 495, 'wish': 496, 'whom': 497, 'known': 498, 'threati5': 499, 'living': 500, 'heard': 501, 'voice': 502, 'smile': 503, 'play': 504, 'nearly': 505, 'three': 506, 'months': 507, 'ready': 508, 'next': 509, 'while': 510, 'spread': 511, 'sleeping': 512, 'quilts': 513, 'between': 514, 'led': 515, 'kitchen': 516, 'just': 517, 'heal': 518, 'wounds': 519, 'gardener': 520, 'caught': 521, 'heals': 522, 'take': 523, 'revenge': 524, 'politely': 525, 'herself': 526, 'superstitious': 527, 'ever': 528, 'help': 529, 'nevertheless': 530, 'ahead': 531, 'partitions': 532, 'yet': 533, 'following': 534, 'wooden': 535, 'bucket': 536, 'commands': 537, 'command': 538, 'stubbornly': 539, 'upon': 540, 'yumis': 541, 'round': 542, 'dull': 543, 'made': 544, 'report': 545, 'happened': 546, 'well': 547, 'dignity': 548, 'understand': 549, 'want': 550, 'senses': 551, 'poor': 552, 'person': 553, 'business': 554, 'gently': 555, 'return': 556, 'work': 557, 'stay': 558, 'courage': 559, 'stupid': 560, 'helpless': 561, 'untied': 562, 'dipped': 563, 'small': 564, 'towel': 565, 'steaming': 566, 'carefully': 567, 'washing': 568, 'upper': 569, 'body': 570, 'quite': 571, 'dared': 572, 'disappearing': 573, 'anxiousg': 574, 'got': 575, 'wiped': 576, 'wouldnt': 577, 'brought': 578, 'surgeons': 579, 'emergency': 580}\n","581\n"]}]},{"cell_type":"code","source":["# We will turn the sentences to sequences line by line and create n_gram sequences\n","\n","input_seq = []\n","\n","for line in final_data:\n","  token_list = tokenizer.texts_to_sequences([line])[0]\n","  for i in range(1, len(token_list)):\n","    n_gram_seq = token_list[:i+1]\n","    input_seq.append(n_gram_seq)\n","\n","print(input_seq)\n","\n","# Getting the maximum length of sequence for padding purpose\n","max_seq_length = max(len(x) for x in input_seq)\n","print(max_seq_length)\n","\n","# Padding the sequences and converting them to array\n","input_seq = np.array(pad_sequences(input_seq, maxlen=max_seq_length, padding='pre'))\n","print(input_seq)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jxmhFa574J2i","executionInfo":{"status":"ok","timestamp":1691874528725,"user_tz":-330,"elapsed":38,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"cfa47f15-36a4-491b-95ea-04c31f7d837b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["[[243, 10], [243, 10, 244], [243, 10, 244, 59], [243, 10, 244, 59, 6], [243, 10, 244, 59, 6, 154], [243, 10, 244, 59, 6, 154, 25], [243, 10, 244, 59, 6, 154, 25, 9], [243, 10, 244, 59, 6, 154, 25, 9, 245], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106, 2], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106, 2, 7], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106, 2, 7, 107], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106, 2, 7, 107, 156], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106, 2, 7, 107, 156, 29], [243, 10, 244, 59, 6, 154, 25, 9, 245, 246, 1, 105, 247, 38, 9, 155, 106, 2, 7, 107, 156, 29, 4], [243, 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[28, 104, 1, 150, 22, 34, 104, 13, 137], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171, 49], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171, 49, 27], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171, 49, 27, 233], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171, 49, 27, 233, 240], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171, 49, 27, 233, 240, 3], [28, 104, 1, 150, 22, 34, 104, 13, 137, 21, 1, 37, 12, 5, 171, 49, 27, 233, 240, 3, 558], [22, 24], [22, 24, 241], [22, 24, 241, 26], [22, 24, 241, 26, 28], [22, 24, 241, 26, 28, 164], [22, 24, 241, 26, 28, 164, 24], [22, 24, 241, 26, 28, 164, 24, 559], [560, 28], [560, 28, 5], [560, 28, 5, 14], [560, 28, 5, 14, 19], [560, 28, 5, 14, 19, 34], [560, 28, 5, 14, 19, 34, 224], [560, 28, 5, 14, 19, 34, 224, 22], [560, 28, 5, 14, 19, 34, 224, 22, 9], [560, 28, 5, 14, 19, 34, 224, 22, 9, 12], [560, 28, 5, 14, 19, 34, 224, 22, 9, 12, 9], [560, 28, 5, 14, 19, 34, 224, 22, 9, 12, 9, 95], [560, 28, 5, 14, 19, 34, 224, 22, 9, 12, 9, 95, 561], [560, 28, 5, 14, 19, 34, 224, 22, 9, 12, 9, 95, 561, 12], [5, 562], [5, 562, 1], [5, 562, 1, 201], [5, 562, 1, 201, 17], [5, 562, 1, 201, 17, 229], [5, 562, 1, 201, 17, 229, 1], [5, 562, 1, 201, 17, 229, 1, 37], [5, 562, 1, 201, 17, 229, 1, 37, 12], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564, 242], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564, 242, 565], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564, 242, 565, 63], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564, 242, 565, 63, 1], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564, 242, 565, 63, 1, 566], [5, 562, 1, 201, 17, 229, 1, 37, 12, 5, 563, 9, 564, 242, 565, 63, 1, 566, 146], [147, 8], [147, 8, 75], [147, 8, 75, 4], [147, 8, 75, 4, 58], [147, 8, 75, 4, 58, 567], [147, 8, 75, 4, 58, 567, 5], [147, 8, 75, 4, 58, 567, 5, 174], [147, 8, 75, 4, 58, 567, 5, 174, 25], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4, 569], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4, 569, 570], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4, 569, 570, 6], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4, 569, 570, 6, 571], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4, 569, 570, 6, 571, 242], [147, 8, 75, 4, 58, 567, 5, 174, 25, 568, 11, 180, 4, 569, 570, 6, 571, 242, 22], [5, 572], [5, 572, 15], [5, 572, 15, 138], [5, 572, 15, 138, 11], [5, 572, 15, 138, 11, 51], [109, 6], [109, 6, 10], [109, 6, 10, 42], [109, 6, 10, 42, 24], [109, 6, 10, 42, 24, 241], [109, 6, 10, 42, 24, 241, 6], [109, 6, 10, 42, 24, 241, 6, 573], [109, 6, 10, 42, 24, 241, 6, 573, 8], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6, 574], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6, 574, 74], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6, 574, 74, 5], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6, 574, 74, 5, 575], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6, 574, 74, 5, 575, 98], [109, 6, 10, 42, 24, 241, 6, 573, 8, 5, 6, 574, 74, 5, 575, 98, 8], [576, 24], [576, 24, 93], [576, 24, 93, 5], [576, 24, 93, 5, 45], [576, 24, 93, 5, 45, 48], [576, 24, 93, 5, 45, 48, 1], [576, 24, 93, 5, 45, 48, 1, 144], [576, 24, 93, 5, 45, 48, 1, 144, 51], [576, 24, 93, 5, 45, 48, 1, 144, 51, 11], [576, 24, 93, 5, 45, 48, 1, 144, 51, 11, 55], [576, 24, 93, 5, 45, 48, 1, 144, 51, 11, 55, 2], [576, 24, 93, 5, 45, 48, 1, 144, 51, 11, 55, 2, 577], [576, 24, 93, 5, 45, 48, 1, 144, 51, 11, 55, 2, 577, 30], [576, 24, 93, 5, 45, 48, 1, 144, 51, 11, 55, 2, 577, 30, 232], [10, 5], [10, 5, 151], [10, 5, 151, 216], [2, 7], [2, 7, 27], [2, 7, 27, 88], [2, 7, 27, 88, 3], [2, 7, 27, 88, 3, 71], [2, 7, 27, 88, 3, 71, 18], [2, 7, 27, 88, 3, 71, 18, 235], [2, 7, 27, 88, 3, 71, 18, 235, 5], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17, 2], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17, 2, 7], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17, 2, 7, 578], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17, 2, 7, 578, 4], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17, 2, 7, 578, 4, 579], [2, 7, 27, 88, 3, 71, 18, 235, 5, 151, 5, 57, 17, 2, 7, 578, 4, 579, 580]]\n","27\n","[[  0   0   0 ...   0 243  10]\n"," [  0   0   0 ... 243  10 244]\n"," [  0   0   0 ...  10 244  59]\n"," ...\n"," [  0   0   0 ...   7 578   4]\n"," [  0   0   0 ... 578   4 579]\n"," [  0   0   0 ...   4 579 580]]\n"]}]},{"cell_type":"code","source":["# Taking xs and labels to train the model.\n","\n","xs = input_seq[:, :-1]        # xs contains every word in sentence except the last one because we are using this value to predict the y value\n","labels = input_seq[:, -1]     # labels contains only the last word of the sentence which will help in hot encoding the y value in next step\n","print(\"xs: \",xs)\n","print(\"labels:\",labels)\n","\n","from tensorflow.keras.utils import to_categorical\n","\n","# one-hot encoding the labels according to the vocab size\n","\n","# The matrix is square matrix of the size of vocab_size. Each row will denote a label and it will have\n","# a single +ve value(i.e 1) for that label and other values will be zero.\n","\n","ys = to_categorical(labels, num_classes=vocab_size)\n","print(ys)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BQPZb5nK4WGH","executionInfo":{"status":"ok","timestamp":1691874528725,"user_tz":-330,"elapsed":31,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"6a8b0353-8019-42bd-adcd-d537bb6d935b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["xs:  [[  0   0   0 ...   0   0 243]\n"," [  0   0   0 ...   0 243  10]\n"," [  0   0   0 ... 243  10 244]\n"," ...\n"," [  0   0   0 ...   2   7 578]\n"," [  0   0   0 ...   7 578   4]\n"," [  0   0   0 ... 578   4 579]]\n","labels: [ 10 244  59 ...   4 579 580]\n","[[0. 0. 0. ... 0. 0. 0.]\n"," [0. 0. 0. ... 0. 0. 0.]\n"," [0. 0. 0. ... 0. 0. 0.]\n"," ...\n"," [0. 0. 0. ... 0. 0. 0.]\n"," [0. 0. 0. ... 0. 1. 0.]\n"," [0. 0. 0. ... 0. 0. 1.]]\n"]}]},{"cell_type":"code","source":["from tensorflow.keras.layers import Input, Dense, Embedding, LSTM, Dropout, Bidirectional, GlobalMaxPooling1D\n","from tensorflow.keras.models import Model\n","from tensorflow.keras.optimizers import Adam\n","from tensorflow.keras.models import Sequential\n","\n","# using the keras to define the model\n","\n","i = Input(shape=(max_seq_length - 1, ))                           # using 1 less value becasuse we are preserving the last value for predicted word\n","x = Embedding(vocab_size, 124)(i)\n","x = Dropout(0.2)(x)\n","x = LSTM(520, return_sequences=True)(x)\n","x = Bidirectional(layer=LSTM(340, return_sequences=True))(x)\n","x = GlobalMaxPooling1D()(x)\n","x = Dense(1024, activation='relu')(x)\n","x = Dense(vocab_size, activation='softmax')(x)\n","\n","model = Model(i,x)\n"],"metadata":{"id":"Tzg6GReo4dji"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["from keras.utils.vis_utils import plot_model\n","keras.utils.plot_model(model, to_file='plot.png', show_layer_names=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":758},"id":"BppZJbz_aIgx","executionInfo":{"status":"ok","timestamp":1691874532646,"user_tz":-330,"elapsed":31,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"99b4266b-6f07-4822-c763-da5db4ef1bf1"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"image/png":"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\n","text/plain":["<IPython.core.display.Image object>"]},"metadata":{},"execution_count":12}]},{"cell_type":"code","source":["checkpoint = ModelCheckpoint(\"next_words.h5\", monitor='loss', verbose=1, save_best_only=True)\n","model.compile(optimizer=Adam(learning_rate=0.001),\n","              loss = 'categorical_crossentropy',\n","              metrics=['accuracy'])\n","\n","\n","# We can know about the shape of the model\n","r = model.fit(xs,ys,epochs=50,callbacks=[checkpoint])\n","\n","\n","# Evaluating the model on accuracy\n","import matplotlib.pyplot as plt\n","plt.plot(r.history['accuracy'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"PgP2As-L45__","executionInfo":{"status":"ok","timestamp":1691874616029,"user_tz":-330,"elapsed":83412,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"2afb0a87-3136-4895-8bef-59f0088694f1"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/50\n","60/60 [==============================] - ETA: 0s - loss: 5.8706 - accuracy: 0.0444\n","Epoch 1: loss improved from inf to 5.87057, saving model to next_words.h5\n","60/60 [==============================] - 21s 147ms/step - loss: 5.8706 - accuracy: 0.0444\n","Epoch 2/50\n","59/60 [============================>.] - ETA: 0s - loss: 5.5850 - accuracy: 0.0530\n","Epoch 2: loss improved from 5.87057 to 5.58917, saving model to next_words.h5\n","60/60 [==============================] - 4s 72ms/step - loss: 5.5892 - accuracy: 0.0522\n","Epoch 3/50\n","60/60 [==============================] - ETA: 0s - loss: 5.5369 - accuracy: 0.0543\n","Epoch 3: loss improved from 5.58917 to 5.53686, saving model to next_words.h5\n","60/60 [==============================] - 3s 47ms/step - loss: 5.5369 - accuracy: 0.0543\n","Epoch 4/50\n","60/60 [==============================] - ETA: 0s - loss: 5.5159 - accuracy: 0.0543\n","Epoch 4: loss improved from 5.53686 to 5.51590, saving model to next_words.h5\n","60/60 [==============================] - 2s 35ms/step - loss: 5.5159 - accuracy: 0.0543\n","Epoch 5/50\n","58/60 [============================>.] - ETA: 0s - loss: 5.5055 - accuracy: 0.0555\n","Epoch 5: loss improved from 5.51590 to 5.51342, saving model to next_words.h5\n","60/60 [==============================] - 2s 26ms/step - loss: 5.5134 - accuracy: 0.0543\n","Epoch 6/50\n","60/60 [==============================] - ETA: 0s - loss: 5.5047 - accuracy: 0.0543\n","Epoch 6: loss improved from 5.51342 to 5.50467, saving model to next_words.h5\n","60/60 [==============================] - 1s 19ms/step - loss: 5.5047 - accuracy: 0.0543\n","Epoch 7/50\n","58/60 [============================>.] - ETA: 0s - loss: 5.4967 - accuracy: 0.0544\n","Epoch 7: loss did not improve from 5.50467\n","60/60 [==============================] - 1s 17ms/step - loss: 5.5053 - accuracy: 0.0543\n","Epoch 8/50\n","59/60 [============================>.] - ETA: 0s - loss: 5.5016 - accuracy: 0.0546\n","Epoch 8: loss improved from 5.50467 to 5.49622, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 5.4962 - accuracy: 0.0543\n","Epoch 9/50\n","57/60 [===========================>..] - ETA: 0s - loss: 5.4942 - accuracy: 0.0532\n","Epoch 9: loss improved from 5.49622 to 5.49361, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 5.4936 - accuracy: 0.0533\n","Epoch 10/50\n","60/60 [==============================] - ETA: 0s - loss: 5.3958 - accuracy: 0.0543\n","Epoch 10: loss improved from 5.49361 to 5.39584, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 5.3958 - accuracy: 0.0543\n","Epoch 11/50\n","59/60 [============================>.] - ETA: 0s - loss: 5.2335 - accuracy: 0.0551\n","Epoch 11: loss improved from 5.39584 to 5.24615, saving model to next_words.h5\n","60/60 [==============================] - 2s 30ms/step - loss: 5.2462 - accuracy: 0.0543\n","Epoch 12/50\n","59/60 [============================>.] - ETA: 0s - loss: 5.0947 - accuracy: 0.0561\n","Epoch 12: loss improved from 5.24615 to 5.10556, saving model to next_words.h5\n","60/60 [==============================] - 1s 24ms/step - loss: 5.1056 - accuracy: 0.0559\n","Epoch 13/50\n","57/60 [===========================>..] - ETA: 0s - loss: 4.9752 - accuracy: 0.0554\n","Epoch 13: loss improved from 5.10556 to 4.97806, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 4.9781 - accuracy: 0.0548\n","Epoch 14/50\n","57/60 [===========================>..] - ETA: 0s - loss: 4.8630 - accuracy: 0.0587\n","Epoch 14: loss improved from 4.97806 to 4.87514, saving model to next_words.h5\n","60/60 [==============================] - 2s 26ms/step - loss: 4.8751 - accuracy: 0.0585\n","Epoch 15/50\n","59/60 [============================>.] - ETA: 0s - loss: 4.7481 - accuracy: 0.0636\n","Epoch 15: loss improved from 4.87514 to 4.75071, saving model to next_words.h5\n","60/60 [==============================] - 1s 23ms/step - loss: 4.7507 - accuracy: 0.0637\n","Epoch 16/50\n","57/60 [===========================>..] - ETA: 0s - loss: 4.6213 - accuracy: 0.0833\n","Epoch 16: loss improved from 4.75071 to 4.62519, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 4.6252 - accuracy: 0.0830\n","Epoch 17/50\n","60/60 [==============================] - ETA: 0s - loss: 4.4797 - accuracy: 0.0820\n","Epoch 17: loss improved from 4.62519 to 4.47973, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 4.4797 - accuracy: 0.0820\n","Epoch 18/50\n","57/60 [===========================>..] - ETA: 0s - loss: 4.3302 - accuracy: 0.0943\n","Epoch 18: loss improved from 4.47973 to 4.33316, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 4.3332 - accuracy: 0.0945\n","Epoch 19/50\n","59/60 [============================>.] - ETA: 0s - loss: 4.1976 - accuracy: 0.1186\n","Epoch 19: loss improved from 4.33316 to 4.19228, saving model to next_words.h5\n","60/60 [==============================] - 1s 19ms/step - loss: 4.1923 - accuracy: 0.1191\n","Epoch 20/50\n","57/60 [===========================>..] - ETA: 0s - loss: 4.0170 - accuracy: 0.1294\n","Epoch 20: loss improved from 4.19228 to 4.01753, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 4.0175 - accuracy: 0.1279\n","Epoch 21/50\n","60/60 [==============================] - ETA: 0s - loss: 3.8723 - accuracy: 0.1410\n","Epoch 21: loss improved from 4.01753 to 3.87230, saving model to next_words.h5\n","60/60 [==============================] - 1s 21ms/step - loss: 3.8723 - accuracy: 0.1410\n","Epoch 22/50\n","59/60 [============================>.] - ETA: 0s - loss: 3.7121 - accuracy: 0.1711\n","Epoch 22: loss improved from 3.87230 to 3.72115, saving model to next_words.h5\n","60/60 [==============================] - 1s 19ms/step - loss: 3.7211 - accuracy: 0.1697\n","Epoch 23/50\n","58/60 [============================>.] - ETA: 0s - loss: 3.6049 - accuracy: 0.1821\n","Epoch 23: loss improved from 3.72115 to 3.58524, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 3.5852 - accuracy: 0.1849\n","Epoch 24/50\n","57/60 [===========================>..] - ETA: 0s - loss: 3.3819 - accuracy: 0.2067\n","Epoch 24: loss improved from 3.58524 to 3.39798, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 3.3980 - accuracy: 0.2068\n","Epoch 25/50\n","57/60 [===========================>..] - ETA: 0s - loss: 3.2082 - accuracy: 0.2352\n","Epoch 25: loss improved from 3.39798 to 3.21421, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 3.2142 - accuracy: 0.2355\n","Epoch 26/50\n","60/60 [==============================] - ETA: 0s - loss: 3.0828 - accuracy: 0.2491\n","Epoch 26: loss improved from 3.21421 to 3.08278, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 3.0828 - accuracy: 0.2491\n","Epoch 27/50\n","57/60 [===========================>..] - ETA: 0s - loss: 2.8445 - accuracy: 0.2966\n","Epoch 27: loss improved from 3.08278 to 2.86663, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 2.8666 - accuracy: 0.2945\n","Epoch 28/50\n","60/60 [==============================] - ETA: 0s - loss: 2.6936 - accuracy: 0.3091\n","Epoch 28: loss improved from 2.86663 to 2.69362, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 2.6936 - accuracy: 0.3091\n","Epoch 29/50\n","57/60 [===========================>..] - ETA: 0s - loss: 2.4556 - accuracy: 0.3525\n","Epoch 29: loss improved from 2.69362 to 2.47379, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 2.4738 - accuracy: 0.3478\n","Epoch 30/50\n","57/60 [===========================>..] - ETA: 0s - loss: 2.2916 - accuracy: 0.3975\n","Epoch 30: loss improved from 2.47379 to 2.28655, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 2.2865 - accuracy: 0.3974\n","Epoch 31/50\n","57/60 [===========================>..] - ETA: 0s - loss: 2.0178 - accuracy: 0.4430\n","Epoch 31: loss improved from 2.28655 to 2.01465, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 2.0146 - accuracy: 0.4439\n","Epoch 32/50\n","57/60 [===========================>..] - ETA: 0s - loss: 1.7849 - accuracy: 0.5170\n","Epoch 32: loss improved from 2.01465 to 1.82126, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 1.8213 - accuracy: 0.5055\n","Epoch 33/50\n","57/60 [===========================>..] - ETA: 0s - loss: 1.6161 - accuracy: 0.5329\n","Epoch 33: loss improved from 1.82126 to 1.61739, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 1.6174 - accuracy: 0.5337\n","Epoch 34/50\n","60/60 [==============================] - ETA: 0s - loss: 1.4532 - accuracy: 0.5943\n","Epoch 34: loss improved from 1.61739 to 1.45316, saving model to next_words.h5\n","60/60 [==============================] - 1s 25ms/step - loss: 1.4532 - accuracy: 0.5943\n","Epoch 35/50\n","60/60 [==============================] - ETA: 0s - loss: 1.2007 - accuracy: 0.6642\n","Epoch 35: loss improved from 1.45316 to 1.20074, saving model to next_words.h5\n","60/60 [==============================] - 1s 19ms/step - loss: 1.2007 - accuracy: 0.6642\n","Epoch 36/50\n","58/60 [============================>.] - ETA: 0s - loss: 1.0079 - accuracy: 0.7112\n","Epoch 36: loss improved from 1.20074 to 1.01285, saving model to next_words.h5\n","60/60 [==============================] - 1s 25ms/step - loss: 1.0128 - accuracy: 0.7102\n","Epoch 37/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.8332 - accuracy: 0.7637\n","Epoch 37: loss improved from 1.01285 to 0.84335, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 0.8433 - accuracy: 0.7619\n","Epoch 38/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.7377 - accuracy: 0.7939\n","Epoch 38: loss improved from 0.84335 to 0.73480, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 0.7348 - accuracy: 0.7963\n","Epoch 39/50\n","60/60 [==============================] - ETA: 0s - loss: 0.6068 - accuracy: 0.8444\n","Epoch 39: loss improved from 0.73480 to 0.60678, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 0.6068 - accuracy: 0.8444\n","Epoch 40/50\n","60/60 [==============================] - ETA: 0s - loss: 0.5192 - accuracy: 0.8548\n","Epoch 40: loss improved from 0.60678 to 0.51922, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 0.5192 - accuracy: 0.8548\n","Epoch 41/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.4487 - accuracy: 0.8876\n","Epoch 41: loss improved from 0.51922 to 0.44766, saving model to next_words.h5\n","60/60 [==============================] - 1s 20ms/step - loss: 0.4477 - accuracy: 0.8883\n","Epoch 42/50\n","59/60 [============================>.] - ETA: 0s - loss: 0.3499 - accuracy: 0.9084\n","Epoch 42: loss improved from 0.44766 to 0.34943, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 0.3494 - accuracy: 0.9086\n","Epoch 43/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.3114 - accuracy: 0.9216\n","Epoch 43: loss improved from 0.34943 to 0.30867, saving model to next_words.h5\n","60/60 [==============================] - 1s 16ms/step - loss: 0.3087 - accuracy: 0.9232\n","Epoch 44/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.2630 - accuracy: 0.9413\n","Epoch 44: loss improved from 0.30867 to 0.26543, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 0.2654 - accuracy: 0.9410\n","Epoch 45/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.2235 - accuracy: 0.9424\n","Epoch 45: loss improved from 0.26543 to 0.22166, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 0.2217 - accuracy: 0.9436\n","Epoch 46/50\n","59/60 [============================>.] - ETA: 0s - loss: 0.2112 - accuracy: 0.9433\n","Epoch 46: loss improved from 0.22166 to 0.21185, saving model to next_words.h5\n","60/60 [==============================] - 1s 24ms/step - loss: 0.2119 - accuracy: 0.9431\n","Epoch 47/50\n","60/60 [==============================] - ETA: 0s - loss: 0.2149 - accuracy: 0.9394\n","Epoch 47: loss did not improve from 0.21185\n","60/60 [==============================] - 1s 16ms/step - loss: 0.2149 - accuracy: 0.9394\n","Epoch 48/50\n","58/60 [============================>.] - ETA: 0s - loss: 0.1780 - accuracy: 0.9553\n","Epoch 48: loss improved from 0.21185 to 0.17744, saving model to next_words.h5\n","60/60 [==============================] - 1s 19ms/step - loss: 0.1774 - accuracy: 0.9551\n","Epoch 49/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.1446 - accuracy: 0.9594\n","Epoch 49: loss improved from 0.17744 to 0.14900, saving model to next_words.h5\n","60/60 [==============================] - 1s 17ms/step - loss: 0.1490 - accuracy: 0.9582\n","Epoch 50/50\n","57/60 [===========================>..] - ETA: 0s - loss: 0.1870 - accuracy: 0.9507\n","Epoch 50: loss did not improve from 0.14900\n","60/60 [==============================] - 1s 14ms/step - loss: 0.1881 - accuracy: 0.9499\n"]},{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 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\n"},"metadata":{}}]},{"cell_type":"code","source":["def predict_words(seed, no_words):\n","  for i in range(no_words):\n","    token_list = tokenizer.texts_to_sequences([seed])[0]\n","    token_list = pad_sequences([token_list], maxlen=max_seq_length-1, padding='pre')\n","    predicted = np.argmax(model.predict(token_list), axis=1)\n","\n","    new_word = ''\n","\n","    for word, index in tokenizer.word_index.items():\n","      if predicted == index:\n","        new_word = word\n","        break\n","    seed += \" \" + new_word\n","  print(\"\\n\",seed)\n","\n","# Generating the next 10 words from seed text given by the user\n","\n","next_words = 10\n","\n","while(True):\n","  text = input(\"Enter your line: \")\n","  print(\"\\nPlease enter 0 to end Execution\\n\")\n","\n","  if text == \"0\":\n","      print(\"Execution completed.....\")\n","      break\n","\n","  else:\n","      try:\n","        predict_words(text, next_words)\n","      except Exception as e:\n","        print(\"Error occurred: \",e)\n","        continue"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7ceqauGj5evF","executionInfo":{"status":"ok","timestamp":1691874650394,"user_tz":-330,"elapsed":34403,"user":{"displayName":"Tarun Sheoran","userId":"02018464390268511348"}},"outputId":"c4c1768d-a1f3-4da2-ef2e-6b97ea29c686"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Enter your line: i will tell him what you say hana answered\n","\n","Please enter 0 to end Execution\n","\n","1/1 [==============================] - 1s 926ms/step\n","1/1 [==============================] - 0s 25ms/step\n","1/1 [==============================] - 0s 21ms/step\n","1/1 [==============================] - 0s 21ms/step\n","1/1 [==============================] - 0s 20ms/step\n","1/1 [==============================] - 0s 19ms/step\n","1/1 [==============================] - 0s 22ms/step\n","1/1 [==============================] - 0s 21ms/step\n","1/1 [==============================] - 0s 21ms/step\n","1/1 [==============================] - 0s 19ms/step\n","\n"," i will tell him what you say hana answered politely but she herself was also frightened although she said\n","Enter your line: 0\n","\n","Please enter 0 to end Execution\n","\n","Execution completed.....\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"MO9P8TXWCIn4"},"execution_count":null,"outputs":[]}]}