├── .gitignore ├── LICENSE ├── README.md ├── datas ├── ch.vec ├── en.vec └── translate.csv ├── seq2seq.py └── 手写AI.jpg /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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-------------------------------------------------------------------------------- https://raw.githubusercontent.com/shouxieai/seq2seq_translation/6d53debe1341e4c21ae1c72255f7ffc8caa1808c/README.md -------------------------------------------------------------------------------- /datas/ch.vec: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shouxieai/seq2seq_translation/6d53debe1341e4c21ae1c72255f7ffc8caa1808c/datas/ch.vec -------------------------------------------------------------------------------- /datas/en.vec: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shouxieai/seq2seq_translation/6d53debe1341e4c21ae1c72255f7ffc8caa1808c/datas/en.vec -------------------------------------------------------------------------------- /seq2seq.py: -------------------------------------------------------------------------------- 1 | import torch 2 | import torch.nn as nn 3 | import pandas as pd 4 | from torch.utils.data import Dataset,DataLoader 5 | import pickle 6 | 7 | def get_datas(file = "datas\\translate.csv",nums = None): 8 | all_datas = pd.read_csv(file) 9 | en_datas = list(all_datas["english"]) 10 | ch_datas = list(all_datas["chinese"]) 11 | 12 | if nums == None: 13 | return en_datas,ch_datas 14 | else: 15 | return en_datas[:nums],ch_datas[:nums] 16 | 17 | 18 | class MyDataset(Dataset): 19 | def __init__(self,en_data,ch_data,en_word_2_index,ch_word_2_index): 20 | self.en_data = en_data 21 | self.ch_data = ch_data 22 | self.en_word_2_index = en_word_2_index 23 | self.ch_word_2_index = ch_word_2_index 24 | 25 | def __getitem__(self,index): 26 | en = self.en_data[index] 27 | ch = self.ch_data[index] 28 | 29 | en_index = [self.en_word_2_index[i] for i in en] 30 | ch_index = [self.ch_word_2_index[i] for i in ch] 31 | 32 | return en_index,ch_index 33 | 34 | 35 | def batch_data_process(self,batch_datas): 36 | global device 37 | en_index , ch_index = [],[] 38 | en_len , ch_len = [],[] 39 | 40 | for en,ch in batch_datas: 41 | en_index.append(en) 42 | ch_index.append(ch) 43 | en_len.append(len(en)) 44 | ch_len.append(len(ch)) 45 | 46 | max_en_len = max(en_len) 47 | max_ch_len = max(ch_len) 48 | 49 | en_index = [ i + [self.en_word_2_index[""]] * (max_en_len - len(i)) for i in en_index] 50 | ch_index = [[self.ch_word_2_index[""]]+ i + [self.ch_word_2_index[""]] + [self.ch_word_2_index[""]] * (max_ch_len - len(i)) for i in ch_index] 51 | 52 | en_index = torch.tensor(en_index,device = device) 53 | ch_index = torch.tensor(ch_index,device = device) 54 | 55 | 56 | return en_index,ch_index 57 | 58 | 59 | def __len__(self): 60 | assert len(self.en_data) == len(self.ch_data) 61 | return len(self.ch_data) 62 | 63 | 64 | class Encoder(nn.Module): 65 | def __init__(self,encoder_embedding_num,encoder_hidden_num,en_corpus_len): 66 | super().__init__() 67 | self.embedding = nn.Embedding(en_corpus_len,encoder_embedding_num) 68 | self.lstm = nn.LSTM(encoder_embedding_num,encoder_hidden_num,batch_first=True) 69 | 70 | def forward(self,en_index): 71 | en_embedding = self.embedding(en_index) 72 | _,encoder_hidden =self.lstm(en_embedding) 73 | 74 | return encoder_hidden 75 | 76 | 77 | 78 | class Decoder(nn.Module): 79 | def __init__(self,decoder_embedding_num,decoder_hidden_num,ch_corpus_len): 80 | super().__init__() 81 | self.embedding = nn.Embedding(ch_corpus_len,decoder_embedding_num) 82 | self.lstm = nn.LSTM(decoder_embedding_num,decoder_hidden_num,batch_first=True) 83 | 84 | def forward(self,decoder_input,hidden): 85 | embedding = self.embedding(decoder_input) 86 | decoder_output,decoder_hidden = self.lstm(embedding,hidden) 87 | 88 | return decoder_output,decoder_hidden 89 | 90 | 91 | def translate(sentence): 92 | global en_word_2_index,model,device,ch_word_2_index,ch_index_2_word 93 | en_index = torch.tensor([[en_word_2_index[i] for i in sentence]],device=device) 94 | 95 | result = [] 96 | encoder_hidden = model.encoder(en_index) 97 | decoder_input = torch.tensor([[ch_word_2_index[""]]],device=device) 98 | 99 | decoder_hidden = encoder_hidden 100 | while True: 101 | decoder_output,decoder_hidden = model.decoder(decoder_input,decoder_hidden) 102 | pre = model.classifier(decoder_output) 103 | 104 | w_index = int(torch.argmax(pre,dim=-1)) 105 | word = ch_index_2_word[w_index] 106 | 107 | if word == "" or len(result) > 50: 108 | break 109 | 110 | result.append(word) 111 | decoder_input = torch.tensor([[w_index]],device=device) 112 | 113 | print("译文: ","".join(result)) 114 | 115 | 116 | 117 | 118 | 119 | class Seq2Seq(nn.Module): 120 | def __init__(self,encoder_embedding_num,encoder_hidden_num,en_corpus_len,decoder_embedding_num,decoder_hidden_num,ch_corpus_len): 121 | super().__init__() 122 | self.encoder = Encoder(encoder_embedding_num,encoder_hidden_num,en_corpus_len) 123 | self.decoder = Decoder(decoder_embedding_num,decoder_hidden_num,ch_corpus_len) 124 | self.classifier = nn.Linear(decoder_hidden_num,ch_corpus_len) 125 | 126 | self.cross_loss = nn.CrossEntropyLoss() 127 | 128 | def forward(self,en_index,ch_index): 129 | decoder_input = ch_index[:,:-1] 130 | label = ch_index[:,1:] 131 | 132 | encoder_hidden = self.encoder(en_index) 133 | decoder_output,_ = self.decoder(decoder_input,encoder_hidden) 134 | 135 | pre = self.classifier(decoder_output) 136 | loss = self.cross_loss(pre.reshape(-1,pre.shape[-1]),label.reshape(-1)) 137 | 138 | return loss 139 | 140 | 141 | 142 | if __name__ == "__main__": 143 | device = "cuda:0" if torch.cuda.is_available() else "cpu" 144 | 145 | with open("datas\\ch.vec","rb") as f1: 146 | _, ch_word_2_index,ch_index_2_word = pickle.load(f1) 147 | 148 | with open("datas\\en.vec","rb") as f2: 149 | _, en_word_2_index, en_index_2_word = pickle.load(f2) 150 | 151 | ch_corpus_len = len(ch_word_2_index) 152 | en_corpus_len = len(en_word_2_index) 153 | 154 | ch_word_2_index.update({"":ch_corpus_len,"":ch_corpus_len + 1 , "":ch_corpus_len+2}) 155 | en_word_2_index.update({"":en_corpus_len}) 156 | 157 | ch_index_2_word += ["","",""] 158 | en_index_2_word += [""] 159 | 160 | ch_corpus_len += 3 161 | en_corpus_len = len(en_word_2_index) 162 | 163 | 164 | en_datas,ch_datas = get_datas(nums=200) 165 | encoder_embedding_num = 50 166 | encoder_hidden_num = 100 167 | decoder_embedding_num = 107 168 | decoder_hidden_num = 100 169 | 170 | batch_size = 2 171 | epoch = 40 172 | lr = 0.001 173 | 174 | dataset = MyDataset(en_datas,ch_datas,en_word_2_index,ch_word_2_index) 175 | dataloader = DataLoader(dataset,batch_size,shuffle=False,collate_fn = dataset.batch_data_process) 176 | 177 | model = Seq2Seq(encoder_embedding_num,encoder_hidden_num,en_corpus_len,decoder_embedding_num,decoder_hidden_num,ch_corpus_len) 178 | model = model.to(device) 179 | 180 | opt = torch.optim.Adam(model.parameters(),lr = lr) 181 | 182 | for e in range(epoch): 183 | for en_index,ch_index in dataloader: 184 | loss = model(en_index,ch_index) 185 | loss.backward() 186 | opt.step() 187 | opt.zero_grad() 188 | 189 | print(f"loss:{loss:.3f}") 190 | 191 | 192 | while True: 193 | s = input("请输入英文: ") 194 | translate(s) 195 | -------------------------------------------------------------------------------- /手写AI.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/shouxieai/seq2seq_translation/6d53debe1341e4c21ae1c72255f7ffc8caa1808c/手写AI.jpg --------------------------------------------------------------------------------