Update run.py

run.py

@@ -1,36 +1,36 @@
-from tokenizers import Tokenizer
-from tensorflow.keras.models import load_model
-from tensorflow.keras.preprocessing.sequence import pad_sequences
-import numpy as np
-# 1. Load từ file tokenizer.json
-src_tokenizer = Tokenizer.from_file("khmer_tokenizer.json")
-tgt_tokenizer = Tokenizer.from_file("vietnamese_tokenizer.json")
-model = load_model("translate_khmer_to_vi_fix_final.keras")
-max_len_src= 963
-max_len_tgt= 268
-model.summary()
-# def translate_sentence(sentence):
-
-#     sentence_ids = src_tokenizer.encode(sentence).ids
-#     sentence_decode_in = tgt_tokenizer.encode("<s>" + sentence).ids
-
-#     # return sentence_ids
-#     x_train = pad_sequences([sentence_ids], maxlen=max_len_src, padding='post')
-#     train_encoder = pad_sequences([sentence_decode_in],maxlen=max_len_tgt-1,padding='post')
-#     output = model.predict([x_train,train_encoder])
-#     # return output
-
-#     predicted_ids = np.argmax(output[0], axis=-1)
-#     # return predicted_ids
-#     # return tgt_tokenizer.decode(output[0]), tgt_tokenizer.decode(output[1])
-#     tokens = tgt_tokenizer.decode(predicted_ids)
-
-#     return tokens
-
-#     # return predicted_ids
-
-
-# khmer_sentence = "លោកនាយករដ្ឋមន្រ្តីទើបតែបានអត្ថាធិប្បាយលើព័ត៌មានមួយចំនួនដែលបានលើកឡើងនៅក្នុងកាសែតអេឡិចត្រូនិក VietNamNet ដែលទាក់ទងនឹង…"
-
-
-# print(translate_sentence(khmer_sentence))
+from tokenizers import Tokenizer
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing.sequence import pad_sequences
+import numpy as np
+# 1. Load từ file tokenizer.json
+src_tokenizer = Tokenizer.from_file("khmer_tokenizer.json")
+tgt_tokenizer = Tokenizer.from_file("vietnamese_tokenizer.json")
+model = load_model("translate_khmer_to_vi_fix_final.keras")
+max_len_src= 963
+max_len_tgt= 268
+# model.summary()
+def translate_sentence(sentence):
+
+    sentence_ids = src_tokenizer.encode(sentence).ids
+    sentence_decode_in = tgt_tokenizer.encode("<s>" + sentence).ids
+
+    # return sentence_ids
+    x_train = pad_sequences([sentence_ids], maxlen=max_len_src, padding='post')
+    train_encoder = pad_sequences([sentence_decode_in],maxlen=max_len_tgt-1,padding='post')
+    output = model.predict([x_train,train_encoder])
+    # return output
+
+    predicted_ids = np.argmax(output[0], axis=-1)
+    # return predicted_ids
+    # return tgt_tokenizer.decode(output[0]), tgt_tokenizer.decode(output[1])
+    tokens = tgt_tokenizer.decode(predicted_ids)
+
+    return tokens
+
+    # return predicted_ids
+
+
+khmer_sentence = "លោកនាយករដ្ឋមន្រ្តីទើបតែបានអត្ថាធិប្បាយលើព័ត៌មានមួយចំនួនដែលបានលើកឡើងនៅក្នុងកាសែតអេឡិចត្រូនិក VietNamNet ដែលទាក់ទងនឹង…"
+
+
+print(translate_sentence(khmer_sentence))