init the operator.

Signed-off-by: wxywb <xy.wang@zilliz.com>

README.md

@@ -1,2 +1,2 @@
-# opus-mt
+# opus_mt
 

__init__.py

@@ -0,0 +1,18 @@
+# Copyright 2021 Zilliz. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .opus_mt import OpusMT
+
+def opus_mt(model_name: str):
+    return OpusMT(model_name)

opus_mt.py

@@ -0,0 +1,54 @@
+# Copyright 2021 Zilliz. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import sys
+from pathlib import Path
+
+import torch
+from torchvision import transforms
+
+from towhee.types.image_utils import to_pil
+from towhee.operator.base import NNOperator, OperatorFlag
+from towhee.types.arg import arg, to_image_color
+from towhee import register
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+class OpusMT()
+    """
+    Opus-mt machine translation
+    """
+    def __init__(self, model_name: str):
+        super().__init__()
+        self.device = "cuda" if torch.cuda.is_available() else "cpu"
+        config = self.configs[model_name]  
+        self.tokenizer = AutoTokenizer.from_pretrained(config['tokenizer'])
+        self.model = AutoModelForSeq2SeqLM.from_pretrained(config['model'])
+        self.model.to(self.device)
+
+    def __call__(self, data): 
+        input_ids = tokenizer(data, return_tensors='pt', padding=True)['input_ids'].to(self.device)
+        outputs = model.generate(input_ids)
+        decoded = tokenizer.decode(outputs[0].detach().cpu(), skip_special_tokens=True)
+        return decoded
+~
+    def _configs(self):
+        config = {}
+        config['opus-mt-en-zh'] = {}
+        config['opus-mt-en-zh']['tokenizer'] = 'Helsinki-NLP/opus-mt-en-zh'
+        config['opus-mt-en-zh']['model'] = 'Helsinki-NLP/opus-mt-en-zh'
+
+        config['opus-mt-zh-en'] = {}
+        config['opus-mt-zh-en']['tokenizer'] = 'Helsinki-NLP/opus-mt-zh-en'
+        config['opus-mt-zh-en']['model'] = 'Helsinki-NLP/opus-mt-zh-en'