init the operator.

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

README.md

@@ -1,2 +1,63 @@
-# data2vec-text
+# Text Embdding with data2vec
+
+*author: David Wang*
+
+
+<br />
+
+
+
+## Description
+
+This operator extracts features for text with [data2vec](https://arxiv.org/abs/2202.03555). The core idea is to predict latent representations of the full input data based on a masked view of the input in a self-distillation setup using a standard Transformer architecture.
+
+<br />
+
+
+## Code Example
+
+Use the pre-trained model to generate a text embedding for the sentence "Hello, world.".
+
+ *Write the pipeline in simplified style*:
+
+```python
+import towhee
+
+towhee.dc(["Hello, world."]) \
+      .text_embedding.data2vec_text() \
+      .show()
+
+```
+
+
+<br />
+
+
+
+## Factory Constructor
+
+Create the operator via the following factory method
+
+***data2vec_text()***
+
+<br />
+
+
+
+## Interface
+
+
+**Parameters:**
+
+​	***text:*** *str*
+
+​	The text in string.
+
+
+
+**Returns:** *numpy.ndarray*
+
+​   The text embedding extracted by model.
+
+
 

__init__.py

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+# 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 .data2vec_text import Data2VecText
+ 
+ 
+def data2vec_text(model_name='facebook/data2vec-vision-base'):
+    return Data2Text(model_name)

data2vec_text.py

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+# 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 numpy
+import torch
+from transformers import RobertaTokenizer, Data2VecTextModel
+from towhee.operator.base import NNOperator
+
+class Data2VecText(NNOperator):
+    def __init__(self):
+        self.model = Data2VecTextModel.from_pretrained("facebook/data2vec-text-base")
+        self.tokenizer = RobertaTokenizer.from_pretrained("facebook/data2vec-text-base")
+
+    def __call__(self, text: str) -> numpy.ndarray:
+        inputs = self.tokenizer(data, return_tensors="pt")
+        outputs = self.model(**inputs)
+        return outputs.pooler_output.detach().cpu().numpy()

requirements.txt

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+numpy
+transformers>4.19.0