40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
# coding=utf-8
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# Copyright 2018 The HuggingFace Inc. team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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""" Conditional generation class. """
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class Seq2SeqModel(object):
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def __init__(self):
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raise EnvironmentError(
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"""Seq2Seq is designed to be instantiated using the
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`Seq2Seq.from_pretrained(encoder_name_or_path, decoder_name_or_path)` method."""
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)
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@classmethod
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def from_pretrained(cls, encoder_name, decoder_name):
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# Here we should call AutoModel to initialize the models depending
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# on the pretrained models taken as an input.
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# For a first iteration we only work with Bert.
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raise NotImplementedError
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def __call__(self):
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# allows to call an instance of the class
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# model = Seq2Seq(encode='bert', decoder='bert')
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raise NotImplementedError
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def process(self):
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# alternative API to __call__ it is more explicit.
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raise NotImplementedError
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