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"""Base class for encoders and generic multi encoders.""" |
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import torch.nn as nn |
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class EncoderBase(nn.Module): |
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""" |
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Base encoder class. Specifies the interface used by different encoder types |
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and required by :class:`onmt.Models.NMTModel`. |
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""" |
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@classmethod |
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def from_opt(cls, opt, embeddings=None): |
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raise NotImplementedError |
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def forward(self, src, src_len=None): |
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""" |
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Args: |
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src (LongTensor): |
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padded sequences of sparse indices ``(batch, src_len, nfeat)`` |
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src_len (LongTensor): length of each sequence ``(batch,)`` |
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Returns: |
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(FloatTensor, FloatTensor, FloatTensor): |
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* enc_out (encoder output used for attention), |
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``(batch, src_len, hidden_size)`` |
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for bidirectional rnn last dimension is 2x hidden_size |
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* enc_final_hs: encoder final hidden state |
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``(num_layers x dir, batch, hidden_size)`` |
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In the case of LSTM this is a tuple. |
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* src_len ``(batch)`` |
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""" |
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raise NotImplementedError |
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