chore: import upstream snapshot with attribution
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# Copyright (c) Facebook, Inc. and its affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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from fairseq.modules import TransformerSentenceEncoderLayer
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from fairseq.modules.sparse_multihead_attention import SparseMultiheadAttention
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class SparseTransformerSentenceEncoderLayer(TransformerSentenceEncoderLayer):
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"""
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Implements a Sprase Transformer Encoder Layer (see SparseMultiheadAttention)
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"""
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def __init__(
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self,
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embedding_dim: int = 768,
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ffn_embedding_dim: int = 3072,
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num_attention_heads: int = 8,
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dropout: float = 0.1,
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attention_dropout: float = 0.1,
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activation_dropout: float = 0.1,
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activation_fn: str = "relu",
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export: bool = False,
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is_bidirectional: bool = True,
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stride: int = 32,
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expressivity: int = 8,
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) -> None:
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super().__init__(
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embedding_dim,
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ffn_embedding_dim,
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num_attention_heads,
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dropout,
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attention_dropout,
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activation_dropout,
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activation_fn,
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export,
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)
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self.self_attn = SparseMultiheadAttention(
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self.embedding_dim,
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num_attention_heads,
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dropout=attention_dropout,
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add_bias_kv=False,
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add_zero_attn=False,
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self_attention=True,
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is_bidirectional=is_bidirectional,
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stride=stride,
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expressivity=expressivity,
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)
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