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2.32

Getting started

  • Quickstart
  • Installation

Configuration

  • Model
  • Parameters
  • Data
  • Vocabulary
  • Tokenization
  • Embeddings
  • Alignments

Usage

  • Training
  • Inference
  • Serving
  • 2.0 Transition Guide
  • Frequently Asked Questions

API

  • Python
    • opennmt
    • opennmt.data
    • opennmt.decoders
    • opennmt.encoders
    • opennmt.inputters
    • opennmt.layers
      • Bridge
      • ConcatReducer
      • CopyBridge
      • Dense
      • DenseBridge
      • DenseReducer
      • FeedForwardNetwork
      • JoinReducer
      • LSTM
      • LayerNorm
      • LayerWrapper
      • MultiHeadAttention
      • MultiHeadAttentionReduction
      • MultiplyReducer
      • PositionEmbedder
      • PositionEncoder
      • RNN
      • RNNCellWrapper
      • Reducer
      • SelfAttentionDecoderLayer
      • SelfAttentionEncoderLayer
      • SinusoidalPositionEncoder
      • SumReducer
      • TransformerLayerWrapper
      • ZeroBridge
      • combine_heads
      • dropout
      • future_mask
      • gelu
      • make_rnn_cell
      • split_heads
    • opennmt.models
    • opennmt.optimizers
    • opennmt.schedules
    • opennmt.tokenizers
    • opennmt.utils
OpenNMT-tf
  • »
  • Python »
  • opennmt.layers

opennmt.layers

Module defining reusable and model specific layers.

  • Bridge
  • ConcatReducer
  • CopyBridge
  • Dense
  • DenseBridge
  • DenseReducer
  • FeedForwardNetwork
  • JoinReducer
  • LSTM
  • LayerNorm
  • LayerWrapper
  • MultiHeadAttention
  • MultiHeadAttentionReduction
  • MultiplyReducer
  • PositionEmbedder
  • PositionEncoder
  • RNN
  • RNNCellWrapper
  • Reducer
  • SelfAttentionDecoderLayer
  • SelfAttentionEncoderLayer
  • SinusoidalPositionEncoder
  • SumReducer
  • TransformerLayerWrapper
  • ZeroBridge
  • combine_heads
  • dropout
  • future_mask
  • gelu
  • make_rnn_cell
  • split_heads
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