NMT-Keras
  • Installation
    • Requirements
  • Usage
    • Training
    • Decoding
    • Scoring
  • Configuration options
    • Naming and experiment setup
    • Input/output
    • Evaluation
    • Decoding
    • Search normalization
    • Sampling
    • Unknown words treatment
    • Word representation
    • Text representation
    • Input text
    • Output text
    • Optimization
      • Optimizer setup
      • Advanced parameters for optimizers
    • Learning rate schedule
    • Training options
    • Early stop
    • Model main hyperparameters
      • Source word embeddings
      • Target word embedding
      • Deepness
    • AttentionRNNEncoderDecoder model
      • Encoder configuration
      • Decoder configuration
    • Transformer model
    • Regularizers
      • Regularization functions
      • Dropout
      • Gaussian noise
      • Batch normalization
      • Additional normalization layers
    • Tensorboard
    • Storage and plotting
  • Resources
    • Theoretical NMT
    • NMT-Keras Step-by-step
    • NMT-Keras Output
    • Tensorboard integration
      • Loss curve
      • Model graphs
      • Embedding visualization
  • Tutorials
  • Modules
    • nmt_keras package
      • Submodules
      • model_zoo
      • training
      • apply_model
      • build_callbacks
      • Module contents
    • data_engine package
      • Submodules
      • prepare_data module
      • Module contents
    • utils package
      • Submodules
      • evaluate_from_file module
      • preprocess_binary_word_vectors module
      • preprocess_text_word_vectors module
      • utils module
      • Module contents
  • Contact
    • Acknowledgement
      • Related projects
NMT-Keras
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Index

A | B | D | G | K | N | P | S | T | U | W

A

  • AttentionRNNEncoderDecoder() (nmt_keras.model_zoo.TranslationModel method)

B

  • build_dataset() (in module data_engine.prepare_data)
  • buildCallbacks() (in module nmt_keras.build_callbacks)

D

  • data_engine.prepare_data (module)

G

  • getPositionalEncodingWeights() (in module nmt_keras.model_zoo)
  • GroundHogModel() (nmt_keras.model_zoo.TranslationModel method)

K

  • keep_n_captions() (in module data_engine.prepare_data)

N

  • nmt_keras.apply_model (module)
  • nmt_keras.build_callbacks (module)
  • nmt_keras.model_zoo (module)
  • nmt_keras.training (module)

P

  • parse_args() (in module utils.preprocess_binary_word_vectors)
    • (in module utils.preprocess_text_word_vectors)
  • prepare_references() (in module data_engine.prepare_data)

S

  • sample_ensemble() (in module nmt_keras.apply_model)
  • score_corpus() (in module nmt_keras.apply_model)
  • setOptimizer() (nmt_keras.model_zoo.TranslationModel method)
  • setParams() (nmt_keras.model_zoo.TranslationModel method)

T

  • train_model() (in module nmt_keras.training)
  • Transformer() (nmt_keras.model_zoo.TranslationModel method)
  • TranslationModel (class in nmt_keras.model_zoo)
  • txtvec2npy() (in module utils.preprocess_text_word_vectors)

U

  • update_dataset_from_file() (in module data_engine.prepare_data)
  • update_parameters() (in module utils.utils)
  • utils (module)
  • utils.preprocess_binary_word_vectors (module)
  • utils.preprocess_text_word_vectors (module)
  • utils.utils (module)

W

  • word2vec2npy() (in module utils.preprocess_binary_word_vectors)

© Copyright 2017, Álvaro Peris Revision 865613dd.

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