Python Config Exemples

Exemple #1

import text_model

features = {'tokens', 'word_tokens', 'uncased_word_tokens'}

config = text_model.Config(
    lstm_size=512,
    embedding_size=128,
    use_word_level_embeddings=True,
    glove_vocab_size=text_model.FULL_GLOVE_VOCAB_SIZE,
    dense_dropout=.5,
    lstm_dropout=.5,
    dense_regularization_coef=1e-4,
    attention_num_heads=3,
    attention_head_size=128,
    feature_params={'vocab_size': 255},
)

Exemple #2

Fichier : large_model_w_pretrained_config.py Projet : dandersonw/ai-final-project

import text_model

features = {'tokens'}

config = text_model.Config(
    lstm_size=512,
    embedding_size=300,
    lstm_dropout=.5,
    use_pretrained_embeddings=True,
    attention_num_heads=3,
    attention_head_size=128,
    feature_params={'vocab_size': 255},
)

Exemple #3

Fichier : small_model_w_word_level_config.py Projet : dandersonw/ai-final-project

import text_model

features = {'tokens', 'word_tokens', 'uncased_word_tokens'}

config = text_model.Config(
    lstm_size=256,
    embedding_size=64,
    use_word_level_embeddings=True,
    dense_regularization_coef=1e-4,
    dense_dropout=.5,
    lstm_dropout=.5,
    attention_num_heads=3,
    attention_head_size=64,
    feature_params={'vocab_size': 255},
)

Exemple #4

Fichier : large_model_config.py Projet : dandersonw/ai-final-project

import text_model

features = {'tokens'}

config = text_model.Config(lstm_layers=1,
                           lstm_size=512,
                           embedding_size=128,
                           dense_regularization_coef=1e-4,
                           dense_dropout=.5,
                           lstm_dropout=.5,
                           attention_num_heads=3,
                           attention_head_size=128,
                           feature_params={'vocab_size': 255},)