MLPs (GMLP) අත්හදා බැලීම කෙරෙහි අවධානය යොමු කරන්න

18from labml import experiment
19from labml.configs import option
20from labml_nn.transformers import TransformerConfigs
21from labml_nn.transformers.basic.autoregressive_experiment import Configs as BasicAutoRegressionConfigs
22from labml_nn.transformers.gmlp import GMLPBlock

25class Configs(BasicAutoRegressionConfigs):

34    transformer: TransformerConfigs = 'gMLP'

36    gmlp: GMLPBlock

38    d_ffn: int = 2048

41@option(Configs.gmlp, 'gMLP')
42def _gmlp_configs(c: Configs):

46    return GMLPBlock(c.d_model, c.d_ffn, c.seq_len)

49@option(Configs.transformer, 'gMLP')
50def _transformer_configs(c: Configs):

57    conf = TransformerConfigs()

59    conf.n_src_vocab = c.n_tokens
60    conf.n_tgt_vocab = c.n_tokens

62    conf.d_model = c.d_model

64    conf.encoder_layer = c.gmlp
65
66    return conf

69def main():

71    experiment.create(name="gMLP")

73    conf = Configs()

75    experiment.configs(conf, {

77        'tokenizer': 'character',

79        'prompt_separator': '',

81        'prompt': 'It is ',

83        'text': 'tiny_shakespeare',

86        'seq_len': 256,

88        'epochs': 128,

90        'batch_size': 32,

93        'inner_iterations': 10,

96        'd_model': 512,
97        'd_ffn': 2048,

100        'optimizer.optimizer': 'Noam',
101        'optimizer.learning_rate': 1.,
102    })

105    experiment.add_pytorch_models({'model': conf.model})

108    with experiment.start():

110        conf.run()

114if __name__ == '__main__':
115    main()