CIFAR 10 මත කොන්වී මික්සර් පුහුණු කරන්න

20from labml import experiment
21from labml.configs import option
22from labml_nn.experiments.cifar10 import CIFAR10Configs

25class Configs(CIFAR10Configs):

34    patch_size: int = 2

36    d_model: int = 256

38    n_layers: int = 8

40    kernel_size: int = 7

42    n_classes: int = 10

45@option(Configs.model)
46def _conv_mixer(c: Configs):

50    from labml_nn.conv_mixer import ConvMixerLayer, ConvMixer, ClassificationHead, PatchEmbeddings

53    return ConvMixer(ConvMixerLayer(c.d_model, c.kernel_size), c.n_layers,
54                     PatchEmbeddings(c.d_model, c.patch_size, 3),
55                     ClassificationHead(c.d_model, c.n_classes)).to(c.device)

58def main():

60    experiment.create(name='ConvMixer', comment='cifar10')

62    conf = Configs()

64    experiment.configs(conf, {

66        'optimizer.optimizer': 'Adam',
67        'optimizer.learning_rate': 2.5e-4,

70        'epochs': 150,
71        'train_batch_size': 64,

74        'train_dataset': 'cifar10_train_augmented',

76        'valid_dataset': 'cifar10_valid_no_augment',
77    })

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

81    with experiment.start():
82        conf.run()

86if __name__ == '__main__':
87    main()