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| from transformers.configuration_utils import PretrainedConfig | |
| from transformers.utils import logging | |
| from fairseq.data import Dictionary | |
| from transformers import AutoConfig, AutoModel, AutoModelForImageClassification | |
| logger = logging.get_logger(__name__) | |
| class VallexConfig(PretrainedConfig): | |
| model_type = "vallex" | |
| def __init__(self, | |
| n_layer=24, | |
| n_head=16, | |
| n_dim=1024, | |
| prefix_mode=1, | |
| num_quantizers=8, | |
| sample_rate=24000, | |
| ar_at_dict="", | |
| ar_st_dict="", | |
| nar_at_dict="", | |
| nar_st_dict="", | |
| nar_scale_factor=1.0, | |
| prepend_bos=True, | |
| norm_first=True, | |
| eps=0.0, | |
| only_ar=False, | |
| only_nar=False, | |
| **kwargs | |
| ): | |
| self.n_layer = n_layer | |
| self.n_head = n_head | |
| self.n_dim = n_dim | |
| self.prefix_mode = prefix_mode | |
| self.num_quantizers = num_quantizers | |
| self.sample_rate = sample_rate | |
| self.nar_scale_factor = nar_scale_factor | |
| self.prepend_bos = prepend_bos | |
| self.norm_first = norm_first | |
| self.ar_at_dict = ar_at_dict | |
| self.ar_st_dict = ar_st_dict | |
| self.nar_at_dict = nar_at_dict | |
| self.nar_st_dict = nar_st_dict | |
| self.eps = eps | |
| self.only_ar = only_ar | |
| self.only_nar = only_nar | |
| super().__init__( | |
| **kwargs | |
| ) | |
| AutoConfig.register("vallex", VallexConfig) |