| """CM3P model configuration"""
|
| from transformers import AutoConfig
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| from transformers.configuration_utils import PretrainedConfig
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| from transformers.utils import logging
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|
|
|
|
| logger = logging.get_logger(__name__)
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|
|
|
|
| class CM3PMetadataConfig(PretrainedConfig):
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| model_type = "CM3PMetadata"
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| base_config_key = "metadata_config"
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|
|
| def __init__(
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| self,
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| cls_embed=True,
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|
|
| projection_dim=512,
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| initializer_factor=1.0,
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|
|
| vocab_size=1000,
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| hidden_size=256,
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| intermediate_size=512,
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| num_hidden_layers=6,
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| num_attention_heads=4,
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| hidden_activation="gelu",
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| max_position_embeddings=128,
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| initializer_range=0.02,
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| initializer_cutoff_factor=2.0,
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| norm_eps=1e-5,
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| norm_bias=False,
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| pad_token_id=0,
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| bos_token_id=1,
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| eos_token_id=2,
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| global_rope_theta=10000.0,
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| attention_bias=False,
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| attention_dropout=0.0,
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| global_attn_every_n_layers=1,
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| local_attention=128,
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| local_rope_theta=10000.0,
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| embedding_dropout=0.0,
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| mlp_bias=False,
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| mlp_dropout=0.0,
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| decoder_bias=True,
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| deterministic_flash_attn=False,
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| reference_compile=None,
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| **kwargs,
|
| ):
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| super().__init__(
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| pad_token_id=pad_token_id,
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| bos_token_id=bos_token_id,
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| eos_token_id=eos_token_id,
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| **kwargs,
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| )
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|
|
| self.cls_embed = cls_embed
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|
|
| self.projection_dim = projection_dim
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| self.initializer_range = initializer_range
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| self.initializer_factor = initializer_factor
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| self.attention_dropout = attention_dropout
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|
|
| self.vocab_size = vocab_size
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| self.max_position_embeddings = max_position_embeddings
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| self.hidden_size = hidden_size
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| self.intermediate_size = intermediate_size
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| self.num_hidden_layers = num_hidden_layers
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| self.num_attention_heads = num_attention_heads
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| self.initializer_range = initializer_range
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| self.initializer_cutoff_factor = initializer_cutoff_factor
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| self.norm_eps = norm_eps
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| self.norm_bias = norm_bias
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| self.global_rope_theta = global_rope_theta
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| self.attention_bias = attention_bias
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| self.attention_dropout = attention_dropout
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| self.hidden_activation = hidden_activation
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| self.global_attn_every_n_layers = global_attn_every_n_layers
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| self.local_attention = local_attention
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| self.local_rope_theta = local_rope_theta
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| self.embedding_dropout = embedding_dropout
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| self.mlp_bias = mlp_bias
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| self.mlp_dropout = mlp_dropout
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| self.decoder_bias = decoder_bias
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| self.deterministic_flash_attn = deterministic_flash_attn
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| self.reference_compile = reference_compile
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|
|
| def to_dict(self):
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| output = super().to_dict()
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| output.pop("reference_compile", None)
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| return output
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|
|
|
|
| class CM3PAudioConfig(PretrainedConfig):
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| model_type = "CM3PAudio"
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| base_config_key = "audio_config"
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|
|
| def __init__(
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| self,
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| hidden_size=512,
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| intermediate_size=1024,
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| num_hidden_layers=6,
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| num_attention_heads=8,
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| hidden_activation="gelu",
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| max_position_embeddings=4096,
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| initializer_range=0.02,
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| initializer_cutoff_factor=2.0,
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| norm_eps=1e-5,
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| norm_bias=False,
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| global_rope_theta=160000.0,
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| attention_bias=False,
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| attention_dropout=0.0,
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| global_attn_every_n_layers=3,
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| local_attention=128,
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| local_rope_theta=10000.0,
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| embedding_dropout=0.0,
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| mlp_bias=False,
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| mlp_dropout=0.0,
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| decoder_bias=True,
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| deterministic_flash_attn=False,
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| reference_compile=None,
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|
|
| projector_intermediate_size=2048,
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| projector_dim=768,
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| projector_hidden_act="gelu",
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|
|
| sample_rate: int = 16000,
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| n_ftt: int = 2048,
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| n_mels: int = 80,
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| hop_length: int = 128,
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| f_min: int = 0,
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| f_max: int = 8000,
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| pad_mode: str = "constant",
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| **kwargs,
|
| ):
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| super().__init__(**kwargs)
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| self.vocab_size = 1
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| self.max_position_embeddings = max_position_embeddings
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| self.hidden_size = hidden_size
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| self.intermediate_size = intermediate_size
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| self.num_hidden_layers = num_hidden_layers
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| self.num_attention_heads = num_attention_heads
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| self.initializer_range = initializer_range
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| self.initializer_cutoff_factor = initializer_cutoff_factor
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| self.norm_eps = norm_eps
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| self.norm_bias = norm_bias
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| self.global_rope_theta = global_rope_theta
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| self.attention_bias = attention_bias
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| self.attention_dropout = attention_dropout
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| self.hidden_activation = hidden_activation
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| self.global_attn_every_n_layers = global_attn_every_n_layers
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| self.local_attention = local_attention
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| self.local_rope_theta = local_rope_theta
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| self.embedding_dropout = embedding_dropout
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| self.mlp_bias = mlp_bias
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| self.mlp_dropout = mlp_dropout
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| self.decoder_bias = decoder_bias
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| self.deterministic_flash_attn = deterministic_flash_attn
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| self.reference_compile = reference_compile
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|
|
| self.projector_intermediate_size = projector_intermediate_size
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| self.projector_dim = projector_dim
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| self.projector_hidden_act = projector_hidden_act
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|
|
| self.sample_rate = sample_rate
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| self.n_ftt = n_ftt
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| self.n_mels = n_mels
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| self.hop_length = hop_length
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| self.f_min = f_min
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| self.f_max = f_max
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| self.pad_mode = pad_mode
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|
|
| def to_dict(self):
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| output = super().to_dict()
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| output.pop("reference_compile", None)
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| return output
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|
|
|
|
| class CM3PBeatmapConfig(PretrainedConfig):
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| model_type = "CM3PBeatmap"
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| is_composition = True
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| base_config_key = "beatmap_config"
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| sub_configs = {"audio_config": CM3PAudioConfig}
|
|
|
| def __init__(
|
| self,
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| audio_config: dict = None,
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| audio_sos_token_id=3164,
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| audio_eos_token_id=3165,
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| audio_token_id=3166,
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| cls_embed=True,
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|
|
| projection_dim=512,
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| initializer_factor=1.0,
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|
|
| vocab_size=3167,
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| hidden_size=768,
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| intermediate_size=1152,
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| num_hidden_layers=22,
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| num_attention_heads=12,
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| hidden_activation="gelu",
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| max_position_embeddings=8192,
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| initializer_range=0.02,
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| initializer_cutoff_factor=2.0,
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| norm_eps=1e-5,
|
| norm_bias=False,
|
| pad_token_id=0,
|
| bos_token_id=1,
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| eos_token_id=2,
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| global_rope_theta=160000.0,
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| attention_bias=False,
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| attention_dropout=0.0,
|
| global_attn_every_n_layers=3,
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| local_attention=128,
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| local_rope_theta=10000.0,
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| embedding_dropout=0.0,
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| mlp_bias=False,
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| mlp_dropout=0.0,
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| decoder_bias=True,
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| classifier_bias=False,
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| classifier_activation="gelu",
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| deterministic_flash_attn=False,
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| sparse_prediction=False,
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| sparse_pred_ignore_index=-100,
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| reference_compile=None,
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| repad_logits_with_grad=False,
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|
|
| attn_implementation: str = None,
|
| **kwargs,
|
| ):
|
| super().__init__(
|
| pad_token_id=pad_token_id,
|
| bos_token_id=bos_token_id,
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| eos_token_id=eos_token_id,
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| attn_implementation=attn_implementation,
|
| **kwargs,
|
| )
|
|
|
| if audio_config is None:
|
| audio_config = {}
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| logger.info("`audio_config` is `None`. Initializing the `CM3PAudioConfig` with default values.")
|
|
|
| self.audio_config = CM3PAudioConfig(
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| attn_implementation=attn_implementation,
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| **audio_config
|
| )
|
|
|
| self.audio_sos_token_id = audio_sos_token_id
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| self.audio_eos_token_id = audio_eos_token_id
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| self.audio_token_id = audio_token_id
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| self.cls_embed = cls_embed
|
|
|
| self.projection_dim = projection_dim
|
| self.initializer_factor = initializer_factor
|
| self.vocab_size = vocab_size
|
| self.max_position_embeddings = max_position_embeddings
|
| self.hidden_size = hidden_size
|
| self.intermediate_size = intermediate_size
|
| self.num_hidden_layers = num_hidden_layers
|
| self.num_attention_heads = num_attention_heads
|
| self.initializer_range = initializer_range
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| self.initializer_cutoff_factor = initializer_cutoff_factor
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| self.norm_eps = norm_eps
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| self.norm_bias = norm_bias
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| self.global_rope_theta = global_rope_theta
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| self.attention_bias = attention_bias
|
| self.attention_dropout = attention_dropout
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| self.hidden_activation = hidden_activation
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| self.global_attn_every_n_layers = global_attn_every_n_layers
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| self.local_attention = local_attention
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| self.local_rope_theta = local_rope_theta
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| self.embedding_dropout = embedding_dropout
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| self.mlp_bias = mlp_bias
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| self.mlp_dropout = mlp_dropout
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| self.decoder_bias = decoder_bias
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| self.classifier_bias = classifier_bias
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| self.classifier_activation = classifier_activation
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| self.deterministic_flash_attn = deterministic_flash_attn
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| self.sparse_prediction = sparse_prediction
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| self.sparse_pred_ignore_index = sparse_pred_ignore_index
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| self.reference_compile = reference_compile
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| self.repad_logits_with_grad = repad_logits_with_grad
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|
|
| def to_dict(self):
|
| output = super().to_dict()
|
| output.pop("reference_compile", None)
|
| return output
|
|
|
|
|
| class CM3PConfig(PretrainedConfig):
|
| model_type = "CM3P"
|
| is_composition = True
|
| sub_configs = {"metadata_config": CM3PMetadataConfig, "beatmap_config": CM3PBeatmapConfig}
|
|
|
| def __init__(
|
| self,
|
| metadata_config=None,
|
| beatmap_config=None,
|
| projection_dim=512,
|
| logit_scale_init_value=2.6592,
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| initializer_factor=1.0,
|
| initializer_range=0.02,
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| loss_type=None,
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| has_decoder_head=False,
|
|
|
| attn_implementation: str = None,
|
| **kwargs
|
| ):
|
| super().__init__(
|
| attn_implementation=attn_implementation,
|
| **kwargs
|
| )
|
|
|
| if metadata_config is None:
|
| metadata_config = {}
|
| logger.debug("`metadata_config` is `None`. Initializing the `CM3PMetadataConfig` with default values.")
|
|
|
| if beatmap_config is None:
|
| beatmap_config = {}
|
| logger.debug("`beatmap_config` is `None`. initializing the `CM3PBeatmapConfig` with default values.")
|
|
|
| self.metadata_config = CM3PMetadataConfig(
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| attn_implementation=attn_implementation,
|
| **metadata_config
|
| )
|
| self.beatmap_config = CM3PBeatmapConfig(
|
| attn_implementation=attn_implementation,
|
| **beatmap_config
|
| )
|
|
|
| self.projection_dim = projection_dim
|
| self.logit_scale_init_value = logit_scale_init_value
|
| self.initializer_factor = initializer_factor
|
| self.initializer_range = initializer_range
|
| self.loss_type = loss_type
|
| self.has_decoder_head = has_decoder_head
|
|
|
|
|
| AutoConfig.register("CM3PMetadata", CM3PMetadataConfig)
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| AutoConfig.register("CM3PAudio", CM3PAudioConfig)
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| AutoConfig.register("CM3PBeatmap", CM3PBeatmapConfig)
|
| AutoConfig.register("CM3P", CM3PConfig)
|
|
|
| __all__ = ["CM3PConfig", "CM3PMetadataConfig", "CM3PAudioConfig", "CM3PBeatmapConfig"]
|
|
|
