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e8694e9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 | """CM3P model configuration"""
from transformers import AutoConfig
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
class CM3PMetadataConfig(PretrainedConfig):
model_type = "cm3p_metadata_model"
base_config_key = "metadata_config"
def __init__(
self,
cls_embed=False,
projection_dim=512,
initializer_factor=1.0,
vocab_size=1000,
hidden_size=256,
intermediate_size=512,
num_hidden_layers=6,
num_attention_heads=4,
hidden_activation="gelu",
max_position_embeddings=128,
initializer_range=0.02,
initializer_cutoff_factor=2.0,
norm_eps=1e-5,
norm_bias=False,
pad_token_id=0,
bos_token_id=1,
eos_token_id=2,
global_rope_theta=10000.0,
attention_bias=False,
attention_dropout=0.0,
global_attn_every_n_layers=1,
local_attention=128,
local_rope_theta=10000.0,
embedding_dropout=0.0,
mlp_bias=False,
mlp_dropout=0.0,
decoder_bias=True,
deterministic_flash_attn=False,
reference_compile=None,
**kwargs,
):
super().__init__(
pad_token_id=pad_token_id,
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
**kwargs,
)
self.cls_embed = cls_embed
self.projection_dim = projection_dim
self.initializer_range = initializer_range
self.initializer_factor = initializer_factor
self.attention_dropout = attention_dropout
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
self.initializer_cutoff_factor = initializer_cutoff_factor
self.norm_eps = norm_eps
self.norm_bias = norm_bias
self.global_rope_theta = global_rope_theta
self.attention_bias = attention_bias
self.attention_dropout = attention_dropout
self.hidden_activation = hidden_activation
self.global_attn_every_n_layers = global_attn_every_n_layers
self.local_attention = local_attention
self.local_rope_theta = local_rope_theta
self.embedding_dropout = embedding_dropout
self.mlp_bias = mlp_bias
self.mlp_dropout = mlp_dropout
self.decoder_bias = decoder_bias
self.deterministic_flash_attn = deterministic_flash_attn
self.reference_compile = reference_compile
def to_dict(self):
output = super().to_dict()
output.pop("reference_compile", None)
return output
class CM3PAudioConfig(PretrainedConfig):
model_type = "cm3p_audio_model"
base_config_key = "audio_config"
def __init__(
self,
hidden_size=512,
intermediate_size=1024,
num_hidden_layers=6,
num_attention_heads=8,
hidden_activation="gelu",
max_position_embeddings=4096,
initializer_range=0.02,
initializer_cutoff_factor=2.0,
norm_eps=1e-5,
norm_bias=False,
global_rope_theta=160000.0,
attention_bias=False,
attention_dropout=0.0,
global_attn_every_n_layers=3,
local_attention=128,
local_rope_theta=10000.0,
embedding_dropout=0.0,
mlp_bias=False,
mlp_dropout=0.0,
decoder_bias=True,
deterministic_flash_attn=False,
reference_compile=None,
projector_intermediate_size=2048, # 4 * hidden_size for a 4x reduction in tokens
projector_dim=768,
projector_hidden_act="gelu",
sample_rate: int = 16000,
n_ftt: int = 2048,
n_mels: int = 80,
hop_length: int = 128,
f_min: int = 0,
f_max: int = 8000,
pad_mode: str = "constant",
**kwargs,
):
super().__init__(**kwargs)
self.vocab_size = 1
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
self.initializer_cutoff_factor = initializer_cutoff_factor
self.norm_eps = norm_eps
self.norm_bias = norm_bias
self.global_rope_theta = global_rope_theta
self.attention_bias = attention_bias
self.attention_dropout = attention_dropout
self.hidden_activation = hidden_activation
self.global_attn_every_n_layers = global_attn_every_n_layers
self.local_attention = local_attention
self.local_rope_theta = local_rope_theta
self.embedding_dropout = embedding_dropout
self.mlp_bias = mlp_bias
self.mlp_dropout = mlp_dropout
self.decoder_bias = decoder_bias
self.deterministic_flash_attn = deterministic_flash_attn
self.reference_compile = reference_compile
self.projector_intermediate_size = projector_intermediate_size
self.projector_dim = projector_dim
self.projector_hidden_act = projector_hidden_act
self.sample_rate = sample_rate
self.n_ftt = n_ftt
self.n_mels = n_mels
self.hop_length = hop_length
self.f_min = f_min
self.f_max = f_max
self.pad_mode = pad_mode
def to_dict(self):
output = super().to_dict()
output.pop("reference_compile", None)
return output
class CM3PBeatmapConfig(PretrainedConfig):
model_type = "cm3p_beatmap_model"
base_config_key = "beatmap_config"
sub_configs = {"audio_config": CM3PAudioConfig}
def __init__(
self,
audio_config: dict = None,
audio_sos_token_id=3164,
audio_eos_token_id=3165,
audio_token_id=3166,
cls_embed=False,
projection_dim=512,
initializer_factor=1.0,
vocab_size=3167,
hidden_size=768,
intermediate_size=1152,
num_hidden_layers=22,
num_attention_heads=12,
hidden_activation="gelu",
max_position_embeddings=8192,
initializer_range=0.02,
initializer_cutoff_factor=2.0,
norm_eps=1e-5,
norm_bias=False,
pad_token_id=0,
bos_token_id=1,
eos_token_id=2,
global_rope_theta=160000.0,
attention_bias=False,
attention_dropout=0.0,
global_attn_every_n_layers=3,
local_attention=128,
local_rope_theta=10000.0,
embedding_dropout=0.0,
mlp_bias=False,
mlp_dropout=0.0,
decoder_bias=True,
classifier_bias=False,
classifier_activation="gelu",
deterministic_flash_attn=False,
sparse_prediction=False,
sparse_pred_ignore_index=-100,
reference_compile=None,
repad_logits_with_grad=False,
**kwargs,
):
super().__init__(
pad_token_id=pad_token_id,
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
**kwargs,
)
if audio_config is None:
audio_config = {}
logger.info("`audio_config` is `None`. Initializing the `CM3PAudioConfig` with default values.")
self.audio_config = CM3PAudioConfig(**audio_config)
self.audio_sos_token_id = audio_sos_token_id
self.audio_eos_token_id = audio_eos_token_id
self.audio_token_id = audio_token_id
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
self.initializer_cutoff_factor = initializer_cutoff_factor
self.norm_eps = norm_eps
self.norm_bias = norm_bias
self.global_rope_theta = global_rope_theta
self.attention_bias = attention_bias
self.attention_dropout = attention_dropout
self.hidden_activation = hidden_activation
self.global_attn_every_n_layers = global_attn_every_n_layers
self.local_attention = local_attention
self.local_rope_theta = local_rope_theta
self.embedding_dropout = embedding_dropout
self.mlp_bias = mlp_bias
self.mlp_dropout = mlp_dropout
self.decoder_bias = decoder_bias
self.classifier_bias = classifier_bias
self.classifier_activation = classifier_activation
self.deterministic_flash_attn = deterministic_flash_attn
self.sparse_prediction = sparse_prediction
self.sparse_pred_ignore_index = sparse_pred_ignore_index
self.reference_compile = reference_compile
self.repad_logits_with_grad = repad_logits_with_grad
def to_dict(self):
output = super().to_dict()
output.pop("reference_compile", None)
return output
class CM3PConfig(PretrainedConfig):
model_type = "cm3p"
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,
initializer_factor=1.0,
initializer_range=0.02,
loss_type=None,
**kwargs
):
super().__init__(**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(**metadata_config)
self.beatmap_config = CM3PBeatmapConfig(**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
AutoConfig.register("cm3p_metadata_model", CM3PMetadataConfig)
AutoConfig.register("cm3p_audio_model", CM3PAudioConfig)
AutoConfig.register("cm3p_beatmap_model", CM3PBeatmapConfig)
AutoConfig.register("cm3p", CM3PConfig)
__all__ = ["CM3PConfig", "CM3PMetadataConfig", "CM3PAudioConfig", "CM3PBeatmapConfig"]
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