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from models.m2d.portable_m2d import PortableM2D as M2D
from models.transformer_wrapper import BaseModelWrapper
class M2DWrapper(BaseModelWrapper):
def __init__(self) -> None:
super().__init__()
self.m2d = M2D()
def mel_forward(self, x):
return self.m2d.to_normalized_feature(x)
def forward(self, spec):
return self.m2d.forward_mel(spec)
def separate_params(self):
pt_params = [[], [], [], [], [], [], [], [], [], [], [], []]
for k, p in self.named_parameters():
if any(['cls_token' in k,
'pos_embed' in k,
'norm_stats' in k,
'patch_embed' in k]):
pt_params[0].append(p)
elif 'blocks.0.' in k:
pt_params[0].append(p)
elif 'blocks.1.' in k:
pt_params[1].append(p)
elif 'blocks.2.' in k:
pt_params[2].append(p)
elif 'blocks.3.' in k:
pt_params[3].append(p)
elif 'blocks.4.' in k:
pt_params[4].append(p)
elif 'blocks.5.' in k:
pt_params[5].append(p)
elif 'blocks.6.' in k:
pt_params[6].append(p)
elif 'blocks.7.' in k:
pt_params[7].append(p)
elif 'blocks.8.' in k:
pt_params[8].append(p)
elif 'blocks.9.' in k:
pt_params[9].append(p)
elif 'blocks.10.' in k:
pt_params[10].append(p)
elif 'blocks.11.' in k:
pt_params[11].append(p)
elif 'backbone.norm.weight' in k or 'backbone.norm.bias' in k:
pt_params[11].append(p)
else:
raise ValueError(f"Check separate params for M2D! Unknown key: {k}")
return list(reversed(pt_params))