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Running
on
Zero
Running
on
Zero
| import torch | |
| from .perceiver import DynamicCompressor | |
| class IdentityMap(torch.nn.Module): | |
| def __init__(self): | |
| super().__init__() | |
| def forward(self, x, *args, **kwargs): | |
| return x | |
| def config(self): | |
| return {"mm_resampler_type": None} | |
| def build_vision_resampler(model_args, delay_load=False, **kwargs): | |
| # import pdb;pdb.set_trace() | |
| resampler_type = getattr(model_args, 'mm_resampler_type', None) | |
| if resampler_type == 'dynamic_compressor': | |
| return DynamicCompressor(model_args, **kwargs) | |
| elif resampler_type is None: | |
| return IdentityMap() | |
| else: | |
| raise ValueError(f'Unknown resampler type: {resampler_type}') | |