flavioschneider
commited on
Commit
•
e661388
1
Parent(s):
3548637
Upload DMAE1d
Browse files- config.json +6 -1
- dmae.py +52 -0
- pytorch_model.bin +3 -0
config.json
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{
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"auto_map": {
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"AutoConfig": "dmae_config.DMAE1dConfig"
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},
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"model_type": "archinetai/dmae1d-ATC64-v2",
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"transformers_version": "4.24.0"
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}
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{
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"architectures": [
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"DMAE1d"
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],
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"auto_map": {
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"AutoConfig": "dmae_config.DMAE1dConfig",
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"AutoModel": "dmae.DMAE1d"
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},
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"model_type": "archinetai/dmae1d-ATC64-v2",
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"torch_dtype": "float32",
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"transformers_version": "4.24.0"
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}
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dmae.py
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import torch
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from transformers import PreTrainedModel
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from .dmae_config import DMAE1dConfig
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from audio_encoders_pytorch import ME1d, TanhBottleneck # pip install audio_encoders_pytorch==0.0.20
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from audio_diffusion_pytorch.unets import UNetV0, LTPlugin # pip install -U git+https://github.com/archinetai/audio-diffusion-pytorch.git@nightly # v0.0.2
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from audio_diffusion_pytorch.models import DiffusionAE
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class DMAE1d(PreTrainedModel):
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config_class = DMAE1dConfig
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def __init__(self, config: DMAE1dConfig):
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super().__init__(config)
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UNet = LTPlugin(
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UNetV0,
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num_filters=128,
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window_length=64,
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stride=64,
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)
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self.model = DiffusionAE(
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net_t=UNet,
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dim=1,
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in_channels=2,
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channels=[256, 512, 512, 512, 1024, 1024, 1024],
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factors=[1, 2, 2, 2, 2, 2, 2],
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items=[1, 2, 2, 2, 2, 2, 2],
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encoder=ME1d(
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in_channels=2,
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channels=512,
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multipliers=[1, 1, 1],
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factors=[2, 2],
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num_blocks=[4, 8],
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stft_num_fft=1023,
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stft_hop_length=256,
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out_channels=32,
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bottleneck=TanhBottleneck()
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),
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inject_depth=4
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)
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def forward(self, *args, **kwargs):
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return self.model(*args, **kwargs)
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def encode(self, *args, **kwargs):
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return self.model.encode(*args, **kwargs)
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@torch.no_grad()
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def decode(self, *args, **kwargs):
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return self.model.decode(*args, **kwargs)
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c9ad49fb4b5ba60c7db2774eebee21590731c9b2d423efff47d8e57119982f20
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size 740732261
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