Ethanfel
d642255e70
Integrates GIMM-VFI alongside existing BIM/EMA/SGM models. Key feature: generates all intermediate frames in one forward pass (no recursive 2x passes needed for 4x/8x). - Vendor gimm_vfi_arch/ from kijai/ComfyUI-GIMM-VFI with device fixes - Two variants: RAFT-based (~80MB) and FlowFormer-based (~123MB) - Auto-download checkpoints from HuggingFace (Kijai/GIMM-VFI_safetensors) - Three new nodes: Load GIMM-VFI Model, GIMM-VFI Interpolate, GIMM-VFI Segment Interpolate - single_pass toggle: True=arbitrary timestep (default), False=recursive like other models - ds_factor parameter for high-res input downscaling Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
43 lines
1021 B
Python
43 lines
1021 B
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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# This source code is licensed under the license found in the
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# LICENSE file in the root directory of this source tree.
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# --------------------------------------------------------
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from torch import nn
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import torch
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# define siren layer & Siren model
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class Sine(nn.Module):
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"""Sine activation with scaling.
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Args:
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w0 (float): Omega_0 parameter from SIREN paper.
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"""
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def __init__(self, w0=1.0):
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super().__init__()
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self.w0 = w0
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def forward(self, x):
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return torch.sin(self.w0 * x)
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# Damping activation from http://arxiv.org/abs/2306.15242
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class Damping(nn.Module):
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"""Sine activation with sublinear factor
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Args:
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w0 (float): Omega_0 parameter from SIREN paper.
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"""
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def __init__(self, w0=1.0):
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super().__init__()
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self.w0 = w0
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def forward(self, x):
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x = torch.clamp(x, min=1e-30)
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return torch.sin(self.w0 * x) * torch.sqrt(x.abs())
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