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zR 2024-09-14 18:29:38 +08:00
parent 300fc75c49
commit e7835cd79c
2 changed files with 5 additions and 5 deletions
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6
sat/diffusion_video.py
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@ -323,10 +323,8 @@ class SATVideoDiffusionEngine(nn.Module):
if isinstance(c[k], torch.Tensor): if isinstance(c[k], torch.Tensor):
c[k], uc[k] = map(lambda y: y[k][:N].to(self.device), (c, uc)) c[k], uc[k] = map(lambda y: y[k][:N].to(self.device), (c, uc))
samples = self.sample(c, shape=z.shape[1:], uc=uc, batch_size=N, **sampling_kwargs) # b t c h w
samples = samples.permute(0, 2, 1, 3, 4).contiguous()
if self.noised_image_input: if self.noised_image_input:
print("Adding noise to first frame")
image = x[:, :, 0:1] image = x[:, :, 0:1]
image = self.add_noise_to_first_frame(image) image = self.add_noise_to_first_frame(image)
image = self.encode_first_stage(image, batch) image = self.encode_first_stage(image, batch)
@ -344,6 +342,8 @@ class SATVideoDiffusionEngine(nn.Module):
samples = samples.permute(0, 2, 1, 3, 4).contiguous() samples = samples.permute(0, 2, 1, 3, 4).contiguous()
log["samples"] = samples log["samples"] = samples
else: else:
samples = self.sample(c, shape=z.shape[1:], uc=uc, batch_size=N, **sampling_kwargs) # b t c h w
samples = samples.permute(0, 2, 1, 3, 4).contiguous()
if only_log_video_latents: if only_log_video_latents:
latents = 1.0 / self.scale_factor * samples latents = 1.0 / self.scale_factor * samples
log["latents"] = latents log["latents"] = latents

4
sat/finetune_multi_gpus.sh
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@ -1,8 +1,8 @@
#! /bin/bash #! /bin/bash
echo "RUN on $(hostname), CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES" echo "RUN on $(hostname), CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True"
run_cmd="torchrun --standalone --nproc_per_node=8 train_video.py --base configs/cogvideox_2b_lora.yaml configs/sft.yaml --seed $RANDOM" run_cmd="torchrun --standalone --nproc_per_node=8 train_video.py --base configs/cogvideox_5b_i2v_lora.yaml configs/sft.yaml --seed $RANDOM"
echo ${run_cmd} echo ${run_cmd}
eval ${run_cmd} eval ${run_cmd}