update
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@@ -102,6 +102,8 @@ class Discriminator(nn.Module):
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class DMDiscriminator(nn.Module):
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def __init__(self):
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super().__init__()
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self.cls_pred_branch = nn.Sequential(
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nn.Conv2d(kernel_size=4, in_channels=1280, out_channels=1280, stride=2, padding=1), # 8x8 -> 4x4
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nn.GroupNorm(num_groups=32, num_channels=1280),
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@@ -191,7 +191,7 @@ def predict_noise(
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encoder_attention_mask,
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return_dict=False,
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guidance_scale=1,
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)
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):
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do_classifier_free_guidance = guidance_scale > 1.0
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latent_model_input = (
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torch.cat([noisy_model_input] * 2) if do_classifier_free_guidance else noisy_model_input
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@@ -1035,6 +1035,12 @@ if __name__ == "__main__":
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default=0.025,
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help="The threshold of the linear quadratic scheduler.",
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)
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parser.add_argument(
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"--linear_range",
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type=float,
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default=0.5,
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help="Range for linear quadratic scheduler.",
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)
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parser.add_argument(
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"--master_weight_type",
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type=str,
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@@ -0,0 +1,38 @@
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export WANDB_BASE_URL="https://api.wandb.ai"
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export WANDB_MODE=online
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torchrun --nnodes 1 --nproc_per_node 4 \
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fastvideo/distill_dmd.py \
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--seed 42 \
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--pretrained_model_name_or_path data/mochi \
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--model_type "mochi" \
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--cache_dir data/.cache \
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--data_json_path data/Mochi-425-Data/video2caption.json \
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--validation_prompt_dir data/Mochi-425-Data/validation \
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--gradient_checkpointing \
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--train_batch_size=1 \
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--num_latent_t 28 \
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--sp_size 4 \
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--train_sp_batch_size 2 \
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--dataloader_num_workers 4 \
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--gradient_accumulation_steps=1 \
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--max_train_steps=4000 \
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--learning_rate=1e-6 \
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--mixed_precision=bf16 \
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--checkpointing_steps=64 \
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--validation_steps 1 \
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--validation_sampling_steps 8 \
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--checkpoints_total_limit 3 \
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--allow_tf32 \
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--ema_start_step 0 \
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--cfg 0.0 \
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--log_validation \
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--output_dir="data/outputs/lq_euler_50_thres0.1_lrg_0.75_phase1_lr1e-6_repro" \
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--tracker_project_name PCM \
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--num_frames 29 \
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--scheduler_type pcm_linear_quadratic \
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--validation_guidance_scale 0.5,1.5,2.5 \
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--num_euler_timesteps 50 \
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--linear_quadratic_threshold 0.1 \
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--linear_range 0.75 \
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--multi_phased_distill_schedule 4000-1
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