clean up
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@@ -115,7 +115,6 @@ class ParquetVideoTextDataset(Dataset):
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else:
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pass
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# get_world_group().barrier()
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dist.barrier()
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if validation:
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with open(self.plan_output_dir) as f:
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@@ -126,4 +126,3 @@ class ForwardBatch:
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# Set do_classifier_free_guidance based on guidance scale and negative prompt
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if self.guidance_scale > 1.0:
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self.do_classifier_free_guidance = True
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# self.negative_prompt_embeds = []
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@@ -272,7 +272,6 @@ class WanTrainingPipeline(TrainingPipeline):
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logger.info("GPU memory usage before train_one_step: %s MB",
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gpu_memory_usage)
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# self._log_validation(self.transformer, self.training_args, 1)
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for step in range(self.init_steps + 1,
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self.training_args.max_train_steps + 1):
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start_time = time.perf_counter()
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@@ -2,15 +2,15 @@
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GPU_NUM=1 # 2,4,8
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MODEL_PATH="Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
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MODEL_TYPE="wan"
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DATA_MERGE_PATH="data/cats_480/merge.txt"
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OUTPUT_DIR="cats_480_2_latents_parq_neg2"
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VALIDATION_PATH="assets/2_cat_prompt.txt"
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DATA_MERGE_PATH="your/path/to/Mixkit-Src/merge.txt"
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OUTPUT_DIR="your/path"
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VALIDATION_PATH="assets/prompt.txt"
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torchrun --nproc_per_node=$GPU_NUM \
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fastvideo/data_preprocess/preprocess.py \
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--model_path $MODEL_PATH \
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--data_merge_path $DATA_MERGE_PATH \
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--preprocess_video_batch_size 1 \
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--preprocess_video_batch_size 8 \
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--max_height 480 \
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--max_width 832 \
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--num_frames 81 \
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@@ -19,6 +19,6 @@ torchrun --nproc_per_node=$GPU_NUM \
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--model_type $MODEL_TYPE \
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--train_fps 16 \
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--validation_prompt_txt $VALIDATION_PATH \
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--samples_per_file 1 \
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--flush_frequency 1 \
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--samples_per_file 32 \
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--flush_frequency 128 \
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--preprocess_task "t2v"
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