(
vae, flux_transformer, flux_controlnet, args, accelerator, weight_dtype, step, is_final_validation=False
)
| 73 | |
| 74 | |
| 75 | def log_validation( |
| 76 | vae, flux_transformer, flux_controlnet, args, accelerator, weight_dtype, step, is_final_validation=False |
| 77 | ): |
| 78 | logger.info("Running validation... ") |
| 79 | |
| 80 | if not is_final_validation: |
| 81 | flux_controlnet = accelerator.unwrap_model(flux_controlnet) |
| 82 | pipeline = FluxControlNetPipeline.from_pretrained( |
| 83 | args.pretrained_model_name_or_path, |
| 84 | controlnet=flux_controlnet, |
| 85 | transformer=flux_transformer, |
| 86 | torch_dtype=torch.bfloat16, |
| 87 | ) |
| 88 | else: |
| 89 | flux_controlnet = FluxControlNetModel.from_pretrained( |
| 90 | args.output_dir, torch_dtype=torch.bfloat16, variant=args.save_weight_dtype |
| 91 | ) |
| 92 | pipeline = FluxControlNetPipeline.from_pretrained( |
| 93 | args.pretrained_model_name_or_path, |
| 94 | controlnet=flux_controlnet, |
| 95 | transformer=flux_transformer, |
| 96 | torch_dtype=torch.bfloat16, |
| 97 | ) |
| 98 | |
| 99 | pipeline.to(accelerator.device) |
| 100 | pipeline.set_progress_bar_config(disable=True) |
| 101 | |
| 102 | if args.enable_xformers_memory_efficient_attention: |
| 103 | pipeline.enable_xformers_memory_efficient_attention() |
| 104 | |
| 105 | if args.seed is None: |
| 106 | generator = None |
| 107 | else: |
| 108 | generator = torch.Generator(device=accelerator.device).manual_seed(args.seed) |
| 109 | |
| 110 | if len(args.validation_image) == len(args.validation_prompt): |
| 111 | validation_images = args.validation_image |
| 112 | validation_prompts = args.validation_prompt |
| 113 | elif len(args.validation_image) == 1: |
| 114 | validation_images = args.validation_image * len(args.validation_prompt) |
| 115 | validation_prompts = args.validation_prompt |
| 116 | elif len(args.validation_prompt) == 1: |
| 117 | validation_images = args.validation_image |
| 118 | validation_prompts = args.validation_prompt * len(args.validation_image) |
| 119 | else: |
| 120 | raise ValueError( |
| 121 | "number of `args.validation_image` and `args.validation_prompt` should be checked in `parse_args`" |
| 122 | ) |
| 123 | |
| 124 | image_logs = [] |
| 125 | if is_final_validation or torch.backends.mps.is_available(): |
| 126 | autocast_ctx = nullcontext() |
| 127 | else: |
| 128 | autocast_ctx = torch.autocast(accelerator.device.type) |
| 129 | |
| 130 | for validation_prompt, validation_image in zip(validation_prompts, validation_images): |
| 131 | from diffusers.utils import load_image |
| 132 |
no test coverage detected