mirror of
https://github.com/kohya-ss/sd-scripts.git
synced 2026-04-15 08:36:41 +00:00
Update accel_sdxl_gen_img.py
This commit is contained in:
DKnight54
GitHub
@@ -2440,272 +2440,275 @@ def main(args):
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# repeat prompt
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for pi in range(args.images_per_prompt if len(raw_prompts) == 1 else len(raw_prompts)):
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raw_prompt = raw_prompts[pi] if len(raw_prompts) > 1 else raw_prompts[0]
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if distributed_state.is_main_process:
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raw_prompt = raw_prompts[pi] if len(raw_prompts) > 1 else raw_prompts[0]
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if pi == 0 or len(raw_prompts) > 1:
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# parse prompt: if prompt is not changed, skip parsing
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width = args.W
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height = args.H
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original_width = args.original_width
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original_height = args.original_height
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original_width_negative = args.original_width_negative
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original_height_negative = args.original_height_negative
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crop_top = args.crop_top
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crop_left = args.crop_left
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scale = args.scale
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negative_scale = args.negative_scale
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steps = args.steps
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seed = None
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seeds = None
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strength = 0.8 if args.strength is None else args.strength
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negative_prompt = ""
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clip_prompt = None
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network_muls = None
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if distributed_state.is_main_process:
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# parse prompt: if prompt is not changed, skip parsing
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width = args.W
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height = args.H
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original_width = args.original_width
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original_height = args.original_height
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original_width_negative = args.original_width_negative
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original_height_negative = args.original_height_negative
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crop_top = args.crop_top
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crop_left = args.crop_left
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scale = args.scale
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negative_scale = args.negative_scale
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steps = args.steps
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seed = None
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seeds = None
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strength = 0.8 if args.strength is None else args.strength
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negative_prompt = ""
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clip_prompt = None
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network_muls = None
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# Deep Shrink
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ds_depth_1 = None # means no override
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ds_timesteps_1 = args.ds_timesteps_1
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ds_depth_2 = args.ds_depth_2
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ds_timesteps_2 = args.ds_timesteps_2
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ds_ratio = args.ds_ratio
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# Deep Shrink
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ds_depth_1 = None # means no override
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ds_timesteps_1 = args.ds_timesteps_1
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ds_depth_2 = args.ds_depth_2
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ds_timesteps_2 = args.ds_timesteps_2
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ds_ratio = args.ds_ratio
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# Gradual Latent
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gl_timesteps = None # means no override
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gl_ratio = args.gradual_latent_ratio
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gl_every_n_steps = args.gradual_latent_every_n_steps
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gl_ratio_step = args.gradual_latent_ratio_step
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gl_s_noise = args.gradual_latent_s_noise
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gl_unsharp_params = args.gradual_latent_unsharp_params
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# Gradual Latent
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gl_timesteps = None # means no override
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gl_ratio = args.gradual_latent_ratio
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gl_every_n_steps = args.gradual_latent_every_n_steps
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gl_ratio_step = args.gradual_latent_ratio_step
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gl_s_noise = args.gradual_latent_s_noise
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gl_unsharp_params = args.gradual_latent_unsharp_params
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prompt_args = raw_prompt.strip().split(" --")
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prompt = prompt_args[0]
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logger.info(f"prompt {prompt_index+1}/{len(prompt_list)}: {prompt}")
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prompt_args = raw_prompt.strip().split(" --")
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prompt = prompt_args[0]
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logger.info(f"prompt {prompt_index+1}/{len(prompt_list)}: {prompt}")
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for parg in prompt_args[1:]:
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try:
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m = re.match(r"w (\d+)", parg, re.IGNORECASE)
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if m:
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width = int(m.group(1))
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logger.info(f"width: {width}")
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continue
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if distributed_state.is_main_process:
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try:
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m = re.match(r"w (\d+)", parg, re.IGNORECASE)
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if m:
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width = int(m.group(1))
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logger.info(f"width: {width}")
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continue
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m = re.match(r"h (\d+)", parg, re.IGNORECASE)
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if m:
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height = int(m.group(1))
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logger.info(f"height: {height}")
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continue
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m = re.match(r"h (\d+)", parg, re.IGNORECASE)
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if m:
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height = int(m.group(1))
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logger.info(f"height: {height}")
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continue
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m = re.match(r"ow (\d+)", parg, re.IGNORECASE)
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if m:
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original_width = int(m.group(1))
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logger.info(f"original width: {original_width}")
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continue
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m = re.match(r"ow (\d+)", parg, re.IGNORECASE)
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if m:
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original_width = int(m.group(1))
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logger.info(f"original width: {original_width}")
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continue
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m = re.match(r"oh (\d+)", parg, re.IGNORECASE)
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if m:
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original_height = int(m.group(1))
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logger.info(f"original height: {original_height}")
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continue
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m = re.match(r"oh (\d+)", parg, re.IGNORECASE)
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if m:
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original_height = int(m.group(1))
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logger.info(f"original height: {original_height}")
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continue
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m = re.match(r"nw (\d+)", parg, re.IGNORECASE)
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if m:
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original_width_negative = int(m.group(1))
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logger.info(f"original width negative: {original_width_negative}")
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continue
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m = re.match(r"nw (\d+)", parg, re.IGNORECASE)
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if m:
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original_width_negative = int(m.group(1))
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logger.info(f"original width negative: {original_width_negative}")
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continue
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m = re.match(r"nh (\d+)", parg, re.IGNORECASE)
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if m:
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original_height_negative = int(m.group(1))
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logger.info(f"original height negative: {original_height_negative}")
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continue
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m = re.match(r"nh (\d+)", parg, re.IGNORECASE)
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if m:
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original_height_negative = int(m.group(1))
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logger.info(f"original height negative: {original_height_negative}")
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continue
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m = re.match(r"ct (\d+)", parg, re.IGNORECASE)
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if m:
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crop_top = int(m.group(1))
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logger.info(f"crop top: {crop_top}")
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continue
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m = re.match(r"ct (\d+)", parg, re.IGNORECASE)
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if m:
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crop_top = int(m.group(1))
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logger.info(f"crop top: {crop_top}")
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continue
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m = re.match(r"cl (\d+)", parg, re.IGNORECASE)
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if m:
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crop_left = int(m.group(1))
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logger.info(f"crop left: {crop_left}")
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continue
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m = re.match(r"cl (\d+)", parg, re.IGNORECASE)
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if m:
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crop_left = int(m.group(1))
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logger.info(f"crop left: {crop_left}")
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continue
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m = re.match(r"s (\d+)", parg, re.IGNORECASE)
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if m: # steps
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steps = max(1, min(1000, int(m.group(1))))
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logger.info(f"steps: {steps}")
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continue
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m = re.match(r"s (\d+)", parg, re.IGNORECASE)
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if m: # steps
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steps = max(1, min(1000, int(m.group(1))))
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logger.info(f"steps: {steps}")
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continue
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m = re.match(r"d ([\d,]+)", parg, re.IGNORECASE)
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if m: # seed
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seeds = [int(d) for d in m.group(1).split(",")]
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logger.info(f"seeds: {seeds}")
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continue
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m = re.match(r"d ([\d,]+)", parg, re.IGNORECASE)
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if m: # seed
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seeds = [int(d) for d in m.group(1).split(",")]
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logger.info(f"seeds: {seeds}")
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continue
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m = re.match(r"l ([\d\.]+)", parg, re.IGNORECASE)
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if m: # scale
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scale = float(m.group(1))
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logger.info(f"scale: {scale}")
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continue
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m = re.match(r"l ([\d\.]+)", parg, re.IGNORECASE)
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if m: # scale
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scale = float(m.group(1))
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logger.info(f"scale: {scale}")
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continue
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m = re.match(r"nl ([\d\.]+|none|None)", parg, re.IGNORECASE)
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if m: # negative scale
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if m.group(1).lower() == "none":
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negative_scale = None
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else:
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negative_scale = float(m.group(1))
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logger.info(f"negative scale: {negative_scale}")
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continue
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m = re.match(r"nl ([\d\.]+|none|None)", parg, re.IGNORECASE)
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if m: # negative scale
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if m.group(1).lower() == "none":
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negative_scale = None
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else:
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negative_scale = float(m.group(1))
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logger.info(f"negative scale: {negative_scale}")
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continue
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m = re.match(r"t ([\d\.]+)", parg, re.IGNORECASE)
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if m: # strength
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strength = float(m.group(1))
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logger.info(f"strength: {strength}")
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continue
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m = re.match(r"t ([\d\.]+)", parg, re.IGNORECASE)
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if m: # strength
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strength = float(m.group(1))
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logger.info(f"strength: {strength}")
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continue
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m = re.match(r"n (.+)", parg, re.IGNORECASE)
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if m: # negative prompt
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negative_prompt = m.group(1)
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logger.info(f"negative prompt: {negative_prompt}")
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continue
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m = re.match(r"n (.+)", parg, re.IGNORECASE)
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if m: # negative prompt
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negative_prompt = m.group(1)
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logger.info(f"negative prompt: {negative_prompt}")
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continue
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m = re.match(r"c (.+)", parg, re.IGNORECASE)
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if m: # clip prompt
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clip_prompt = m.group(1)
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logger.info(f"clip prompt: {clip_prompt}")
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continue
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m = re.match(r"c (.+)", parg, re.IGNORECASE)
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if m: # clip prompt
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clip_prompt = m.group(1)
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logger.info(f"clip prompt: {clip_prompt}")
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continue
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m = re.match(r"am ([\d\.\-,]+)", parg, re.IGNORECASE)
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if m: # network multiplies
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network_muls = [float(v) for v in m.group(1).split(",")]
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while len(network_muls) < len(networks):
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network_muls.append(network_muls[-1])
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logger.info(f"network mul: {network_muls}")
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continue
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m = re.match(r"am ([\d\.\-,]+)", parg, re.IGNORECASE)
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if m: # network multiplies
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network_muls = [float(v) for v in m.group(1).split(",")]
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while len(network_muls) < len(networks):
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network_muls.append(network_muls[-1])
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logger.info(f"network mul: {network_muls}")
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continue
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# Deep Shrink
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m = re.match(r"dsd1 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink depth 1
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ds_depth_1 = int(m.group(1))
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logger.info(f"deep shrink depth 1: {ds_depth_1}")
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continue
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m = re.match(r"dsd1 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink depth 1
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ds_depth_1 = int(m.group(1))
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logger.info(f"deep shrink depth 1: {ds_depth_1}")
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continue
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m = re.match(r"dst1 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink timesteps 1
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ds_timesteps_1 = int(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink timesteps 1: {ds_timesteps_1}")
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continue
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m = re.match(r"dst1 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink timesteps 1
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ds_timesteps_1 = int(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink timesteps 1: {ds_timesteps_1}")
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continue
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m = re.match(r"dsd2 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink depth 2
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ds_depth_2 = int(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink depth 2: {ds_depth_2}")
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continue
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m = re.match(r"dsd2 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink depth 2
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ds_depth_2 = int(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink depth 2: {ds_depth_2}")
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continue
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m = re.match(r"dst2 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink timesteps 2
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ds_timesteps_2 = int(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink timesteps 2: {ds_timesteps_2}")
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continue
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m = re.match(r"dst2 ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink timesteps 2
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ds_timesteps_2 = int(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink timesteps 2: {ds_timesteps_2}")
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continue
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m = re.match(r"dsr ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink ratio
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ds_ratio = float(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink ratio: {ds_ratio}")
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continue
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m = re.match(r"dsr ([\d\.]+)", parg, re.IGNORECASE)
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if m: # deep shrink ratio
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ds_ratio = float(m.group(1))
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ds_depth_1 = ds_depth_1 if ds_depth_1 is not None else -1 # -1 means override
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logger.info(f"deep shrink ratio: {ds_ratio}")
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continue
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# Gradual Latent
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m = re.match(r"glt ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent timesteps
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gl_timesteps = int(m.group(1))
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logger.info(f"gradual latent timesteps: {gl_timesteps}")
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continue
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m = re.match(r"glr ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent ratio
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gl_ratio = float(m.group(1))
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gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
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logger.info(f"gradual latent ratio: {ds_ratio}")
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continue
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m = re.match(r"gle ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent every n steps
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gl_every_n_steps = int(m.group(1))
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gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
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logger.info(f"gradual latent every n steps: {gl_every_n_steps}")
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continue
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m = re.match(r"gls ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent ratio step
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gl_ratio_step = float(m.group(1))
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gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
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logger.info(f"gradual latent ratio step: {gl_ratio_step}")
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continue
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m = re.match(r"glsn ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent s noise
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gl_s_noise = float(m.group(1))
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gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
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logger.info(f"gradual latent s noise: {gl_s_noise}")
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continue
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m = re.match(r"glus ([\d\.\-,]+)", parg, re.IGNORECASE)
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if m: # gradual latent unsharp params
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gl_unsharp_params = m.group(1)
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gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
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logger.info(f"gradual latent unsharp params: {gl_unsharp_params}")
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continue
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# Gradual Latent
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m = re.match(r"glt ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent timesteps
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gl_timesteps = int(m.group(1))
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logger.info(f"gradual latent timesteps: {gl_timesteps}")
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continue
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m = re.match(r"glt ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent timesteps
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gl_timesteps = int(m.group(1))
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logger.info(f"gradual latent timesteps: {gl_timesteps}")
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continue
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m = re.match(r"glr ([\d\.]+)", parg, re.IGNORECASE)
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if m: # gradual latent ratio
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gl_ratio = float(m.group(1))
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gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
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logger.info(f"gradual latent ratio: {ds_ratio}")
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continue
|
||||
m = re.match(r"glr ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent ratio
|
||||
gl_ratio = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent ratio: {ds_ratio}")
|
||||
continue
|
||||
|
||||
m = re.match(r"gle ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent every n steps
|
||||
gl_every_n_steps = int(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent every n steps: {gl_every_n_steps}")
|
||||
continue
|
||||
m = re.match(r"gle ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent every n steps
|
||||
gl_every_n_steps = int(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent every n steps: {gl_every_n_steps}")
|
||||
continue
|
||||
|
||||
m = re.match(r"gls ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent ratio step
|
||||
gl_ratio_step = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent ratio step: {gl_ratio_step}")
|
||||
continue
|
||||
m = re.match(r"gls ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent ratio step
|
||||
gl_ratio_step = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent ratio step: {gl_ratio_step}")
|
||||
continue
|
||||
|
||||
m = re.match(r"glsn ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent s noise
|
||||
gl_s_noise = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent s noise: {gl_s_noise}")
|
||||
continue
|
||||
m = re.match(r"glsn ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent s noise
|
||||
gl_s_noise = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent s noise: {gl_s_noise}")
|
||||
continue
|
||||
|
||||
m = re.match(r"glus ([\d\.\-,]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent unsharp params
|
||||
gl_unsharp_params = m.group(1)
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent unsharp params: {gl_unsharp_params}")
|
||||
continue
|
||||
m = re.match(r"glus ([\d\.\-,]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent unsharp params
|
||||
gl_unsharp_params = m.group(1)
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent unsharp params: {gl_unsharp_params}")
|
||||
continue
|
||||
|
||||
# Gradual Latent
|
||||
m = re.match(r"glt ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent timesteps
|
||||
gl_timesteps = int(m.group(1))
|
||||
logger.info(f"gradual latent timesteps: {gl_timesteps}")
|
||||
continue
|
||||
|
||||
m = re.match(r"glr ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent ratio
|
||||
gl_ratio = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent ratio: {ds_ratio}")
|
||||
continue
|
||||
|
||||
m = re.match(r"gle ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent every n steps
|
||||
gl_every_n_steps = int(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent every n steps: {gl_every_n_steps}")
|
||||
continue
|
||||
|
||||
m = re.match(r"gls ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent ratio step
|
||||
gl_ratio_step = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent ratio step: {gl_ratio_step}")
|
||||
continue
|
||||
|
||||
m = re.match(r"glsn ([\d\.]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent s noise
|
||||
gl_s_noise = float(m.group(1))
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent s noise: {gl_s_noise}")
|
||||
continue
|
||||
|
||||
m = re.match(r"glus ([\d\.\-,]+)", parg, re.IGNORECASE)
|
||||
if m: # gradual latent unsharp params
|
||||
gl_unsharp_params = m.group(1)
|
||||
gl_timesteps = gl_timesteps if gl_timesteps is not None else -1 # -1 means override
|
||||
logger.info(f"gradual latent unsharp params: {gl_unsharp_params}")
|
||||
continue
|
||||
|
||||
except ValueError as ex:
|
||||
logger.error(f"Exception in parsing / 解析エラー: {parg}")
|
||||
logger.error(f"{ex}")
|
||||
except ValueError as ex:
|
||||
logger.error(f"Exception in parsing / 解析エラー: {parg}")
|
||||
logger.error(f"{ex}")
|
||||
|
||||
# override Deep Shrink
|
||||
if ds_depth_1 is not None:
|
||||
@@ -2825,12 +2828,14 @@ def main(args):
|
||||
batch_data_split = [] #[batch_data[i:i+3] for i in range(0, len(my_list), 3)]
|
||||
batch_index = []
|
||||
for i in range(len(batch_data)):
|
||||
logger.info(f"Prompt {i+1}: {batch_data[i].base.prompt}\n{batch_data[i]}")
|
||||
batch_index.append(batch_data[i])
|
||||
if (i+1) % args.batch_size == 0:
|
||||
batch_data_split.append(batch_index.copy())
|
||||
batch_index.clear()
|
||||
logger.info(f"batch_data_split: {batch_data_split}")
|
||||
if distributed_state.is_main_process:
|
||||
logger.info(f"Prompt {i+1}: {batch_data[i].base.prompt}\n{batch_data[i]}")
|
||||
batch_index.append(batch_data[i])
|
||||
if (i+1) % args.batch_size == 0:
|
||||
batch_data_split.append(batch_index.copy())
|
||||
batch_index.clear()
|
||||
if distributed_state.is_main_process:
|
||||
logger.info(f"batch_data_split: {batch_data_split}")
|
||||
with torch.no_grad():
|
||||
with distributed_state.split_between_processes(batch_data_split) as batch_list:
|
||||
logger.info(f"Loading batch of {len(batch_list[0])} prompts onto device {distributed_state.device}:")
|
||||
@@ -2839,33 +2844,35 @@ def main(args):
|
||||
logger.info(f"Prompt {i+1}: {batch_list[0][i].base.prompt}")
|
||||
prev_image = process_batch(batch_list[0], highres_fix)[0]
|
||||
distributed_state.wait_for_everyone()
|
||||
batch_data.clear()
|
||||
|
||||
batch_data.append(b1)
|
||||
if distributed_state.is_main_process:
|
||||
batch_data.clear()
|
||||
if distributed_state.is_main_process:
|
||||
batch_data.append(b1)
|
||||
if len(batch_data) == args.batch_size*distributed_state.num_processes:
|
||||
logger.info(f"Collected {len(batch_data)} prompts for {distributed_state.num_processes} devices.")
|
||||
logger.info(f"{batch_data}")
|
||||
batch_data_split = [] #[batch_data[i:i+3] for i in range(0, len(my_list), 3)]
|
||||
batch_index = []
|
||||
test_batch_data_split = []
|
||||
test_batch_index = []
|
||||
for i in range(len(batch_data)):
|
||||
logger.info(f"Prompt {i+1}: {batch_data[i].base.prompt}\n{batch_data[i]}")
|
||||
batch_index.append(batch_data[i])
|
||||
test_batch_index.append(batch_data[i])
|
||||
if (i+1) % args.batch_size == 0:
|
||||
logger.info(f"Loading {batch_index}")
|
||||
batch_data_split.append(batch_index.copy())
|
||||
batch_index.clear()
|
||||
if (i+1) % 4 == 0:
|
||||
logger.info(f"Loading {test_batch_index}")
|
||||
test_batch_data_split.append(test_batch_index.copy())
|
||||
test_batch_index.clear()
|
||||
logger.info(f"batch_data_split: {batch_data_split}")
|
||||
for i in range(len(test_batch_data_split)):
|
||||
logger.info(f"test_batch_data_split[{i}]: {test_batch_data_split[i]}")
|
||||
for j in range(len(test_batch_data_split[i])):
|
||||
logger.info(f"Prompt {j}: {test_batch_data_split[i][j].base.prompt}")
|
||||
if distributed_state.is_main_process:
|
||||
logger.info(f"Collected {len(batch_data)} prompts for {distributed_state.num_processes} devices.")
|
||||
logger.info(f"{batch_data}")
|
||||
batch_data_split = [] #[batch_data[i:i+3] for i in range(0, len(my_list), 3)]
|
||||
batch_index = []
|
||||
test_batch_data_split = []
|
||||
test_batch_index = []
|
||||
for i in range(len(batch_data)):
|
||||
logger.info(f"Prompt {i+1}: {batch_data[i].base.prompt}\n{batch_data[i]}")
|
||||
batch_index.append(batch_data[i])
|
||||
test_batch_index.append(batch_data[i])
|
||||
if (i+1) % args.batch_size == 0:
|
||||
logger.info(f"Loading {batch_index}")
|
||||
batch_data_split.append(batch_index.copy())
|
||||
batch_index.clear()
|
||||
if (i+1) % 4 == 0:
|
||||
logger.info(f"Loading {test_batch_index}")
|
||||
test_batch_data_split.append(test_batch_index.copy())
|
||||
test_batch_index.clear()
|
||||
logger.info(f"batch_data_split: {batch_data_split}")
|
||||
for i in range(len(test_batch_data_split)):
|
||||
logger.info(f"test_batch_data_split[{i}]: {test_batch_data_split[i]}")
|
||||
for j in range(len(test_batch_data_split[i])):
|
||||
logger.info(f"Prompt {j}: {test_batch_data_split[i][j].base.prompt}")
|
||||
|
||||
with torch.no_grad():
|
||||
with distributed_state.split_between_processes(batch_data_split) as batch_list:
|
||||
@@ -2875,7 +2882,8 @@ def main(args):
|
||||
logger.info(f"Prompt {i+1}: {batch_list[0][i].base.prompt}")
|
||||
prev_image = process_batch(batch_list[0], highres_fix)[0]
|
||||
distributed_state.wait_for_everyone()
|
||||
batch_data.clear()
|
||||
if distributed_state.is_main_process:
|
||||
batch_data.clear()
|
||||
|
||||
global_step += 1
|
||||
|
||||
@@ -2884,13 +2892,14 @@ def main(args):
|
||||
if len(batch_data) > 0:
|
||||
batch_data_split = [] #[batch_data[i:i+3] for i in range(0, len(my_list), 3)]
|
||||
batch_index = []
|
||||
for i in range(len(batch_data)):
|
||||
logger.info(f"Prompt {i+1}: {batch_data[i].base.prompt}\n{batch_data[i]}")
|
||||
batch_index.append(batch_data[i])
|
||||
if (i+1) % args.batch_size == 0:
|
||||
batch_data_split.append(batch_index.copy())
|
||||
batch_index.clear()
|
||||
logger.info(f"{batch_data_split}")
|
||||
if distributed_state.is_main_process:
|
||||
for i in range(len(batch_data)):
|
||||
logger.info(f"Prompt {i+1}: {batch_data[i].base.prompt}\n{batch_data[i]}")
|
||||
batch_index.append(batch_data[i])
|
||||
if (i+1) % args.batch_size == 0:
|
||||
batch_data_split.append(batch_index.copy())
|
||||
batch_index.clear()
|
||||
logger.info(f"{batch_data_split}")
|
||||
with torch.no_grad():
|
||||
with distributed_state.split_between_processes(batch_data_split) as batch_list:
|
||||
logger.info(f"Loading batch of {len(batch_list[0])} prompts onto device {distributed_state.device}:")
|
||||
@@ -2899,7 +2908,8 @@ def main(args):
|
||||
logger.info(f"Prompt {i+1}: {batch_list[0][i].base.prompt}")
|
||||
prev_image = process_batch(batch_list[0], highres_fix)[0]
|
||||
distributed_state.wait_for_everyone()
|
||||
batch_data.clear()
|
||||
if distributed_state.is_main_process:
|
||||
batch_data.clear()
|
||||
|
||||
logger.info("done!")
|
||||
|
||||
|
||||
Reference in New Issue
Block a user