Spaces:
Running
on
Zero
Running
on
Zero
NIRVANALAN
commited on
Commit
•
c3a2df4
1
Parent(s):
592a426
update
Browse files- app.py +88 -84
- configs/i23d_args.json +284 -0
app.py
CHANGED
@@ -32,6 +32,8 @@ import numpy as np
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import torch as th
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import torch.distributed as dist
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def install_dependency():
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# install full cuda first
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# subprocess.run(
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@@ -53,13 +55,13 @@ th.backends.cudnn.enabled = True
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from guided_diffusion import dist_util, logger
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from guided_diffusion.script_util import (
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NUM_CLASSES,
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model_and_diffusion_defaults,
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create_model_and_diffusion,
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add_dict_to_argparser,
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args_to_dict,
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)
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from pathlib import Path
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@@ -72,11 +74,11 @@ import nsr
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import nsr.lsgm
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from nsr.script_util import create_3DAE_model, encoder_and_nsr_defaults, loss_defaults, AE_with_Diffusion, rendering_options_defaults, eg3d_options_default, dataset_defaults
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from datasets.shapenet import load_eval_data
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from torch.utils.data import Subset
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from datasets.eg3d_dataset import init_dataset_kwargs
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from transport.train_utils import parse_transport_args
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from utils.infer_utils import remove_background, resize_foreground
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@@ -376,81 +378,81 @@ def main(args):
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def create_argparser():
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if __name__ == "__main__":
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os.environ[
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"TORCH_DISTRIBUTED_DEBUG"] = "DETAIL" # set to DETAIL for runtime logging.
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args = create_argparser().parse_args()
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# args.local_rank = int(os.environ["LOCAL_RANK"])
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args.local_rank = 0
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args.gpus = th.cuda.device_count()
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args.rendering_kwargs = rendering_options_defaults(args)
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# main(args)
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import torch as th
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import torch.distributed as dist
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from dnnlib.util import EasyDict
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def install_dependency():
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# install full cuda first
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# subprocess.run(
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from guided_diffusion import dist_util, logger
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from guided_diffusion.script_util import (
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model_and_diffusion_defaults,
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create_model_and_diffusion,
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args_to_dict,
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# NUM_CLASSES,
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# add_dict_to_argparser,
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# continuous_diffusion_defaults,
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# control_net_defaults,
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)
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from pathlib import Path
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import nsr.lsgm
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from nsr.script_util import create_3DAE_model, encoder_and_nsr_defaults, loss_defaults, AE_with_Diffusion, rendering_options_defaults, eg3d_options_default, dataset_defaults
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# from datasets.shapenet import load_eval_data
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# from torch.utils.data import Subset
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# from datasets.eg3d_dataset import init_dataset_kwargs
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# from transport.train_utils import parse_transport_args
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from utils.infer_utils import remove_background, resize_foreground
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# def create_argparser():
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# defaults = dict(
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# image_size_encoder=224,
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# triplane_scaling_divider=1.0, # divide by this value
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# diffusion_input_size=-1,
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# trainer_name='adm',
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# use_amp=False,
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# # triplane_scaling_divider=1.0, # divide by this value
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# # * sampling flags
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# clip_denoised=False,
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# num_samples=10,
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# num_instances=10, # for i23d, loop different condition
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# use_ddim=False,
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# ddpm_model_path="",
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# cldm_model_path="",
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# rec_model_path="",
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# # * eval logging flags
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# logdir="/mnt/lustre/yslan/logs/nips23/",
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# data_dir="",
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# eval_data_dir="",
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# eval_batch_size=1,
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# num_workers=1,
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# # * training flags for loading TrainingLoop class
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# overfitting=False,
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# image_size=128,
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# iterations=150000,
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# schedule_sampler="uniform",
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# anneal_lr=False,
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# lr=5e-5,
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# weight_decay=0.0,
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# lr_anneal_steps=0,
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# batch_size=1,
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# microbatch=-1, # -1 disables microbatches
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# ema_rate="0.9999", # comma-separated list of EMA values
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# log_interval=50,
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# eval_interval=2500,
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# save_interval=10000,
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# resume_checkpoint="",
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# resume_cldm_checkpoint="",
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# resume_checkpoint_EG3D="",
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# use_fp16=False,
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# fp16_scale_growth=1e-3,
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# load_submodule_name='', # for loading pretrained auto_encoder model
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# ignore_resume_opt=False,
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# freeze_ae=False,
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# denoised_ae=True,
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# # inference prompt
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# prompt="a red chair",
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# interval=1,
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# save_img=False,
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# use_train_trajectory=
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# False, # use train trajectory to sample images for fid calculation
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# unconditional_guidance_scale=1.0,
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# use_eos_feature=False,
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# export_mesh=False,
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# cond_key='caption',
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# allow_tf32=True,
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# )
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# defaults.update(model_and_diffusion_defaults())
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# defaults.update(encoder_and_nsr_defaults()) # type: ignore
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# defaults.update(loss_defaults())
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# defaults.update(continuous_diffusion_defaults())
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# defaults.update(control_net_defaults())
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# defaults.update(dataset_defaults())
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# parser = argparse.ArgumentParser()
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# add_dict_to_argparser(parser, defaults)
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# parse_transport_args(parser)
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# return parser
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if __name__ == "__main__":
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os.environ[
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"TORCH_DISTRIBUTED_DEBUG"] = "DETAIL" # set to DETAIL for runtime logging.
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# args = create_argparser().parse_args()
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# args.local_rank = int(os.environ["LOCAL_RANK"])
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# args.local_rank = 0
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# args.gpus = th.cuda.device_count()
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# args.rendering_kwargs = rendering_options_defaults(args)
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with open('configs/i23d_args.json') as f:
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args = json.load(f)
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args = EasyDict(args)
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# main(args)
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configs/i23d_args.json
ADDED
@@ -0,0 +1,284 @@
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{
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"image_size_encoder": 256,
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"triplane_scaling_divider": 0.96806,
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"diffusion_input_size": 32,
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"trainer_name": "flow_matching",
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"use_amp": true,
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"clip_denoised": false,
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"num_samples": 4,
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"num_instances": 10,
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"use_ddim": false,
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"ddpm_model_path": "",
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"cldm_model_path": "",
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"rec_model_path": "",
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"logdir": "./logs/LSGM/inference/Objaverse/i23d/dit-L2/",
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"data_dir": "NONE",
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"eval_data_dir": "/cpfs01/user/lanyushi.p/Repo/eccv24/open-source/InstantMesh/test_dir",
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"eval_batch_size": 1,
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"num_workers": 0,
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"overfitting": false,
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"image_size": 256,
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"iterations": 5000001,
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"schedule_sampler": "uniform",
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"anneal_lr": false,
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"lr": 2e-05,
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"weight_decay": 0.05,
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"lr_anneal_steps": 0,
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"batch_size": 1,
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"microbatch": 1,
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"ema_rate": "0.9999",
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"log_interval": 50,
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"eval_interval": 5000,
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"save_interval": 10000,
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"resume_checkpoint": "/nas/shared/V2V/yslan/logs/nips24/LSGM/t23d/FM/9cls/i23d/dit-L2-pixart-lognorm-rmsnorm-layernorm_before_pooled/gpu7-batch40-lr1e-4-bf16-qknorm-ctd3/model_joint_denoise_rec_model2990000.pt",
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"resume_cldm_checkpoint": "",
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"resume_checkpoint_EG3D": "",
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"use_fp16": false,
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"fp16_scale_growth": 0.001,
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"load_submodule_name": "",
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"ignore_resume_opt": false,
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"freeze_ae": false,
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"denoised_ae": true,
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"prompt": "a red chair",
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"interval": 5,
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"save_img": false,
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"use_train_trajectory": false,
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"unconditional_guidance_scale": 6.5,
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"use_eos_feature": false,
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"export_mesh": false,
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"cond_key": "img",
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"allow_tf32": true,
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"num_channels": 320,
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"num_res_blocks": 2,
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"num_heads": 8,
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"num_heads_upsample": -1,
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"num_head_channels": -1,
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"attention_resolutions": "4,2,1",
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"channel_mult": "",
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"dropout": 0.0,
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"class_cond": false,
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"use_checkpoint": false,
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"use_scale_shift_norm": true,
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"resblock_updown": false,
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"use_new_attention_order": false,
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"denoise_in_channels": 4,
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"denoise_out_channels": 4,
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"create_controlnet": false,
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"create_dit": true,
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"i23d": true,
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"create_unet_with_hint": false,
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"dit_model_arch": "DiT-PixArt-L/2",
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"use_spatial_transformer": true,
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"transformer_depth": 1,
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"context_dim": 1024,
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"pooling_ctx_dim": 768,
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"roll_out": true,
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"n_embed": null,
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"legacy": true,
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"mixing_logit_init": -6,
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"hint_channels": 3,
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"learn_sigma": false,
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"diffusion_steps": 1000,
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"noise_schedule": "linear",
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"standarization_xt": false,
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"timestep_respacing": "",
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"use_kl": false,
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"predict_xstart": false,
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"predict_v": true,
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"rescale_timesteps": false,
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"rescale_learned_sigmas": false,
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"mixed_prediction": false,
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"dino_version": "mv-sd-dit-dynaInp-trilatent",
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"encoder_in_channels": 10,
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"img_size": [
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256
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],
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"patch_size": 14,
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"in_chans": 384,
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"num_classes": 0,
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+
"embed_dim": 384,
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