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1 Parent(s): 20ddbb6

ckpt

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  1. __pycache__/sde.cpython-310.pyc +0 -0
  2. __pycache__/utils.cpython-310.pyc +0 -0
  3. app.py +5 -2
  4. configs/__pycache__/t2i_512px_clip_dimr.cpython-310.pyc +0 -0
  5. diffusion/__pycache__/base_solver.cpython-310.pyc +0 -0
  6. diffusion/__pycache__/flow_matching.cpython-310.pyc +0 -0
  7. libs/__pycache__/__init__.cpython-310.pyc +0 -0
  8. libs/__pycache__/autoencoder.cpython-310.pyc +0 -0
  9. libs/__pycache__/clip.cpython-310.pyc +0 -0
  10. libs/model/__pycache__/axial_rope.cpython-310.pyc +0 -0
  11. libs/model/__pycache__/common_layers.cpython-310.pyc +0 -0
  12. libs/model/__pycache__/dimr_t2i.cpython-310.pyc +0 -0
  13. libs/model/__pycache__/flags.cpython-310.pyc +0 -0
  14. libs/model/__pycache__/trans_autoencoder.cpython-310.pyc +0 -0
  15. libs/model/sigmoid/__pycache__/kernel.cpython-310.pyc +0 -0
  16. libs/model/sigmoid/__pycache__/module.cpython-310.pyc +0 -0
__pycache__/sde.cpython-310.pyc ADDED
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__pycache__/utils.cpython-310.pyc ADDED
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app.py CHANGED
@@ -16,6 +16,7 @@ import numpy as np
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  import torch
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  import torch.nn.functional as F
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  from torchvision.utils import save_image
 
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  from absl import logging
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  import ml_collections
@@ -104,10 +105,12 @@ MAX_SEED = np.iinfo(np.int32).max
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  MAX_IMAGE_SIZE = 1024 # Currently not used.
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  # Load the main diffusion model.
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- nnet_path = os.path.join("..", "..", "ckpt", "released_model", "t2i_512px_clip_dimr.pth")
 
 
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  nnet = utils.get_nnet(**config.nnet)
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  nnet = nnet.to(device)
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- state_dict = torch.load(nnet_path, map_location=device)
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  nnet.load_state_dict(state_dict)
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  nnet.eval()
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  import torch
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  import torch.nn.functional as F
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  from torchvision.utils import save_image
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+ from huggingface_hub import hf_hub_download
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  from absl import logging
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  import ml_collections
 
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  MAX_IMAGE_SIZE = 1024 # Currently not used.
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  # Load the main diffusion model.
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+ repo_id = "QHL067/CrossFlow"
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+ filename = "pretrained_models/t2i_512px_clip_dimr.pth"
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+ checkpoint_path = hf_hub_download(repo_id=repo_id, filename=filename)
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  nnet = utils.get_nnet(**config.nnet)
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  nnet = nnet.to(device)
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+ state_dict = torch.load(checkpoint_path, map_location=device)
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  nnet.load_state_dict(state_dict)
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  nnet.eval()
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configs/__pycache__/t2i_512px_clip_dimr.cpython-310.pyc ADDED
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diffusion/__pycache__/base_solver.cpython-310.pyc ADDED
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diffusion/__pycache__/flow_matching.cpython-310.pyc ADDED
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libs/__pycache__/__init__.cpython-310.pyc ADDED
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libs/__pycache__/autoencoder.cpython-310.pyc ADDED
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libs/__pycache__/clip.cpython-310.pyc ADDED
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libs/model/__pycache__/axial_rope.cpython-310.pyc ADDED
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libs/model/__pycache__/common_layers.cpython-310.pyc ADDED
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libs/model/__pycache__/dimr_t2i.cpython-310.pyc ADDED
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libs/model/__pycache__/flags.cpython-310.pyc ADDED
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libs/model/__pycache__/trans_autoencoder.cpython-310.pyc ADDED
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libs/model/sigmoid/__pycache__/kernel.cpython-310.pyc ADDED
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libs/model/sigmoid/__pycache__/module.cpython-310.pyc ADDED
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