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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,4 +1,4 @@ | ||
| # Sphinx build info version 1 | ||
| # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
| config: 48d0245515a1ca80bc37c0931e40c20f | ||
| config: 84bc96467903e48216c9956d05985a38 | ||
| tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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docs/build/html/_downloads/79dff157bfbc0773edb46ea14b42e885/demo_config_single_run_diva.yaml
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| --- # yaml demo document | ||
|
|
||
| te_d: caltech | ||
| tpath: examples/tasks/task_vlcs.py | ||
| bs: 2 | ||
| model: diva | ||
| debug: True | ||
| gamma_y: 700000.0 #7e5 | ||
| gamma_d: 100000.0 #1e5 | ||
| nname: alexnet | ||
| nname_dom: conv_bn_pool_2 |
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docs/build/html/_downloads/adcf8c984b69173567c65fba4c00b880/task_vlcs.py
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|---|---|---|
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| import os | ||
| from torchvision import transforms | ||
| from domainlab.tasks.task_folder_mk import mk_task_folder | ||
| from domainlab.tasks.utils_task import ImSize | ||
|
|
||
| # relative path is essential here since this file is used for testing, no absolute directory possible | ||
|
|
||
| path_this_file = os.path.dirname(os.path.realpath(__file__)) | ||
| chain = mk_task_folder(extensions={"caltech": "jpg", "sun": | ||
| "jpg", "labelme": "jpg"}, | ||
| list_str_y=["chair", "car"], | ||
| dict_domain_folder_name2class={ | ||
| "caltech": {"auto": "car", "stuhl": "chair"}, | ||
| "sun": {"vehicle": "car", "sofa": "chair"}, | ||
| "labelme": {"drive": "car", "sit": "chair"} | ||
| }, | ||
| dict_domain_img_trans={ | ||
| "caltech": transforms.Compose( | ||
| [transforms.Resize((256, 256)), | ||
| transforms.CenterCrop(224), | ||
| transforms.ToTensor(), | ||
| transforms.Normalize( | ||
| [0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) | ||
| ]), | ||
| "sun": transforms.Compose( | ||
| [transforms.Resize((256, 256)), | ||
| transforms.CenterCrop(224), | ||
| transforms.ToTensor(), | ||
| transforms.Normalize( | ||
| [0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) | ||
| ]), | ||
| "labelme": transforms.Compose( | ||
| [transforms.Resize((256, 256)), | ||
| transforms.CenterCrop(224), | ||
| transforms.ToTensor(), | ||
| transforms.Normalize( | ||
| [0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) | ||
| ]), | ||
| }, | ||
| img_trans_te=transforms.Compose( | ||
| [transforms.Resize((256, 256)), | ||
| transforms.CenterCrop(224), | ||
| transforms.ToTensor(), | ||
| transforms.Normalize( | ||
| [0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]), | ||
| isize=ImSize(3, 224, 224), | ||
| dict_domain2imgroot={ | ||
| "caltech": os.path.join( | ||
| path_this_file, | ||
| "../../data/vlcs_mini/caltech/"), | ||
| "sun": os.path.join( | ||
| path_this_file, | ||
| "../../data/vlcs_mini/sun/"), | ||
| "labelme": os.path.join( | ||
| path_this_file, | ||
| "../../data/vlcs_mini/labelme/")}, | ||
| taskna="e_mini_vlcs") | ||
|
|
||
|
|
||
| def get_task(na=None): | ||
| return chain |
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