<jupyter_start><jupyter_text>================================我是分隔線======================================
U^2-Net<jupyter_code># %cd drive/MyDrive/TibaMe/'Phantom Captcher'
# !git clone https://github.com/NathanUA/U-2-Net.git
# %cd /content/drive/MyDrive/TibaMe/'Phantom Captcher'/U-2-Net
!python /content/drive/MyDrive/TibaMe/'Phantom Captcher'/U-2-Net/u2net_train.py
# %cd /content/<jupyter_output>/usr/local/lib/python3.6/dist-packages/torch/nn/_reduction.py:44: UserWarning: size_average and reduce args will be deprecated, please use reduction='mean' instead.
  warnings.warn(warning.format(ret))
---
train images:  73145
train labels:  73145
---
---define optimizer...
---start training...
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2952: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
  warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3063: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode))
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:1639: UserWarning: nn.functio[...]<jupyter_text>新增區段<jupyter_code># %cd /content/drive/MyDrive/TibaMe/'Phantom Captcher'/U-2-Net
!python /content/drive/MyDrive/TibaMe/'Phantom Captcher'/U-2-Net/u2net_test.py
# %cd /content/<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.17874692874692874, 'fraction_numerical': 0.026412776412776413, 'mean_word_length': 5.217557251908397, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '159813', 'license': 'MIT', 'n_tokens_mistral': 602, 'n_tokens_neox': 566, 'n_words': 100, 'path': 'ipynb/U^2-Net_test.ipynb', 'repo_name': 'svwriting/PhantomCaptcher', 'size': '1628'}