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fixing nn docs to be categorized, and optim docs
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@soumith
soumith committed Nov 18, 2016
1 parent dee8641 commit 7a837b7
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4 changes: 2 additions & 2 deletions docs/docutils/doc2md.py
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Original file line number Diff line number Diff line change
Expand Up @@ -392,7 +392,7 @@ def reset():
_doc2md.code += _doc2md.md
return _doc2md.code

def doc2md(docstr, title, min_level=1, more_info=False, toc=True):
def doc2md(docstr, title, min_level=3, more_info=False, toc=True):
"""
Convert a docstring to a markdown text.
"""
Expand Down Expand Up @@ -444,7 +444,7 @@ def mod2md(module, title, title_api_section, toc=True):
api_sec = []
if title_api_section :
# sections.append((level+1, title_api_section))
for name, entry in iter(sorted(module.__dict__.items())):
for name, entry in iter(module.__dict__.items()):
if name[0] != '_' and entry.__doc__:
#api_sec.append((level+1, name))
#api_md += ['', '']
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96 changes: 95 additions & 1 deletion docs/docutils/gendocs.sh
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@@ -1,6 +1,100 @@
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
pushd $SCRIPT_DIR

python doc2md.py torch.nn --no-toc --all >../nn.md
# module
#python doc2md.py torch.nn Module --title Module --no-toc >../nn_module.md

# containers
echo "## Containers" > ../nn_container.md
python doc2md.py torch.nn Container --title Container --no-toc >>../nn_container.md
python doc2md.py torch.nn Sequential --title Sequential --no-toc >>../nn_container.md

# convolution
echo "## Convolution Layers" > ../nn_convolution.md
echo Conv1d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_convolution.md
echo Conv2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_convolution.md
echo ConvTranspose2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_convolution.md
echo Conv3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_convolution.md
echo ConvTranspose3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_convolution.md

# pooling
echo "## Pooling Layers" > ../nn_pooling.md
echo MaxPool1d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo MaxPool2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo MaxPool3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo MaxUnpool2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo MaxUnpool3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo AvgPool2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo AvgPool3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo FractionalMaxPool2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md
echo LPPool2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_pooling.md

# activations
echo "## Non-linearities" > ../nn_activation.md
echo ReLU | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo ReLU6 | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Threshold | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Hardtanh | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Sigmoid | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Tanh | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo ELU | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo LeakyReLU | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo LogSigmoid | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Softplus | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Softshrink | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo PReLU | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Softsign | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Tanhshrink | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Softmin | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Softmax | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo Softmax2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md
echo LogSoftmax | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_activation.md

# normalization
echo "## Normalization layers" > ../nn_normalization.md
echo BatchNorm1d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_normalization.md
echo BatchNorm2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_normalization.md
echo BatchNorm3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_normalization.md

# recurrentnet
echo "## Recurrent layers" > ../nn_recurrent.md
echo RNN | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_recurrent.md
echo LSTM | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_recurrent.md
echo GRU | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_recurrent.md
echo RNNCell | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_recurrent.md
echo LSTMCell | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_recurrent.md
echo GRUCell | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_recurrent.md

# linear
echo "## Linear layers" > ../nn_linear.md
echo Linear | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_linear.md

# dropout
echo "## Dropout layers" > ../nn_dropout.md
echo Dropout | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_dropout.md
echo Dropout2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_dropout.md
echo Dropout3d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_dropout.md

# Sparse
echo "## Sparse layers" > ../nn_sparse.md
echo Embedding | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_sparse.md

# loss_functions
echo "## Loss functions" > ../nn_loss.md
echo L1Loss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo MSELoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo CrossEntropyLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo NLLLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo NLLLoss2d | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo KLDivLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo BCELoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo MarginRankingLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo HingeEmbeddingLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo MultiLabelMarginLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo SmoothL1Loss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo SoftMarginLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo MultiLabelSoftMarginLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo CosineEmbeddingLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md
echo MultiMarginLoss | xargs -I {} python doc2md.py torch.nn {} --title {} --no-toc >>../nn_loss.md

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