{"push_id":1038527996,"size":1,"distinct_size":1,"ref":"refs/heads/infer_shape_conv_transp","head":"6185052fad308e5eb689faabe6ab9daa3a410563","before":"b58b0fc6897976c4df53606f32c20236aac63ac8","commits":[{"sha":"6185052fad308e5eb689faabe6ab9daa3a410563","author":{"email":"cfafa977d82ebd3f707b1efcb0c47f141af74ad1@iro.umontreal.ca","name":"David Warde-Farley"},"message":"ConvolutionalTranspose: infer original_image_size.\n\nTransposed (strided) convolution is a one-to-many mapping, with zero\npadding of border pixels dropped by the original convolution being\nreconstructed.\n\nIn the most common case, you want to produce an upsampled output image\nof which the transposed convolutional filter touches every pixel. This\nadds the automatic inference of the original_image_size with this case\nin mind. It also adds documentation on what constitutes a valid\noriginal_image_size for manual specification.","distinct":true,"url":"https://api.github.com/repos/dwf/blocks/commits/6185052fad308e5eb689faabe6ab9daa3a410563"}]}