提交 5f50150f authored 作者: Nicolas Ballas's avatar Nicolas Ballas

Update doc, correct link format

上级 efbbd807
......@@ -124,7 +124,7 @@ TODO: Give examples on how to use these things! They are pretty complicated.
- :func:`GpuCorr3dMM <theano.sandbox.cuda.blas.GpuCorr3dMM>`
This is a GPU-only 3d correlation relying on a Toeplitz matrix
and gemm implementation (see `GpuCorrMM <theano.sandbox.cuda.blas.GpuCorrMM>`)
and gemm implementation (see :func:`GpuCorrMM <theano.sandbox.cuda.blas.GpuCorrMM>`)
It needs extra memory for the Toeplitz matrix, which is a 2D matrix of shape
``(no of channels * filter width * filter height * filter depth, output width * output height * output depth)``.
As it provides a gradient, you can use it as a replacement for nnet.conv3d.
......@@ -135,7 +135,7 @@ TODO: Give examples on how to use these things! They are pretty complicated.
overhead is small compared to conv3d_fft, there are no restrictions on
input or kernel shapes and strides are supported. If using it,
please see the warning about a bug in CUDA 5.0 to 6.0
in `GpuCorrMM <theano.sandbox.cuda.blas.GpuCorrMM>`.
in :func:`GpuCorrMM <theano.sandbox.cuda.blas.GpuCorrMM>`.
- :func:`conv3d2d <theano.tensor.nnet.conv3d2d.conv3d>`
Another conv3d implementation that uses the conv2d with data reshaping.
......
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