* module docs
* varbuilder gguf docs
* add a link to gguf files
* small additonal mod doc titles
* safetensor docs
* more core docs
* more module docs in canlde_core
* 2 more link fixes
* Add gradient test for conv_transpose2d with stride of 2.
* Swap dilation and stride in ConvTranspose2D backpropagation.
Without this, a shape mismatch occurs with a stride of 2 and dilation of 1.
* Add further tests of the ConvTranspose2D gradient.
Values calculated with torch, minor numerical errors adjusted and commented.
* add the sign unary operator
* remove uneeded import
* remove uneeded import
* undo formatting
* undo formatting
* remove unnecessary redefintion
* allow gradient to flow through for sign and round
* fix cpu ops to ensure that negzero and positive zero are handled properly
* clippy fixes
* Properly avoid gradient tracking.
* Use a branchless version.
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Co-authored-by: laurent <laurent.mazare@gmail.com>
* encode size of upsample in enum
* working convolution method for limited 2d kernels
* add test for sf 3 interpolation
* add higher dimensional tests, fix to work with multichannel input
* Remove commented out line.
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Co-authored-by: Laurent <laurent.mazare@gmail.com>
* Add the dilation parameter.
* Restore the basic optimizer example.
* Dilation support in cudnn.
* Use the dilation parameter in the cpu backend.
* More dilation support.
* No support for dilation in transposed convolutions.
* Add dilation to a test.
* Remove a print.
* Helper function.
* Add conv-transpose.
* Return zeros for now.
* Naive CPU implementation.
* Add a conv-transpose test + fix the cpu implementation.
* Add a second test.
* Add a couple functions required for yolo.
* Add the yolo-v3 example.
* Add minimum and maximum.
* Use the newly introduced maximum.
* Cuda support for min/max + add some testing.
* Allow for more tests to work with accelerate.
* Fix a typo.
* Add the copy op.
* Tweak some cat error messages.
* Handle the contiguous case in to_vec1.
* Fast variant for to_vec2.
* Add add a faster to_vec3 variant.
* Start adding gather.
* Gather cpu implementation + use in simple training.
* Add scatter_add for the gradient of gather.
* Simple cpu implementation of scatter_add.
* Use gather in the simple-training backprop.
