* Add Llama 3.1 rope
* Clippy
* Format
* Clippy
* Add support for multiple eos tokens:
* Untagged either
* Remove either dep and fix settings.json
* Make the max positional embeddings configurable
* define structs
* construct ResidualConvUnit
* forward() for ResidualConvUnit
* implement FeatureFusionBlock
* implement Scratch
* implement DPTHead
* add identity module
* implement forward for DTPHead
* add get_intermediate_layers to DinoVisionTransformer
* implement DepthAnythingV2
* some minor tweaks
* fix compile errors
* fix var builder prefixes
* setup initial example
* use fixed patch size of 37 (518 / 14)
* debugged until output
* print min and max values
* add some dynamism to the output location
* scale input image
* extract prep function
* extract output path function
* normalize image with magic mean and std
* add spectral coloring
* squeeze in the right place
* make enterpolation optional
* use bail instead of panic
* omit unnecessary Shape call
* remove empty curly braces
* use bail instead of assert
* use vb and pp
* remove closures
* extract config object
* Apply rustfmt.
* Fix some clippy lints.
* More lints.
* Use the array methods.
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
* Add the layernorm cuda kernels.
* Dedicated layer norm op.
* Add the slower variant.
* Plug the cuda implementation.
* Add the metal variant.
* Add a dedicated test.
* Bugfix.
* Add a slice_set op.
* Add some testing.
* Add the dedicated kv-cache module.
* Derive debug and clone.
* Expose more kv-cache functions.
* Return the current data when appending.
* Use the new cache in the quantized phi3 model.
* When converting a tensor to a variable, clone if the tensor is already a variable.
* Add a test to ensure training a batch norm works with VarMaps
---------
Co-authored-by: Jeffrey Dallatezza <jeffreydallatezza@Jeffreys-Laptop.local>
* add sigmoid op
* small fix
* add as a method on `Tensor`
* implement gradient calculation for sigmoid
* add sigmoid tests
* we should have a specialized op for this
* fix clippy
* fix clippy 2
* Revert all previous commits in favor of a `CustomOp` based solution
* use `CustomOp1` implementation
* fix rustfmt
* experimental add metal impl
* add cuda kernel impl
* fix fmt
* Add a test + reduce some cuda duplication.
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
* Fast kernels for rotary embeddings.
* Add a test for the fast CPU kernel.
* Rope cuda bindings.
* Cuda kernel.
* Metal kernel (part 1).
* Cuda kernels.
* Finish the metal kernel.
* Use the new kernels in the quantized example.
* Fix warning.
* Trying out a custom RmsNorm cuda kernel.
* CPU implementation for rms-norm.
* Cuda wrappers.
* Add some validation.
* Add some testing.
* More testing.
* Add a specialized kernel for copy2d.
* Move the cat operations.
* Avoid transpositions in cat.
* Bugfix.
* Bugfix for the cuda kernel.
* Add a benchmark.
* Add more testing.
* Test fix.
* Faster kernel.
* Add the missing kernel.
* Tweak the test.
* Add a metal kernel.
* Fix for the metal kernel.
* Get the tests to pass on metal.
* Also use this opportunity to fix the metal kernel for ELU.
* Add some bf16 kernels.
* Clippy fixes.
* Improve metal buffer usage
* Clone cpu storage when loading to reduce wait_until_complete calls
* Use powers of two for buffer sizes so reuse is more likely.
* Select best available buffer by size.
* Add count to MetalStorage -> can use buffer with different size
Co-authored-by: Chris Fleetwood <christopher.fleetwood@huggingface.co>
* Simplify new buffer creation without blit copy. Revert &[] -> Vec
* Add documentation on newBufferWithBytes safety / synchronization
* Drop unused buffers after command buffer is done syncing.
---------
Co-authored-by: Chris Fleetwood <christopher.fleetwood@huggingface.co>
* Encodec model.
* Fixes.
* Add the padding functions.
* Get the LSTM bit to work.
* Get the encodec model to generate some tokens (decoder only for now).
* Minor tweak.
* Minor tweak.
`candle-nn` already exposes a trait to define custom backends. However,
it's not possible to actually construct a `VarBuilder` with a custom
backend because the constructor is not exposed.
This change makes the constructor public and renames it from `new` to
`from_backend` to avoid that it is seen as the primary
constructor (which could be confusing to users).
* Metal quantized modifications proposal.
- Add a device param, wherever needed.
- Create new QMetal storage thing that implements QuantizedType.
- Update everywhere needed.
Fix Python.
Fixing examples.
Fix: fmt + clippy + stub.
Moving everything around.
Only missing the actual implems.
Fixing everything + adding dequantized kernels.
More work.
Fixing matmul.
Fmt + Clippy
Some clippy fixes.
Working state.
Q2K Metal -> Bugged (also present in GGML).
Q4K CPU -> Bugged (present previously, new test catch it).
Q5K CPU -> Bugged (present previously).
Q8_1 Both -> Never really implemented it seems
Q8K metal -> Never implemented in metal
Fixing Q2K bug (present in ggml).
* Cleanup.
* Fix the rebase.
* Removing the fences speeds everything up and *is* correct this time...
* Cleanup the fence.
* After rebase.
* Bad code removal.
* Rebase after phi2 merge + fix replit default to CPU.
* Making the CI happy.
* More happy tests.
---------
Co-authored-by: Nicolas Patry <nicolas@Nicolass-MacBook-Pro.local>
* Update the Phi model to use the updated architecture.
* Add more of the phi model.
* Repeat KV + caching.
* Apply the rotary embeddings.
* Add support for the new phi model in the phi example.
* Fix a couple glitches.
* Fix a couple more glitches.
* add one-hot encoding
* one_hot: improve error handling, use generic to_vecN::<D>
Bails if the index value is equal to or greater than the depth value,
which would result in an out-of-bounds error.
A redundant check is added to ensure the index value does not exceed
the length of the one-hot matrix size, which would also result in an
out-of-bounds error.
Bails if the index value is less than -1. If the index value is -1,
then it ignores the setting of the on_value for the index value. Only
values that are less than -1 are considered errors.
* one-hot: use two generics, one_hot::<I, O>, for input and output data types
Separating the input and output data types allows the input tensor
indices to be a different data type than the output encoded tensor data type.
For example, one_hot::<i64, u8>(...) will take an input tensor of i64 values
and encode the output tensor using u8 values.
The generic I::DTYPE must match the data type of the input indices, otherwise
the method will bail.
Additionally, this method adds an `allow_f64` option to enable the input indices
data type to be f64 values. f64 values are disabled by default.
TODO: indices data type and the generic I data type are currently not compile-time
checked.
* one_hot: remove input generic, use indices dtype matching
This commit removes the to_f64() type cast and explicitly
matches the DType from the input tensor. Currently, only U8,
U32 and I64 is supported for input tensors.
The match arms on the dtype is verbose. It would be nice
to use a generic type with the WithDtype traitbound to
pass to the to_vecN method and then return an inner value.
Open to suggestions for better approaches here to reduce
the match arm verbosity.
* one_hot: use flat_map iterator over dims instead of nested for loop
This commit replaces the nested for loops with an flat map iter over
the dimensions of the input tensor.
This commit also adds a test for a rank 3 input tensor.
* one_hot: use mandatory on/off-values, remove const msgs
This commit also updates doc tests, comments and test cases.
* Small cleanups.
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
* Add training to batchnorm with exponential moving average
* Add more checks to batch norm
* Resolve some review comments
* Add with_momentum varients of `new` methods
* Add check for range of momentum variable; update batch norm test
* Run cargo fmt
* Add back num_features parameter
* Format; tiny simplification
