Release Notes
24.8.0 - August 1st 2024
This is a major release containing many substantial changes from previous releases.
Major changes
- Changed versioning scheme to CalVer:
Year.Month.Micro
- Transitioned to more of a functional approach in SDK usage, allowing the user
to integrate the CLIKA Compression logic into existing code using
torch.compile
- Deploying models can now be done using a simple
torch.onnx.export
call. - Implemented CLIKA as a backend for
torch.compile
- Added initial support for Qualcomm's QNN. Please let us know if you encounter any issues!
Improvements
- Addition of improved model parsing capabilities
- ONNX export of
ClikaModule
now exports newer ops instead of resorting to the oldest version supported, if possible to do so
Bug fixes
- Fixed an issue with
FloorDivide
module in which the 'Floor' operation was not properly applied after deserialization of aClikaModule
.
Supported operations
Added support for more operations:
sort
, argsort
, topk
, masked_fill
, scatter_nd
, randint
,
unbind
, sym_int
, sym_float
, tensor_split
, amax
, amin
,
builtin.max
, builtin.min
, normalize
Please note that we generally add support for both torch.function_name
and
Tensor.function_name
but if you encounter a case where only one or the other
is supported, please let us know at support@clika.io
.
Future features
- Full Float16/BFloat16 training - the parameters will be in Float16/BFloat16. This will help reduce memory requirement.