* Add stable diffusion 3 example
Add get_qkv_linear to handle different dimensionality in linears
Add stable diffusion 3 example
Add use_quant_conv and use_post_quant_conv for vae in stable diffusion
adapt existing AutoEncoderKLConfig to the change
add forward_until_encoder_layer to ClipTextTransformer
rename sd3 config to sd3_medium in mmdit; minor clean-up
Enable flash-attn for mmdit impl when the feature is enabled.
Add sd3 example codebase
add document
crediting references
pass the cargo fmt test
pass the clippy test
* fix typos
* expose cfg_scale and time_shift as options
* Replace the sample image with JPG version. Change image output format accordingly.
* make meaningful error messages
* remove the tail-end assignment in sd3_vae_vb_rename
* remove the CUDA requirement
* use default_value in clap args
* add use_flash_attn to turn on/off flash-attn for MMDiT at runtime
* resolve clippy errors and warnings
* use default_value_t
* Pin the web-sys dependency.
* Clippy fix.
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Co-authored-by: Laurent <laurent.mazare@gmail.com>
* Add the mimi audio-tokenizer.
* Formatting tweaks.
* Add a full example.
* Use the transformers names.
* More renamings.
* Get encoding and decoding to work.
* Clippy fixes.
* silero-vad v5 example
This change adds an example of how to run silero-vad v5
* PR: rename 'vad' to 'silero-vad'
* Update README.md
---------
Co-authored-by: Laurent Mazare <laurent.mazare@gmail.com>
* 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>
* feat: support microphone whisper streaming
* fix: cleanup print stmts and adjust how input is read
* fix: remove incorrect comment
* feat: split into new example and simplify
* fix: feature flag example file
* fix: fmt fixes
* feat: simplify and remove redundant files
* Supports more audio formats
* Simplify the handling of the different buffer types.
* Check the sample rate.
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
Few fixes.
Going back on remote metal-rs.
Reusing a single buffer (for now) to speed things up.
Adding some half kernels.
All tests are panicking instead of random failure.
Putting back f16 index select.
Add erf.
Working version for llama2-c.
Fixes + cache compute_pipeline_state.
BF16 metal fix.
Remove some prints.
new_owned -> new()..to_owned().
Better batched matmul.
Metal operational.
Reuse buffers on our own reference counts.
Tmp gemm.
Revert "Tmp gemm."
This reverts commit c65f68e988.
Interleave committing.
Speeding up copies using blit.
Fmt.
Fmt.
Remove the assert!
Fmt all.
Fixes after big rebase.
Add softmax for half and bfloat + tests
Fixing Llama example + accumulate softmax in float.
* Support the shape op in ONNX.
* Share the axis normalization bits.
* Add some limited support for gather.
* Unsqueeze.
* Comparison with broadcasting.
* Add Not + handle i32.
* Negative and `*args` shape handling
* Rename to `PyShapeWithHole` + validate that only one hole exists
* Regenerate stubs
---------
Co-authored-by: Laurent Mazare <laurent.mazare@gmail.com>
* Add some reinforcement learning example.
* Python initialization.
* Get the example to run.
* Vectorized gym envs for the atari wrappers.
* Get some simulation loop to run.
* Add some group parameter to convolutions.
* Avoid some unnecessary groups checks.
* Move the tensor convolution bits.
* Properh handling of groups.
* Bump the crate version.
* And add a changelog.
* Add a cudnn feature to be used for conv2d.
* Allocate the proper workspace.
* Only create a single cudnn handle per cuda device.
* Proper cudnn usage.
* Bugfix.
Laurent Mazare