* torch and numpy don't share ops anymore
* that should be filtered out elsewhere
* still const
* graph + enet example cleanup
* hmm, we do still need it because of symbolic
* add name support
* use fetch in gpt2
* remove requests from main lib, networkx also optional
* umm, keep that assert
* updates to fetch
* i love the walrus so much
* stop bundling mnist with tinygrad
* err, https
* download cache names
* add DOWNLOAD_CACHE_VERSION
* need env.
* ugh, wrong path
* replace get_child
* fixed hf convert and now it's working with tinyllama
* added tinyllama config
* refactored code and made it work with all llama models
* prettier order
* prettier order
* fixed suffix for tinyllama and refactored convert_from_hf
* dynamically update help if MODEL_PARAMS changes and default size is the 1st
* beautiful mnist
* beautiful mnist example
* from tinygrad import Tensor
* more beautiful
* the jit is super core tinygrad
* globalcounters reset on jit run
* symlinks and exclude
* beautiful_cartpole
* evaluate is it's own function
* no symlinks
* more beautiful
* jit reset for double speed
* type hinting for JIT
* beautiful_mnist gets 98%
* beautiful_mnist < 4s with BEAM=2
* better cartpole
* use actor critic
* zero_grad got lost
* delete double relu
* stable cartpole with PPO
* beautiful_cartpole is more beautiful
* REPLAY_BUFFER
* beautiful stuff typechecks
* None support in shape
* hp tuning
* var_vals are global
* working with global ish
* better
* fix export model
* fix tests
* better kv cache
* does it run?
* use where for kvmask
* fix excessive var_vals
* fix import
* how does multigpu use this?
* llama kinda work
* faster and simpler
* cleanup
* fix conversation mode
* test cleanups
* fix one more test
* test cleanup
---------
Co-authored-by: George Hotz <geohot@gmail.com>
* WIP: Stable diffusion WebGPU port
* Load whole model: split safetensor to avoid Chrome allocation limit
* Gitignore .DS_Store, remove debug print
* Clip tokenizer in JS
* WIP: Compile model in parts (text model, diffusor, get_x_prev_and_pred_x0, decoder), and recreate forward logic in JS
* e2e stable diffusion flow
* Create initial random latent tensor in JS
* SD working e2e
* Log if some weights were not loaded properly
* Remove latent_tensor.npy used for debugging
* Cleanup, remove useless logs
* Improve UI
* Add progress bar
* Remove .npy files used for debugging
* Add clip tokenizer as external dependency
* Remove alphas_cumprod.js and load it from safetensors
* Refactor
* Simplify a lot
* Dedup base when limiting elementwise merge (webgpu)
* Add return type to safe_load_metadata
* Do not allow run when webgpu is not supported
* Add progress bar, refactor, fix special names
* Add option to chose from local vs huggingface weights
* lowercase tinygrad :)
* fp16 model dl, decompression client side
* Cache f16 model in browser, better progress
* Cache miss recovery
---------
Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
* merge kernel and optimizer
* linearize is reentrant
* move global/local size
* clean up linearizer copy
* remove unneeded lin copies
* stop linearizing twice
* oops, that should be None
* Enable Multi-Output Export
* Add test
* Update examples and lint
* fix padding
* test ops
* dummy commit to rerun test
* revert cuda lint
* Enforce tuple/list of tensors
* subscripted generics
* put back webgpu test
* Re-enable WebGPU Efficientnet test
* stable diffusion < 324ms
* revert swap action
* fix tests due to more sum splitting
* REDUCEOP_SPLIT_THRESHOLD env var
* added from unaligned np test (#2134)
* align cpu buffer before copy into cl buffer (#2135)
* remove shelve from handcode_resnet50_opt.py (#2139)
* Add dictionary keys to reduce db size (#2131)
* work
* ignore beam cache
* dictionary keys are generic
* minor db cleanups
* fix baseline and extract dataset
* fix training
* log likelihood
* more lin to feats
* sts
* training policynet
* net sort of works
* dedup
* refactor, stupid new actions
* fix uops deduping
* BEAM_ESTIMATE
---------
Co-authored-by: chenyu <chenyu@fastmail.com>
Co-authored-by: imaolo <56898718+imaolo@users.noreply.github.com>
* feat: move to hip
* feat: special path for RawBufferTransfer
* feat: initial rawbuffertransfer
* feat: hip ipc
* feat: working hip ipc
* feat: need to base device without args
* feat: close mem handle
* feat: modified test
* feat: more multihip stuff
* clean: cleanup
* feat: cleaner
* feat: don't crash
* feat: test more
* clean: way cleaner hip wrapper
* feat: barrier
* feat: barrier
* feat: this breaks stuff
* feat: we can use empty here
* feat: maybe fix tests
* feat: maybe fix tests again?
* fix: probably fix tests
* feat: no waiting here
* feat: wait here
* feat: much larger test
* feat: need to sync here
* feat: make this async
* feat: no waiting!
* feat: cut here
* feat: sync copy
* feat: random imports
* feat: much cleaner world
* feat: restore this
* feat: restore this
* clean: cleanup
* feat: set this
* create cache for q learning
* make linter happy
* global beam
* where it belongs
* bugfix
* ditch the kopt, use the beam
* faster lin and DEBUG=2 okay
* remove kopt, move search to features
George Hotz
Davi Silva
Francis Lata
George Hotz
mmmkkaaayy
Oleg Rybalko
chenyu
Friedrich Carl Eichenroth
wozeparrot
Ahmed Harmouche
Akshay Kashyap
will
nimlgen
20kdc
Sean D'Souza