text-generation-inference/server/Makefile-flashinfer

install-flashinfer:
	# We need fsspec as an additional dependency, but
	# `pip install flashinfer` cannot resolve it.
	pip install fsspec sympy==1.13.1 numpy
	pip install -U setuptools
	FLASHINFER_ENABLE_AOT=1 pip install git+https://github.com/flashinfer-ai/flashinfer.git@v0.2.0.post1#egg=flashinfer  --no-build-isolation
Lots of improvements (Still 2 allocators) (#2449) * Making prefix/flashinfer the default and testing the full release tests. * Include flashinfer in the docker. * Using prebuilt. * Allowing window_left_size (dummy version). * Disabling flashinfer/prefix caching on odd head_dim * Disable prefix caching for lora. * More specific codes. * Update lock * Updating integration tests with new values with FI/FD. Remove paged as a default too, and using FD everywhere. * Update cargo lock ? * Upgrade to 1.80 because of bitstream... * Everywhere 1.80 * Forgot last default place. * Apply suggestions from code review Co-authored-by: drbh <david.richard.holtz@gmail.com> * Updated flake lock * Tmp * Upgrade resolution system for less errors in resolution. * Remove lambda for cleaner function. * Handling debugger. * OVerride the env in server tests. * Is this enough to make it work ? * This seems to be working. * Downgrade some logs. * Fixing the default for vlm. * Don't enable prefix caching on VLM just yet. * Change `add_special_tokens` in order to have the correct tokens for chat input and not (since it's super important with the prefixing now) * Fixing prefix caching for flashdecoding. * Update all models. * Fixed flashinfer version. * add_special_tokens is internal only * Fixing seqlen with the new vlms. * Fixing the issue with `add_special_tokens` not being passed around. * Fixing the test. * Removing encoder_decoder (seq2seq). * Update the chat test. * Fixing the batching tokenization in flash causal lm. * Truncating left for radix purposes. * Oops this doesn't belong here. * Put back default pure shell. * Update server tests - Default to throughput test in k6 - Use TGI_WIGGLE_ROOM to adjust wiggle room * Only n_heads / process_group.size() are necessary. * Revert the integrationt tests change (seem linked to head_size modification). * Adding error message when assert is violated. * Fixing the free algorithm to handle times where the common prefix is smaller. * Apply suggestions from code review Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Update server/text_generation_server/layers/attention/common.py Co-authored-by: OlivierDehaene <olivier@huggingface.co> * Fix disabling prefix caching - Fix windowing checks. * Revert the Cohere tokenizer change (for now using a revision instead). * Fmt. --------- Co-authored-by: drbh <david.richard.holtz@gmail.com> Co-authored-by: OlivierDehaene <olivier@huggingface.co> 2024-08-29 14:29:01 +00:00			`install-flashinfer:`
Basic flashinfer 0.2 support (#2862) * Basic flashinfer 0.2 support This change does not use any of the new features yet, but makes some small compatibility changes. * Update to flashinfer 0.2.0.post1 * flashinfer: remove `contiguous` calls * Fix flashinfer install * flashinfer: fixup kv cache dtype * Fix some annoying perturbations * More output changes 2025-01-09 15:25:00 +00:00			`# We need fsspec as an additional dependency, but`
			# `pip install flashinfer` cannot resolve it.
Tmp tp transformers (#2942) * Upgrade the version number. * Remove modifications in Lock. * Tmp branch to test transformers backend with 2.5.1 and TP>1 * Fixing the transformers backend. inference_mode forces the use of `aten.matmul` instead of `aten.mm` the former doesn't have sharding support crashing the transformers TP support. `lm_head.forward` also crashes because it skips the hook that cast/decast the DTensor. Torch 2.5.1 is required for sharding support. * Put back the attention impl. * Revert the flashinfer (this will fails). * Building AOT. * Using 2.5 kernels. * Remove the archlist, it's defined in the docker anyway. 2025-01-23 17:07:30 +00:00			`pip install fsspec sympy==1.13.1 numpy`
			`pip install -U setuptools`
			`FLASHINFER_ENABLE_AOT=1 pip install git+https://github.com/flashinfer-ai/flashinfer.git@v0.2.0.post1#egg=flashinfer --no-build-isolation`