From b9633c46d0b64e4c3d52e2e29746abdbfd339dbe Mon Sep 17 00:00:00 2001 From: Jae-Won Chung Date: Mon, 31 Jul 2023 08:35:14 -0400 Subject: [PATCH 01/18] Fix typing in `Model.generate_token` (#733) ## What does this PR do? This PR fixes a minor type annotation issue in the signature of `Model.generate_token`. All existing overrides of `Model.generate_token` return `Tuple[List[Generation], Optional[B]]`: https://github.com/huggingface/text-generation-inference/blob/3ef5ffbc6400370ff2e1546550a6bad3ac61b079/server/text_generation_server/models/causal_lm.py#L535-L537 https://github.com/huggingface/text-generation-inference/blob/3ef5ffbc6400370ff2e1546550a6bad3ac61b079/server/text_generation_server/models/flash_causal_lm.py#L802-L804 https://github.com/huggingface/text-generation-inference/blob/3ef5ffbc6400370ff2e1546550a6bad3ac61b079/server/text_generation_server/models/seq2seq_lm.py#L589-L591 I suspect that back in 017a2a8c when `GeneratedText` and `Generation` were separated, the function signature was not updated. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? CC @OlivierDehaene --- server/text_generation_server/models/model.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/server/text_generation_server/models/model.py b/server/text_generation_server/models/model.py index 9d74247c..806e9833 100644 --- a/server/text_generation_server/models/model.py +++ b/server/text_generation_server/models/model.py @@ -5,7 +5,7 @@ from abc import ABC, abstractmethod from typing import List, Tuple, Optional, TypeVar, Type from transformers import PreTrainedTokenizerBase, PretrainedConfig -from text_generation_server.models.types import Batch, GeneratedText +from text_generation_server.models.types import Batch, Generation from text_generation_server.pb.generate_pb2 import InfoResponse B = TypeVar("B", bound=Batch) @@ -52,7 +52,7 @@ class Model(ABC): raise NotImplementedError @abstractmethod - def generate_token(self, batch: B) -> Tuple[List[GeneratedText], Optional[B]]: + def generate_token(self, batch: B) -> Tuple[List[Generation], Optional[B]]: raise NotImplementedError def warmup(self, batch: B) -> Optional[int]: From 932bdd93ff559702cd51f07311c78cf389ec0542 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Mon, 31 Jul 2023 15:38:47 +0200 Subject: [PATCH 02/18] Adding Rope scaling. (#741) # What does this PR do? - Adds Rope NTK scaling. Done because https://github.com/huggingface/text-generation-inference/pull/529 was closed Took some code from https://github.com/huggingface/transformers/pull/24653 - `--rope-scaling` and `--rope-factor` are added separately. I considered having a single one and parsing something line ("linear:4.0" , or "dynamic") but decided against it because it would push more parsing+validation a bit everywhere (both in the launcher and the server). Fixes #512 Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- launcher/src/main.rs | 61 +++++++++++++ .../custom_modeling/flash_llama_modeling.py | 2 +- .../custom_modeling/flash_neox_modeling.py | 2 +- .../custom_modeling/flash_rw_modeling.py | 4 +- server/text_generation_server/utils/layers.py | 88 ++++++++++++++++--- 5 files changed, 142 insertions(+), 15 deletions(-) diff --git a/launcher/src/main.rs b/launcher/src/main.rs index 2ad788a4..560ce181 100644 --- a/launcher/src/main.rs +++ b/launcher/src/main.rs @@ -60,6 +60,26 @@ impl std::fmt::Display for Dtype { } } +#[derive(Clone, Copy, Debug, ValueEnum)] +enum RopeScaling { + Linear, + Dynamic, +} + +impl std::fmt::Display for RopeScaling { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + // To keep in track with `server`. + match self { + RopeScaling::Linear => { + write!(f, "linear") + } + RopeScaling::Dynamic => { + write!(f, "dynamic") + } + } + } +} + /// App Configuration #[derive(Parser, Debug)] #[clap(author, version, about, long_about = None)] @@ -250,6 +270,26 @@ struct Args { #[clap(default_value = "1.0", long, env)] cuda_memory_fraction: f32, + /// Rope scaling will only be used for RoPE models + /// and allow rescaling the position rotary to accomodate for + /// larger prompts. + /// + /// Goes together with `rope_factor`. + /// + /// `--rope-factor 2.0` gives linear scaling with a factor of 2.0 + /// `--rope-scaling dynamic` gives dynamic scaling with a factor of 1.0 + /// `--rope-scaling linear` gives linear scaling with a factor of 1.0 (Nothing will be changed + /// basically) + /// + /// `--rope-scaling linear --rope-factor` fully describes the scaling you want + #[clap(long, env)] + rope_scaling: Option, + + /// Rope scaling will only be used for RoPE models + /// See `rope_scaling` + #[clap(long, env)] + rope_factor: Option, + /// Outputs the logs in JSON format (useful for telemetry) #[clap(long, env)] json_output: bool, @@ -305,6 +345,8 @@ fn shard_manager( watermark_gamma: Option, watermark_delta: Option, cuda_memory_fraction: f32, + rope_scaling: Option, + rope_factor: Option, otlp_endpoint: Option, status_sender: mpsc::Sender, shutdown: Arc, @@ -358,6 +400,12 @@ fn shard_manager( shard_args.push(revision) } + let rope = match (rope_scaling, rope_factor) { + (None, None) => None, + (Some(scaling), None) => Some((scaling, 1.0)), + (Some(scaling), Some(factor)) => Some((scaling, factor)), + (None, Some(factor)) => Some((RopeScaling::Linear, factor)), + }; // OpenTelemetry if let Some(otlp_endpoint) = otlp_endpoint { shard_args.push("--otlp-endpoint".to_string()); @@ -395,6 +443,15 @@ fn shard_manager( envs.push(("HUGGING_FACE_HUB_TOKEN".into(), api_token.into())) }; + // Detect rope scaling + // Sending as env instead of CLI args to not bloat everything + // those only can be used by RoPE models, so passing information around + // for all models will complexify code unnecessarily + if let Some((scaling, factor)) = rope { + envs.push(("ROPE_SCALING".into(), scaling.to_string().into())); + envs.push(("ROPE_FACTOR".into(), factor.to_string().into())); + } + // If huggingface_hub_cache is some, pass it to the shard // Useful when running inside a docker container if let Some(huggingface_hub_cache) = huggingface_hub_cache { @@ -784,6 +841,8 @@ fn spawn_shards( let watermark_gamma = args.watermark_gamma; let watermark_delta = args.watermark_delta; let cuda_memory_fraction = args.cuda_memory_fraction; + let rope_scaling = args.rope_scaling; + let rope_factor = args.rope_factor; thread::spawn(move || { shard_manager( model_id, @@ -802,6 +861,8 @@ fn spawn_shards( watermark_gamma, watermark_delta, cuda_memory_fraction, + rope_scaling, + rope_factor, otlp_endpoint, status_sender, shutdown, diff --git a/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py b/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py index b6285856..2c22ea46 100644 --- a/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py +++ b/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py @@ -186,7 +186,7 @@ class FlashLlamaAttention(torch.nn.Module): self.head_size = self.hidden_size // self.num_heads self.rotary_emb = PositionRotaryEmbedding.load( - prefix=f"{prefix}.rotary_emb", weights=weights + config=config, prefix=f"{prefix}.rotary_emb", weights=weights ) self.softmax_scale = self.head_size**-0.5 diff --git a/server/text_generation_server/models/custom_modeling/flash_neox_modeling.py b/server/text_generation_server/models/custom_modeling/flash_neox_modeling.py index e7c8ced4..9dc374df 100644 --- a/server/text_generation_server/models/custom_modeling/flash_neox_modeling.py +++ b/server/text_generation_server/models/custom_modeling/flash_neox_modeling.py @@ -102,7 +102,7 @@ class FlashNeoxAttention(torch.nn.Module): self.num_heads = self.num_heads // weights.process_group.size() self.rotary_emb = PositionRotaryEmbedding.load( - prefix=f"{prefix}.rotary_emb", weights=weights + config=config, prefix=f"{prefix}.rotary_emb", weights=weights ) self.softmax_scale = self.head_size ** (-0.5) diff --git a/server/text_generation_server/models/custom_modeling/flash_rw_modeling.py b/server/text_generation_server/models/custom_modeling/flash_rw_modeling.py index 3570b283..14caa23d 100644 --- a/server/text_generation_server/models/custom_modeling/flash_rw_modeling.py +++ b/server/text_generation_server/models/custom_modeling/flash_rw_modeling.py @@ -133,7 +133,7 @@ class FlashRWAttention(torch.nn.Module): self.head_size = self.hidden_size // self.num_heads self.rotary_emb = PositionRotaryEmbedding.static( - dim=self.head_size, base=10000.0, device=weights.device + config=config, dim=self.head_size, base=10000.0, device=weights.device ) self.softmax_scale = self.head_size ** (-0.5) @@ -247,7 +247,7 @@ class FlashRWLargeAttention(torch.nn.Module): self.head_size = hidden_size // num_heads self.rotary_emb = PositionRotaryEmbedding.static( - self.head_size, base=10000.0, device=weights.device + config=config, dim=self.head_size, base=10000.0, device=weights.device ) self.softmax_scale = self.head_size ** (-0.5) diff --git a/server/text_generation_server/utils/layers.py b/server/text_generation_server/utils/layers.py index 183cf2c1..fc92ebe6 100644 --- a/server/text_generation_server/utils/layers.py +++ b/server/text_generation_server/utils/layers.py @@ -381,33 +381,65 @@ try: from flash_attn.layers.rotary import RotaryEmbedding import rotary_emb - class PositionRotaryEmbedding(nn.Module): - def __init__(self, inv_freq): - super().__init__() + def _create_inv_freq(dim, base, device): + inv_freq = 1.0 / ( + base + ** (torch.arange(0, dim, 2, device=device, dtype=torch.float32) / dim) + ) + return inv_freq + def _get_rope_config(config): + if os.getenv("ROPE_SCALING", None) is not None: + rope_scaling = {"type": os.environ["ROPE_SCALING"], "factor": float(os.environ["ROPE_FACTOR"])} + return rope_scaling + return getattr(config, "rope_scaling", None) + + class PositionRotaryEmbedding(nn.Module): + def __init__(self, inv_freq, scaling_factor): + super().__init__() self.inv_freq = inv_freq self._seq_len_cached = 0 self._cos_cached = None self._sin_cached = None self._cos_k_cached = None self._sin_k_cached = None + self.scaling_factor = scaling_factor + self.dynamic_args = None @classmethod - def static(cls, dim, base, device): - inv_freq = 1.0 / ( - base - ** (torch.arange(0, dim, 2, device=device, dtype=torch.float32) / dim) - ) - return cls(inv_freq) + def static(cls, config, dim, base, device): + inv_freq = _create_inv_freq(dim, base, device) + scaling_factor = None + rope_scaling = _get_rope_config(config) + if rope_scaling is not None: + scaling_factor = rope_scaling["factor"] + if rope_scaling["type"] == "linear": + pass + elif rope_scaling["type"] == "dynamic": + return DynamicPositionRotaryEmbedding(dim=dim, max_position_embeddings=config.max_position_embeddings, base=base, device=inv_freq.device, scaling_factor=scaling_factor) + else: + raise NotImplementedError(f"rope scaling type {rope_scaling['type']} is not implemented or invalid") + return cls(inv_freq, scaling_factor) @classmethod - def load(cls, prefix, weights): + def load(cls, config, prefix, weights): # XXX: Always load this in float32 ! dtype = weights.dtype weights.dtype = torch.float32 inv_freq = weights.get_tensor(f"{prefix}.inv_freq") weights.dtype = dtype - return cls(inv_freq) + + scaling_factor = None + rope_scaling = _get_rope_config(config) + if rope_scaling is not None: + scaling_factor = rope_scaling["factor"] + if rope_scaling["type"] == "linear": + pass + elif rope_scaling["type"] == "dynamic": + return DynamicPositionRotaryEmbedding(dim=2*inv_freq.shape[0], max_position_embeddings=config.max_position_embeddings, base=10000.0, device=inv_freq.device, scaling_factor=scaling_factor) + else: + raise NotImplementedError(f"rope scaling type {rope_scaling['type']} is not implemented or invalid") + return cls(inv_freq, scaling_factor) def _update_cos_sin_cache(self, dtype, device, seqlen): # Reset the tables if the sequence length has changed, @@ -419,8 +451,11 @@ try: ): self._seq_len_cached = seqlen t = torch.arange(seqlen, device=device, dtype=self.inv_freq.dtype) + if self.scaling_factor is not None: + t /= self.scaling_factor # Don't do einsum, it converts fp32 to fp16 # freqs = torch.einsum("i,j->ij", t, self.inv_freq) + freqs = torch.outer(t, self.inv_freq.to(device=t.device)) self._cos_cached = torch.cos(freqs).to(dtype) self._sin_cached = torch.sin(freqs).to(dtype) @@ -446,5 +481,36 @@ try: rotary_emb.apply_rotary(x1, x2, cos, sin, x1, x2, False) return x + class DynamicPositionRotaryEmbedding(PositionRotaryEmbedding): + def __init__(self, dim, max_position_embeddings, base, device, scaling_factor): + inv_freq = create_inv_freq(dim, base, device) + super().__init__(inv_freq, scaling_factor) + self.dim = dim + self.max_position_embeddings = max_position_embeddings + self.base = base + + def _update_cos_sin_cache(self, dtype, device, seqlen): + # Reset the tables if the sequence length has changed, + # or if we're on a new device (possibly due to tracing for instance) + if ( + seqlen > self._seq_len_cached + or self._cos_cached.device != device + or self._cos_cached.dtype != dtype + ): + if seqlen > self.max_position_embeddings: + newbase = self.base * ((self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1)) ** (self.dim / (self.dim - 2)) + self.inv_freq = _create_inv_freq(self.dim, newbase, self.inv_freq.device) + self._seq_len_cached = seqlen + t = torch.arange(seqlen, device=device, dtype=self.inv_freq.dtype) + if self.scaling_factor is not None: + t /= self.scaling_factor + # Don't do einsum, it converts fp32 to fp16 + # freqs = torch.einsum("i,j->ij", t, self.inv_freq) + + freqs = torch.outer(t, self.inv_freq.to(device=t.device)) + self._cos_cached = torch.cos(freqs).to(dtype) + self._sin_cached = torch.sin(freqs).to(dtype) + + except ImportError: pass From 2a13f1a04682f43e48aea1f2378d1e32ee726256 Mon Sep 17 00:00:00 2001 From: Ikko Eltociear Ashimine Date: Mon, 31 Jul 2023 22:43:44 +0900 Subject: [PATCH 03/18] chore: fix typo in mpt_modeling.py (#737) # What does this PR do? Fixed typo. implemetation -> implementation ## Before submitting - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- .../models/custom_modeling/mpt_modeling.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/server/text_generation_server/models/custom_modeling/mpt_modeling.py b/server/text_generation_server/models/custom_modeling/mpt_modeling.py index e6057116..5ccf796d 100644 --- a/server/text_generation_server/models/custom_modeling/mpt_modeling.py +++ b/server/text_generation_server/models/custom_modeling/mpt_modeling.py @@ -297,7 +297,7 @@ def triton_flash_attn_fn( class MultiheadAttention(nn.Module): """Multi-head self attention. - Using torch or triton attention implemetation enables user to also use + Using torch or triton attention implementation enables user to also use additive bias. """ @@ -386,7 +386,7 @@ class MultiheadAttention(nn.Module): class MultiQueryAttention(nn.Module): """Multi-Query self attention. - Using torch or triton attention implemetation enables user to also use + Using torch or triton attention implementation enables user to also use additive bias. """ From 15fc64668f8d3dd407768286e5a0536aeb78c2e1 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Mon, 31 Jul 2023 17:51:26 +0200 Subject: [PATCH 04/18] fix(server): Failing quantize config after local read. (#743) # What does this PR do? Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- server/text_generation_server/utils/weights.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/server/text_generation_server/utils/weights.py b/server/text_generation_server/utils/weights.py index dcab6296..ef662ce1 100644 --- a/server/text_generation_server/utils/weights.py +++ b/server/text_generation_server/utils/weights.py @@ -224,7 +224,7 @@ class Weights: def _set_gptq_params(self, model_id): filename = "quantize_config.json" try: - if not os.path.exists(os.path.join(model_id, filename)): + if os.path.exists(os.path.join(model_id, filename)): filename = os.path.join(model_id, filename) else: filename = hf_hub_download(model_id, filename=filename) From d3d8f1bd6b2427fbe5c9c17e3b06899b43038343 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Mon, 31 Jul 2023 18:57:29 +0200 Subject: [PATCH 05/18] Typo fix. (#746) # What does this PR do? Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- server/text_generation_server/utils/layers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/server/text_generation_server/utils/layers.py b/server/text_generation_server/utils/layers.py index fc92ebe6..d7b4c0cc 100644 --- a/server/text_generation_server/utils/layers.py +++ b/server/text_generation_server/utils/layers.py @@ -483,7 +483,7 @@ try: class DynamicPositionRotaryEmbedding(PositionRotaryEmbedding): def __init__(self, dim, max_position_embeddings, base, device, scaling_factor): - inv_freq = create_inv_freq(dim, base, device) + inv_freq = _create_inv_freq(dim, base, device) super().__init__(inv_freq, scaling_factor) self.dim = dim self.max_position_embeddings = max_position_embeddings From 7766fee9b15b6f600ee73db7f8bd72f7c62f335e Mon Sep 17 00:00:00 2001 From: Florian Zimmermeister Date: Mon, 31 Jul 2023 18:58:46 +0200 Subject: [PATCH 06/18] fix typo for dynamic rotary (#745) @Narsil From bd3088748eeb6723b8fdcb26b51ab4b09bf851e7 Mon Sep 17 00:00:00 2001 From: zspo Date: Thu, 3 Aug 2023 02:04:46 +0800 Subject: [PATCH 07/18] add FastLinear import (#750) # What does this PR do? Fixes #749 ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. Co-authored-by: p_spozzhang --- .../models/custom_modeling/opt_modeling.py | 1 + 1 file changed, 1 insertion(+) diff --git a/server/text_generation_server/models/custom_modeling/opt_modeling.py b/server/text_generation_server/models/custom_modeling/opt_modeling.py index 5d1a4b0d..fe6f1e52 100644 --- a/server/text_generation_server/models/custom_modeling/opt_modeling.py +++ b/server/text_generation_server/models/custom_modeling/opt_modeling.py @@ -28,6 +28,7 @@ from transformers.modeling_outputs import ( from transformers.modeling_utils import PreTrainedModel from transformers import OPTConfig from text_generation_server.utils.layers import ( + FastLinear, TensorParallelColumnLinear, TensorParallelEmbedding, TensorParallelRowLinear, From 8b0d608f1f0e5495d7ca53528f602892d81758af Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Wed, 2 Aug 2023 20:24:37 +0200 Subject: [PATCH 08/18] Automatically map deduplicated safetensors weights to their original values (#501) (#761) # What does this PR do? CI cehck for #501 This PR automatically points tensors that were removed due to deduplication to their still existing twin. In `server.text_generation_server.utils.convert.py#convert_file`, tensors that have a value equal to another tensor are removed from the list of weights. Their name, and the name of the still-existing "twin" are logged to the "metadata" dictionary. However, this dictionary was not yet used during loading. This requires explicit in-code remapping when loading the models (as mentioned in the docstring). This PR adds some simple code to check, during loading, if a weight is one of those removed weights. It then automatically retrieves the values of its still-existing "twin" instead. ## What does this fix? We currently cannot load `h2oai/h2ogpt-oig-oasst1-falcon-40b` with the unmodified server, since the `transformer.word_embeddings.weight` weight is equal to `lm_head.weight` and is automatically removed. The falcon code, however, still expects this weight to exist. I could have also added some extra checks to the model itself, though that would only be a workaround. ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --------- # What does this PR do? Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. Co-authored-by: Vincent Brouwers Co-authored-by: Vincent Brouwers From ac736fd89c1f119b770a3385d100a954d2499ff7 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Thu, 3 Aug 2023 17:22:45 +0200 Subject: [PATCH 09/18] feat(server): Add native support for PEFT Lora models (#762) - Will detect `peft` model by finding `adapter_config.json`. - This triggers a totally dedicated `download-weights` path - This path, loads the adapter config, finds the base model_id - It loads the base_model - Then peft_model - Then `merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer.merge_and_unload()` - Then `save_pretrained(.., safe_serialization=True) - Add back the config + tokenizer. - The chosen location is a **local folder with the name of the user chosen model id** PROs: - Easier than to expect user to merge manually - Barely any change outside of `download-weights` command. - This means everything will work in a single load. - Should enable out of the box SM + HFE CONs: - Creates a local merged model in unusual location, potentially not saved across docker reloads, or ovewriting some files if the PEFT itself was local and containing other files in addition to the lora Alternatives considered: - Add `local_files_only=True` every where (discard because of massive code change for not a good enough reason) - Return something to `launcher` about the new model-id (a cleaner location for this new model), but it would introduce new communication somewhere where we didn't need it before. - Using the HF cache folder and *stopping* the flow after `download-weights` and asking user to restart with the actual local model location Fix #482 # What does this PR do? Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- launcher/src/main.rs | 5 + server/poetry.lock | 2190 ++++++++--------- server/pyproject.toml | 1 + server/requirements.txt | 25 +- server/text_generation_server/cli.py | 8 + .../text_generation_server/models/flash_rw.py | 2 +- .../text_generation_server/utils/__init__.py | 2 + server/text_generation_server/utils/peft.py | 46 + 8 files changed, 1136 insertions(+), 1143 deletions(-) create mode 100644 server/text_generation_server/utils/peft.py diff --git a/launcher/src/main.rs b/launcher/src/main.rs index 560ce181..146d83d6 100644 --- a/launcher/src/main.rs +++ b/launcher/src/main.rs @@ -716,6 +716,11 @@ fn download_convert_model(args: &Args, running: Arc) -> Result<(), L download_args.push(revision.to_string()) } + // Trust remote code for automatic peft fusion + if args.trust_remote_code { + download_args.push("--trust-remote-code".to_string()); + } + // Copy current process env let mut envs: Vec<(OsString, OsString)> = env::vars_os().collect(); diff --git a/server/poetry.lock b/server/poetry.lock index 16da22f5..ccbb7661 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -1,10 +1,15 @@ +# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. + [[package]] name = "accelerate" version = "0.19.0" description = "Accelerate" -category = "main" -optional = true +optional = false python-versions = ">=3.7.0" +files = [ + {file = "accelerate-0.19.0-py3-none-any.whl", hash = "sha256:2866b0bf9fff08f51e6384c95fa96725838b70f1988d1cce42e56b820d8a91dd"}, + {file = "accelerate-0.19.0.tar.gz", hash = "sha256:84920226b9e642e453ef37593ee55b956b08d8200dea4087c546c34e26157e76"}, +] [package.dependencies] numpy = ">=1.17" @@ -18,1057 +23,18 @@ dev = ["black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-buil quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.0.241)", "urllib3 (<2.0.0)"] rich = ["rich"] sagemaker = ["sagemaker"] -test_dev = ["datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"] -test_prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"] -test_trackers = ["comet-ml", "tensorboard", "wandb"] +test-dev = ["datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"] +test-prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"] +test-trackers = ["comet-ml", "tensorboard", "wandb"] testing = ["datasets", "deepspeed", "evaluate", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "tqdm", "transformers"] [[package]] name = "aiohttp" version = "3.8.5" description = "Async http client/server framework (asyncio)" -category = "main" optional = true python-versions = ">=3.6" - -[package.dependencies] -aiosignal = ">=1.1.2" -async-timeout = ">=4.0.0a3,<5.0" -attrs = ">=17.3.0" -charset-normalizer = ">=2.0,<4.0" -frozenlist = ">=1.1.1" -multidict = ">=4.5,<7.0" -yarl = ">=1.0,<2.0" - -[package.extras] -speedups = ["Brotli", "aiodns", "cchardet"] - -[[package]] -name = "aiosignal" -version = "1.3.1" -description = "aiosignal: a list of registered asynchronous callbacks" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -frozenlist = ">=1.1.0" - -[[package]] -name = "async-timeout" -version = "4.0.2" -description = "Timeout context manager for asyncio programs" -category = "main" -optional = true -python-versions = ">=3.6" - -[[package]] -name = "attrs" -version = "23.1.0" -description = "Classes Without Boilerplate" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.extras] -cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] -dev = ["attrs[docs,tests]", "pre-commit"] -docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] -tests = ["attrs[tests-no-zope]", "zope-interface"] -tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] - -[[package]] -name = "backoff" -version = "2.2.1" -description = "Function decoration for backoff and retry" -category = "main" -optional = false -python-versions = ">=3.7,<4.0" - -[[package]] -name = "bitsandbytes" -version = "0.38.1" -description = "8-bit optimizers and matrix multiplication routines." -category = "main" -optional = true -python-versions = "*" - -[[package]] -name = "certifi" -version = "2023.5.7" -description = "Python package for providing Mozilla's CA Bundle." -category = "main" -optional = false -python-versions = ">=3.6" - -[[package]] -name = "charset-normalizer" -version = "3.1.0" -description = "The Real First Universal Charset Detector. 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(>=1.3.0,<2.0.0)"] + +[[package]] +name = "typing-extensions" +version = "4.7.1" +description = "Backported and Experimental Type Hints for Python 3.7+" +optional = false +python-versions = ">=3.7" +files = [ {file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"}, {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"}, ] -tzdata = [ + +[[package]] +name = "tzdata" +version = "2023.3" +description = "Provider of IANA time zone data" +optional = true +python-versions = ">=2" +files = [ {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"}, {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"}, ] -urllib3 = [ + +[[package]] +name = "urllib3" +version = "2.0.3" +description = "HTTP library with thread-safe connection pooling, file post, and more." +optional = false +python-versions = ">=3.7" +files = [ {file = "urllib3-2.0.3-py3-none-any.whl", hash = "sha256:48e7fafa40319d358848e1bc6809b208340fafe2096f1725d05d67443d0483d1"}, {file = "urllib3-2.0.3.tar.gz", hash = "sha256:bee28b5e56addb8226c96f7f13ac28cb4c301dd5ea8a6ca179c0b9835e032825"}, ] -win32-setctime = [ + +[package.extras] +brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"] +secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"] +socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] +zstd = ["zstandard (>=0.18.0)"] + +[[package]] +name = "win32-setctime" +version = "1.1.0" +description = "A small Python utility to set file creation time on Windows" +optional = false +python-versions = ">=3.5" +files = [ {file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"}, {file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"}, ] -wrapt = [ + +[package.extras] +dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"] + +[[package]] +name = "wrapt" +version = "1.15.0" +description = "Module for decorators, wrappers and monkey patching." +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" +files = [ {file = "wrapt-1.15.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ca1cccf838cd28d5a0883b342474c630ac48cac5df0ee6eacc9c7290f76b11c1"}, {file = "wrapt-1.15.0-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:e826aadda3cae59295b95343db8f3d965fb31059da7de01ee8d1c40a60398b29"}, {file = "wrapt-1.15.0-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:5fc8e02f5984a55d2c653f5fea93531e9836abbd84342c1d1e17abc4a15084c2"}, @@ -2244,7 +2166,14 @@ wrapt = [ {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"}, {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"}, ] -xxhash = [ + +[[package]] +name = "xxhash" +version = "3.2.0" +description = "Python binding for xxHash" +optional = true +python-versions = ">=3.6" +files = [ {file = "xxhash-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:af44b9e59c4b2926a4e3c7f9d29949ff42fcea28637ff6b8182e654461932be8"}, {file = "xxhash-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1bdd57973e2b802ef32553d7bebf9402dac1557874dbe5c908b499ea917662cd"}, {file = "xxhash-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b7c9aa77bbce61a5e681bd39cb6a804338474dcc90abe3c543592aa5d6c9a9b"}, @@ -2344,7 +2273,14 @@ xxhash = [ {file = "xxhash-3.2.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:9d3f686e3d1c8900c5459eee02b60c7399e20ec5c6402364068a343c83a61d90"}, {file = "xxhash-3.2.0.tar.gz", hash = "sha256:1afd47af8955c5db730f630ad53ae798cf7fae0acb64cebb3cf94d35c47dd088"}, ] -yarl = [ + +[[package]] +name = "yarl" +version = "1.9.2" +description = "Yet another URL library" +optional = true +python-versions = ">=3.7" +files = [ {file = "yarl-1.9.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:8c2ad583743d16ddbdf6bb14b5cd76bf43b0d0006e918809d5d4ddf7bde8dd82"}, {file = "yarl-1.9.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:82aa6264b36c50acfb2424ad5ca537a2060ab6de158a5bd2a72a032cc75b9eb8"}, {file = "yarl-1.9.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c0c77533b5ed4bcc38e943178ccae29b9bcf48ffd1063f5821192f23a1bd27b9"}, @@ -2420,3 +2356,17 @@ yarl = [ {file = "yarl-1.9.2-cp39-cp39-win_amd64.whl", hash = "sha256:61016e7d582bc46a5378ffdd02cd0314fb8ba52f40f9cf4d9a5e7dbef88dee18"}, {file = "yarl-1.9.2.tar.gz", hash = "sha256:04ab9d4b9f587c06d801c2abfe9317b77cdf996c65a90d5e84ecc45010823571"}, ] + +[package.dependencies] +idna = ">=2.0" +multidict = ">=4.0" + +[extras] +accelerate = ["accelerate"] +bnb = ["bitsandbytes"] +quantize = ["accelerate", "datasets", "texttable"] + +[metadata] +lock-version = "2.0" +python-versions = "^3.9" +content-hash = "65fa01feaf4d0c939bfa7991803e4454d853f56652e4349151ea8dd9aa8feedf" diff --git a/server/pyproject.toml b/server/pyproject.toml index fdfbdd70..cc457b14 100644 --- a/server/pyproject.toml +++ b/server/pyproject.toml @@ -30,6 +30,7 @@ transformers = "4.29.2" einops = "^0.6.1" texttable = { version = "^1.6.7", optional = true } datasets = { version = "^2.14.0", optional = true } +peft = "^0.4.0" [tool.poetry.extras] accelerate = ["accelerate"] diff --git a/server/requirements.txt b/server/requirements.txt index 98838b36..4ffb80a1 100644 --- a/server/requirements.txt +++ b/server/requirements.txt @@ -1,22 +1,13 @@ accelerate==0.19.0 ; python_version >= "3.9" and python_version < "4.0" -aiohttp==3.8.5 ; python_version >= "3.9" and python_version < "4.0" -aiosignal==1.3.1 ; python_version >= "3.9" and python_version < "4.0" -async-timeout==4.0.2 ; python_version >= "3.9" and python_version < "4.0" -attrs==23.1.0 ; python_version >= "3.9" and python_version < "4.0" backoff==2.2.1 ; python_version >= "3.9" and python_version < "4.0" -bitsandbytes==0.38.1 ; python_version >= "3.9" and python_version < "4.0" certifi==2023.5.7 ; python_version >= "3.9" and python_version < "4.0" charset-normalizer==3.1.0 ; python_version >= "3.9" and python_version < "4.0" click==8.1.3 ; python_version >= "3.9" and python_version < "4.0" -colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" or python_version >= "3.9" and python_version < "4.0" and platform_system == "Windows" -datasets==2.14.0 ; python_version >= "3.9" and python_version < "4.0" +colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and (sys_platform == "win32" or platform_system == "Windows") deprecated==1.2.14 ; python_version >= "3.9" and python_version < "4.0" -dill==0.3.7 ; python_version >= "3.9" and python_version < "4.0" einops==0.6.1 ; python_version >= "3.9" and python_version < "4.0" filelock==3.12.2 ; python_version >= "3.9" and python_version < "4.0" -frozenlist==1.4.0 ; python_version >= "3.9" and python_version < "4.0" fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "4.0" -fsspec[http]==2023.6.0 ; python_version >= "3.9" and python_version < "4.0" googleapis-common-protos==1.59.1 ; python_version >= "3.9" and python_version < "4.0" grpc-interceptor==0.15.2 ; python_version >= "3.9" and python_version < "4.0" grpcio-reflection==1.56.0 ; python_version >= "3.9" and python_version < "4.0" @@ -29,10 +20,8 @@ jinja2==3.1.2 ; python_version >= "3.9" and python_version < "4.0" loguru==0.6.0 ; python_version >= "3.9" and python_version < "4.0" markupsafe==2.1.3 ; python_version >= "3.9" and python_version < "4.0" mpmath==1.3.0 ; python_version >= "3.9" and python_version < "4.0" -multidict==6.0.4 ; python_version >= "3.9" and python_version < "4.0" -multiprocess==0.70.15 ; python_version >= "3.9" and python_version < "4.0" networkx==3.1 ; python_version >= "3.9" and python_version < "4.0" -numpy==1.25.0 ; python_version < "4.0" and python_version >= "3.9" +numpy==1.25.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "4.0" @@ -43,30 +32,22 @@ opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "4.0" packaging==23.1 ; python_version >= "3.9" and python_version < "4.0" -pandas==2.0.3 ; python_version >= "3.9" and python_version < "4.0" +peft==0.4.0 ; python_version >= "3.9" and python_version < "4.0" protobuf==4.23.3 ; python_version >= "3.9" and python_version < "4.0" psutil==5.9.5 ; python_version >= "3.9" and python_version < "4.0" -pyarrow==12.0.1 ; python_version >= "3.9" and python_version < "4.0" -python-dateutil==2.8.2 ; python_version >= "3.9" and python_version < "4.0" -pytz==2023.3 ; python_version >= "3.9" and python_version < "4.0" pyyaml==6.0 ; python_version >= "3.9" and python_version < "4.0" regex==2023.6.3 ; python_version >= "3.9" and python_version < "4.0" requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0" safetensors==0.3.1 ; python_version >= "3.9" and python_version < "4.0" sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "4.0" setuptools==68.0.0 ; python_version >= "3.9" and python_version < "4.0" -six==1.16.0 ; python_version >= "3.9" and python_version < "4.0" sympy==1.12 ; python_version >= "3.9" and python_version < "4.0" -texttable==1.6.7 ; python_version >= "3.9" and python_version < "4.0" tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "4.0" torch==2.0.1 ; python_version >= "3.9" and python_version < "4.0" tqdm==4.65.0 ; python_version >= "3.9" and python_version < "4.0" transformers==4.29.2 ; python_version >= "3.9" and python_version < "4.0" typer==0.6.1 ; python_version >= "3.9" and python_version < "4.0" typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "4.0" -tzdata==2023.3 ; python_version >= "3.9" and python_version < "4.0" urllib3==2.0.3 ; python_version >= "3.9" and python_version < "4.0" win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" wrapt==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -xxhash==3.2.0 ; python_version >= "3.9" and python_version < "4.0" -yarl==1.9.2 ; python_version >= "3.9" and python_version < "4.0" diff --git a/server/text_generation_server/cli.py b/server/text_generation_server/cli.py index e74c0331..eba807bc 100644 --- a/server/text_generation_server/cli.py +++ b/server/text_generation_server/cli.py @@ -6,6 +6,7 @@ from pathlib import Path from loguru import logger from typing import Optional from enum import Enum +from huggingface_hub import hf_hub_download app = typer.Typer() @@ -88,6 +89,7 @@ def download_weights( auto_convert: bool = True, logger_level: str = "INFO", json_output: bool = False, + trust_remote_code: bool = False, ): # Remove default handler logger.remove() @@ -118,6 +120,12 @@ def download_weights( ) is not None if not is_local_model: + try: + adapter_config_filename = hf_hub_download(model_id, revision=revision, filename="adapter_config.json") + utils.download_and_unload_peft(model_id, revision, trust_remote_code=trust_remote_code) + except (utils.LocalEntryNotFoundError, utils.EntryNotFoundError): + pass + # Try to download weights from the hub try: filenames = utils.weight_hub_files(model_id, revision, extension) diff --git a/server/text_generation_server/models/flash_rw.py b/server/text_generation_server/models/flash_rw.py index 7d655945..2fc7c53d 100644 --- a/server/text_generation_server/models/flash_rw.py +++ b/server/text_generation_server/models/flash_rw.py @@ -54,7 +54,7 @@ class FlashRWSharded(FlashCausalLM): device, dtype, process_group=self.process_group, - aliases={"transformer.word_embeddings.weight": ["lm_head.weight"]}, + aliases={"lm_head.weight": ["transformer.word_embeddings.weight"]}, ) config.quantize = quantize diff --git a/server/text_generation_server/utils/__init__.py b/server/text_generation_server/utils/__init__.py index befedcf0..08ba808d 100644 --- a/server/text_generation_server/utils/__init__.py +++ b/server/text_generation_server/utils/__init__.py @@ -1,6 +1,7 @@ from text_generation_server.utils.convert import convert_file, convert_files from text_generation_server.utils.dist import initialize_torch_distributed from text_generation_server.utils.weights import Weights +from text_generation_server.utils.peft import download_and_unload_peft from text_generation_server.utils.hub import ( weight_files, weight_hub_files, @@ -26,6 +27,7 @@ __all__ = [ "weight_files", "weight_hub_files", "download_weights", + "download_and_unload_peft", "EntryNotFoundError", "HeterogeneousNextTokenChooser", "LocalEntryNotFoundError", diff --git a/server/text_generation_server/utils/peft.py b/server/text_generation_server/utils/peft.py new file mode 100644 index 00000000..be1f9444 --- /dev/null +++ b/server/text_generation_server/utils/peft.py @@ -0,0 +1,46 @@ +import os +import json +from loguru import logger +import torch + +from transformers import AutoTokenizer +from peft import AutoPeftModelForCausalLM, AutoPeftModelForSeq2SeqLM + +def download_and_unload_peft(model_id, revision, trust_remote_code): + torch_dtype = torch.float16 + + logger.info("Peft model detected.") + logger.info("Loading the model it might take a while without feedback") + try: + model = AutoPeftModelForCausalLM.from_pretrained( + model_id, + revision=revision, + torch_dtype=torch_dtype, + trust_remote_code=trust_remote_code, + low_cpu_mem_usage=True, + ) + except Exception: + model = AutoPeftModelForSeq2SeqLM.from_pretrained( + model_id, + revision=revision, + torch_dtype=torch_dtype, + trust_remote_code=trust_remote_code, + low_cpu_mem_usage=True, + ) + logger.info(f"Loaded.") + logger.info(f"Merging the lora weights.") + + base_model_id = model.peft_config["default"].base_model_name_or_path + + model = model.merge_and_unload() + + os.makedirs(model_id, exist_ok=True) + cache_dir = model_id + logger.info(f"Saving the newly created merged model to {cache_dir}") + tokenizer = AutoTokenizer.from_pretrained(base_model_id) + model.save_pretrained(cache_dir, safe_serialization=True) + model.config.save_pretrained(cache_dir) + tokenizer.save_pretrained(cache_dir) + + + From 6ec5288ab76ce91e84bd7389a0249b0254d1d1f8 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Thu, 3 Aug 2023 21:54:39 +0200 Subject: [PATCH 10/18] This should prevent the PyTorch overriding. (#767) # What does this PR do? Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- Dockerfile | 3 +- server/poetry.lock | 861 +++++++++++++++++++++------------------- server/pyproject.toml | 7 + server/requirements.txt | 29 +- 4 files changed, 485 insertions(+), 415 deletions(-) diff --git a/Dockerfile b/Dockerfile index 679fb48a..45e304c4 100644 --- a/Dockerfile +++ b/Dockerfile @@ -39,8 +39,9 @@ RUN cargo build --release # Adapted from: https://github.com/pytorch/pytorch/blob/master/Dockerfile FROM debian:bullseye-slim as pytorch-install -ARG PYTORCH_VERSION=2.0.0 +ARG PYTORCH_VERSION=2.0.1 ARG PYTHON_VERSION=3.9 +# Keep in sync with `server/pyproject.toml ARG CUDA_VERSION=11.8 ARG MAMBA_VERSION=23.1.0-1 ARG CUDA_CHANNEL=nvidia diff --git a/server/poetry.lock b/server/poetry.lock index ccbb7661..70f09f32 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -203,113 +203,142 @@ files = [ [[package]] name = "certifi" -version = "2023.5.7" +version = "2023.7.22" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" files = [ - {file = "certifi-2023.5.7-py3-none-any.whl", hash = "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"}, - {file = "certifi-2023.5.7.tar.gz", hash = "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7"}, + {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"}, + {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"}, ] [[package]] name = "charset-normalizer" -version = "3.1.0" +version = "3.2.0" description = "The Real First Universal Charset Detector. 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"https://download.pytorch.org/whl/cu118" +priority = "explicit" + [tool.pytest.ini_options] markers = ["private: marks tests as requiring an admin hf token (deselect with '-m \"not private\"')"] diff --git a/server/requirements.txt b/server/requirements.txt index 4ffb80a1..f9414b25 100644 --- a/server/requirements.txt +++ b/server/requirements.txt @@ -1,27 +1,31 @@ +--extra-index-url https://download.pytorch.org/whl/cu118 + accelerate==0.19.0 ; python_version >= "3.9" and python_version < "4.0" backoff==2.2.1 ; python_version >= "3.9" and python_version < "4.0" -certifi==2023.5.7 ; python_version >= "3.9" and python_version < "4.0" -charset-normalizer==3.1.0 ; python_version >= "3.9" and python_version < "4.0" -click==8.1.3 ; python_version >= "3.9" and python_version < "4.0" +certifi==2023.7.22 ; python_version >= "3.9" and python_version < "4.0" +charset-normalizer==3.2.0 ; python_version >= "3.9" and python_version < "4.0" +click==8.1.6 ; python_version >= "3.9" and python_version < 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and python_version < "4.0" +grpcio-reflection==1.56.2 ; python_version >= "3.9" and python_version < "4.0" +grpcio-status==1.56.2 ; python_version >= "3.9" and python_version < "4.0" +grpcio==1.56.2 ; python_version >= "3.9" and python_version < "4.0" hf-transfer==0.1.3 ; python_version >= "3.9" and python_version < "4.0" huggingface-hub==0.14.1 ; python_version >= "3.9" and python_version < "4.0" idna==3.4 ; python_version >= "3.9" and python_version < "4.0" jinja2==3.1.2 ; python_version >= "3.9" and python_version < "4.0" +lit==16.0.6 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "4.0" loguru==0.6.0 ; python_version >= "3.9" and python_version < "4.0" markupsafe==2.1.3 ; python_version >= "3.9" and python_version < "4.0" mpmath==1.3.0 ; python_version >= "3.9" and python_version < "4.0" networkx==3.1 ; python_version >= "3.9" and python_version < "4.0" -numpy==1.25.0 ; python_version >= "3.9" and python_version < "4.0" +numpy==1.25.2 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "4.0" @@ -33,9 +37,9 @@ opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "4.0" opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "4.0" packaging==23.1 ; python_version >= "3.9" and python_version < "4.0" peft==0.4.0 ; python_version >= "3.9" and python_version < "4.0" -protobuf==4.23.3 ; python_version >= "3.9" and python_version < "4.0" +protobuf==4.23.4 ; python_version >= "3.9" and python_version < "4.0" psutil==5.9.5 ; python_version >= "3.9" and python_version < "4.0" -pyyaml==6.0 ; python_version >= "3.9" and python_version < "4.0" +pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "4.0" regex==2023.6.3 ; python_version >= "3.9" and python_version < "4.0" requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0" safetensors==0.3.1 ; python_version >= "3.9" and python_version < "4.0" @@ -43,11 +47,12 @@ sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "4.0" setuptools==68.0.0 ; python_version >= "3.9" and python_version < "4.0" sympy==1.12 ; python_version >= "3.9" and python_version < "4.0" tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "4.0" -torch==2.0.1 ; python_version >= "3.9" and python_version < "4.0" +torch==2.0.1+cu118 ; python_version >= "3.9" and python_version < "4.0" tqdm==4.65.0 ; python_version >= "3.9" and python_version < "4.0" transformers==4.29.2 ; python_version >= "3.9" and python_version < "4.0" +triton==2.0.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "4.0" typer==0.6.1 ; python_version >= "3.9" and python_version < "4.0" typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "4.0" -urllib3==2.0.3 ; python_version >= "3.9" and python_version < "4.0" +urllib3==2.0.4 ; python_version >= "3.9" and python_version < "4.0" win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" wrapt==1.15.0 ; python_version >= "3.9" and python_version < "4.0" From f91e9d282d73e09cdb876924412f2ed66212d736 Mon Sep 17 00:00:00 2001 From: zspo Date: Fri, 4 Aug 2023 04:21:33 +0800 Subject: [PATCH 11/18] fix build tokenizer in quantize and remove duplicate import (#768) # What does this PR do? Fixes #732 And remove duplicate AutoTokenizer import ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- .../utils/gptq/quantize.py | 81 ++++++++++++------- 1 file changed, 51 insertions(+), 30 deletions(-) diff --git a/server/text_generation_server/utils/gptq/quantize.py b/server/text_generation_server/utils/gptq/quantize.py index 3f8e897a..9547d534 100644 --- a/server/text_generation_server/utils/gptq/quantize.py +++ b/server/text_generation_server/utils/gptq/quantize.py @@ -360,15 +360,21 @@ class GPTQ: torch.cuda.empty_cache() -def get_wikitext2(nsamples, seed, seqlen, model_id): +def get_wikitext2(nsamples, seed, seqlen, model_id, trust_remote_code): from datasets import load_dataset traindata = load_dataset("wikitext", "wikitext-2-raw-v1", split="train") testdata = load_dataset("wikitext", "wikitext-2-raw-v1", split="test") - from transformers import AutoTokenizer + try: + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=False, trust_remote_code=trust_remote_code + ) + except: + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=True, trust_remote_code=trust_remote_code + ) - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=False) trainenc = tokenizer("\n\n".join(traindata["text"]), return_tensors="pt") testenc = tokenizer("\n\n".join(testdata["text"]), return_tensors="pt") @@ -386,18 +392,21 @@ def get_wikitext2(nsamples, seed, seqlen, model_id): return trainloader, testenc -def get_ptb(nsamples, seed, seqlen, model_id): +def get_ptb(nsamples, seed, seqlen, model_id, trust_remote_code): from datasets import load_dataset traindata = load_dataset("ptb_text_only", "penn_treebank", split="train") valdata = load_dataset("ptb_text_only", "penn_treebank", split="validation") - from transformers import AutoTokenizer - try: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=False) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=False, trust_remote_code=trust_remote_code + ) except: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=True, trust_remote_code=trust_remote_code + ) + trainenc = tokenizer("\n\n".join(traindata["sentence"]), return_tensors="pt") testenc = tokenizer("\n\n".join(valdata["sentence"]), return_tensors="pt") @@ -415,7 +424,7 @@ def get_ptb(nsamples, seed, seqlen, model_id): return trainloader, testenc -def get_c4(nsamples, seed, seqlen, model_id): +def get_c4(nsamples, seed, seqlen, model_id, trust_remote_code): from datasets import load_dataset traindata = load_dataset( @@ -433,12 +442,14 @@ def get_c4(nsamples, seed, seqlen, model_id): use_auth_token=False, ) - from transformers import AutoTokenizer - try: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=False) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=False, trust_remote_code=trust_remote_code + ) except: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=True, trust_remote_code=trust_remote_code + ) import random @@ -481,18 +492,21 @@ def get_c4(nsamples, seed, seqlen, model_id): return trainloader, valenc -def get_ptb_new(nsamples, seed, seqlen, model_id): +def get_ptb_new(nsamples, seed, seqlen, model_id, trust_remote_code): from datasets import load_dataset traindata = load_dataset("ptb_text_only", "penn_treebank", split="train") testdata = load_dataset("ptb_text_only", "penn_treebank", split="test") - from transformers import AutoTokenizer - try: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=False) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=False, trust_remote_code=trust_remote_code + ) except: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=True, trust_remote_code=trust_remote_code + ) + trainenc = tokenizer(" ".join(traindata["sentence"]), return_tensors="pt") testenc = tokenizer(" ".join(testdata["sentence"]), return_tensors="pt") @@ -510,7 +524,7 @@ def get_ptb_new(nsamples, seed, seqlen, model_id): return trainloader, testenc -def get_c4_new(nsamples, seed, seqlen, model_id): +def get_c4_new(nsamples, seed, seqlen, model_id, trust_remote_code): from datasets import load_dataset traindata = load_dataset( @@ -526,12 +540,14 @@ def get_c4_new(nsamples, seed, seqlen, model_id): split="validation", ) - from transformers import AutoTokenizer - try: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=False) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=False, trust_remote_code=trust_remote_code + ) except: - tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True) + tokenizer = AutoTokenizer.from_pretrained( + model_id, use_fast=True, trust_remote_code=trust_remote_code + ) import random @@ -562,17 +578,17 @@ def get_c4_new(nsamples, seed, seqlen, model_id): return trainloader, valenc -def get_loaders(name, nsamples=128, seed=0, seqlen=2048, model_id=""): +def get_loaders(name, nsamples=128, seed=0, seqlen=2048, model_id="", trust_remote_code=False): if "wikitext2" in name: - return get_wikitext2(nsamples, seed, seqlen, model_id) + return get_wikitext2(nsamples, seed, seqlen, model_id, trust_remote_code) if "ptb" in name: if "new" in name: - return get_ptb_new(nsamples, seed, seqlen, model_id) - return get_ptb(nsamples, seed, seqlen, model_id) + return get_ptb_new(nsamples, seed, seqlen, model_id, trust_remote_code) + return get_ptb(nsamples, seed, seqlen, model_id, trust_remote_code) if "c4" in name: if "new" in name: - return get_c4_new(nsamples, seed, seqlen, model_id) - return get_c4(nsamples, seed, seqlen, model_id) + return get_c4_new(nsamples, seed, seqlen, model_id, trust_remote_code) + return get_c4(nsamples, seed, seqlen, model_id, trust_remote_code) def find_layers(module, layers=(nn.Conv2d, nn.Linear), name=""): @@ -906,7 +922,12 @@ def quantize( seed = None dataloader, testloader = get_loaders( - dataset, nsamples=nsamples, seed=seed, model_id=model_id, seqlen=model.seqlen + dataset, + nsamples=nsamples, + seed=seed, + model_id=model_id, + seqlen=model.seqlen, + trust_remote_code=trust_remote_code ) tick = time.time() From 16fadcec5711ff232977b38c74a1c8829af6a63b Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Thu, 3 Aug 2023 23:00:59 +0200 Subject: [PATCH 12/18] Merge BNB 4bit. (#770) # What does this PR do? See #626 Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --------- Co-authored-by: krzim --- README.md | 2 + launcher/src/main.rs | 11 +- server/poetry.lock | 48 +++++++- server/pyproject.toml | 5 +- server/requirements.txt | 113 +++++++++--------- server/text_generation_server/cli.py | 2 + .../text_generation_server/models/__init__.py | 5 +- server/text_generation_server/utils/layers.py | 47 +++++++- 8 files changed, 166 insertions(+), 67 deletions(-) diff --git a/README.md b/README.md index 869cc668..0ba49675 100644 --- a/README.md +++ b/README.md @@ -252,6 +252,8 @@ You can also quantize the weights with bitsandbytes to reduce the VRAM requireme make run-falcon-7b-instruct-quantize ``` +4bit quantization is available using the [NF4 and FP4 data types from bitsandbytes](https://arxiv.org/pdf/2305.14314.pdf). It can be enabled by providing `--quantize bitsandbytes-nf4` or `--quantize bitsandbytes-fp4` as a command line argument to `text-generation-launcher`. + ## Develop ```shell diff --git a/launcher/src/main.rs b/launcher/src/main.rs index 146d83d6..75762712 100644 --- a/launcher/src/main.rs +++ b/launcher/src/main.rs @@ -22,6 +22,8 @@ mod env_runtime; #[derive(Clone, Copy, Debug, ValueEnum)] enum Quantization { Bitsandbytes, + BitsandbytesNF4, + BitsandbytesFP4, Gptq, } @@ -32,6 +34,12 @@ impl std::fmt::Display for Quantization { Quantization::Bitsandbytes => { write!(f, "bitsandbytes") } + Quantization::BitsandbytesNF4 => { + write!(f, "bitsandbytes-nf4") + } + Quantization::BitsandbytesFP4 => { + write!(f, "bitsandbytes-fp4") + } Quantization::Gptq => { write!(f, "gptq") } @@ -116,7 +124,8 @@ struct Args { num_shard: Option, /// Whether you want the model to be quantized. This will use `bitsandbytes` for - /// quantization on the fly, or `gptq`. + /// quantization on the fly, or `gptq`. 4bit quantization is available through + /// `bitsandbytes` by providing the `bitsandbytes-fp4` or `bitsandbytes-nf4` options. #[clap(long, env, value_enum)] quantize: Option, diff --git a/server/poetry.lock b/server/poetry.lock index 70f09f32..f447914a 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -192,13 +192,13 @@ files = [ [[package]] name = "bitsandbytes" -version = "0.38.1" -description = "8-bit optimizers and matrix multiplication routines." +version = "0.40.2" +description = "k-bit optimizers and matrix multiplication routines." optional = true python-versions = "*" files = [ - {file = "bitsandbytes-0.38.1-py3-none-any.whl", hash = "sha256:5f532e7b1353eb7049ae831da2eb62ed8a1e0444116bd51b9e088a6e0bc7a34a"}, - {file = "bitsandbytes-0.38.1.tar.gz", hash = "sha256:ba95a806b5065ea3263558e188f07eacb32ad691842932fb0d36a879883167ce"}, + {file = "bitsandbytes-0.40.2-py3-none-any.whl", hash = "sha256:f0ae26f40c9230c9add9e7c70a10a5ced36fb6deff39906aec1ce4fd25e6ddc0"}, + {file = "bitsandbytes-0.40.2.tar.gz", hash = "sha256:808ac966272c63bccb2be6d77365275a4c28f1fa348d33656e670de3cab40fc4"}, ] [[package]] @@ -1751,6 +1751,42 @@ tensorflow = ["tensorflow (>=2.11.0)"] testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "numpy (>=1.21.6)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)"] torch = ["torch (>=1.10)"] +[[package]] +name = "scipy" +version = "1.11.1" +description = "Fundamental algorithms for scientific computing in Python" +optional = false +python-versions = "<3.13,>=3.9" +files = [ + {file = "scipy-1.11.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:aec8c62fbe52914f9cf28d846cf0401dd80ab80788bbab909434eb336ed07c04"}, + {file = "scipy-1.11.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:3b9963798df1d8a52db41a6fc0e6fa65b1c60e85d73da27ae8bb754de4792481"}, + {file = 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"pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"] + [[package]] name = "sentencepiece" version = "0.1.99" @@ -2425,5 +2461,5 @@ quantize = ["accelerate", "datasets", "texttable"] [metadata] lock-version = "2.0" -python-versions = "^3.9" -content-hash = "93fd0873b3e16c10b67a84216a84f5eb2f5067cb3ff8cb912446cc6a7fa9c030" +python-versions = ">=3.9,<3.13" +content-hash = "2abb80833b678452cfc73464fc5b2e48d74b2672bd987240041a33c724a74000" diff --git a/server/pyproject.toml b/server/pyproject.toml index 56afda0a..88b93f4e 100644 --- a/server/pyproject.toml +++ b/server/pyproject.toml @@ -8,7 +8,7 @@ authors = ["Olivier Dehaene "] text-generation-server = 'text_generation_server.cli:app' [tool.poetry.dependencies] -python = "^3.9" +python = ">=3.9,<3.13" protobuf = "^4.21.7" grpcio = "^1.51.1" grpcio-status = "^1.51.1" @@ -16,7 +16,7 @@ grpcio-reflection = "^1.51.1" grpc-interceptor = "^0.15.0" typer = "^0.6.1" accelerate = { version = "^0.19.0", optional = true } -bitsandbytes = { version = "^0.38.1", optional = true } +bitsandbytes = { version = "^0.40.0", optional = true } safetensors = "0.3.1" loguru = "^0.6.0" opentelemetry-api = "^1.15.0" @@ -32,6 +32,7 @@ texttable = { version = "^1.6.7", optional = true } datasets = { version = "^2.14.0", optional = true } peft = "^0.4.0" torch = {version = "^2.0.1+cu118", source = "pytorch-gpu-src"} +scipy = "^1.11.1" [tool.poetry.extras] accelerate = ["accelerate"] diff --git a/server/requirements.txt b/server/requirements.txt index f9414b25..beab4bf6 100644 --- a/server/requirements.txt +++ b/server/requirements.txt @@ -1,58 +1,59 @@ --extra-index-url https://download.pytorch.org/whl/cu118 -accelerate==0.19.0 ; python_version >= "3.9" and python_version < "4.0" -backoff==2.2.1 ; python_version >= "3.9" and python_version < "4.0" -certifi==2023.7.22 ; python_version >= "3.9" and python_version < "4.0" -charset-normalizer==3.2.0 ; python_version >= "3.9" and python_version < "4.0" -click==8.1.6 ; python_version >= "3.9" and python_version < "4.0" -cmake==3.27.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "4.0" -colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and (sys_platform == "win32" or platform_system == "Windows") -deprecated==1.2.14 ; python_version >= "3.9" and python_version < "4.0" -einops==0.6.1 ; python_version >= "3.9" and python_version < "4.0" -filelock==3.12.2 ; python_version >= "3.9" and python_version < "4.0" -fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "4.0" -googleapis-common-protos==1.60.0 ; python_version >= "3.9" and python_version < "4.0" -grpc-interceptor==0.15.2 ; python_version >= "3.9" and python_version < "4.0" -grpcio-reflection==1.56.2 ; python_version >= "3.9" and python_version < "4.0" -grpcio-status==1.56.2 ; python_version >= "3.9" and python_version < "4.0" -grpcio==1.56.2 ; python_version >= "3.9" and python_version < "4.0" -hf-transfer==0.1.3 ; python_version >= "3.9" and python_version < "4.0" -huggingface-hub==0.14.1 ; python_version >= "3.9" and python_version < "4.0" -idna==3.4 ; python_version >= "3.9" and python_version < "4.0" -jinja2==3.1.2 ; python_version >= "3.9" and python_version < "4.0" -lit==16.0.6 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "4.0" -loguru==0.6.0 ; python_version >= "3.9" and python_version < "4.0" -markupsafe==2.1.3 ; python_version >= "3.9" and python_version < "4.0" -mpmath==1.3.0 ; python_version >= "3.9" and python_version < "4.0" -networkx==3.1 ; python_version >= "3.9" and python_version < "4.0" -numpy==1.25.2 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-exporter-otlp==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-instrumentation-grpc==0.36b0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-instrumentation==0.36b0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "4.0" -opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "4.0" -packaging==23.1 ; python_version >= "3.9" and python_version < "4.0" -peft==0.4.0 ; python_version >= "3.9" and python_version < "4.0" -protobuf==4.23.4 ; python_version >= "3.9" and python_version < "4.0" -psutil==5.9.5 ; python_version >= "3.9" and python_version < "4.0" -pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "4.0" -regex==2023.6.3 ; python_version >= "3.9" and python_version < "4.0" -requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0" -safetensors==0.3.1 ; python_version >= "3.9" and python_version < "4.0" -sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "4.0" -setuptools==68.0.0 ; python_version >= "3.9" and python_version < "4.0" -sympy==1.12 ; python_version >= "3.9" and python_version < "4.0" -tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "4.0" -torch==2.0.1+cu118 ; python_version >= "3.9" and python_version < "4.0" -tqdm==4.65.0 ; python_version >= "3.9" and python_version < "4.0" -transformers==4.29.2 ; python_version >= "3.9" and python_version < "4.0" -triton==2.0.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "4.0" -typer==0.6.1 ; python_version >= "3.9" and python_version < "4.0" -typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "4.0" -urllib3==2.0.4 ; python_version >= "3.9" and python_version < "4.0" -win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" -wrapt==1.15.0 ; python_version >= "3.9" and python_version < "4.0" +accelerate==0.19.0 ; python_version >= "3.9" and python_version < "3.13" +backoff==2.2.1 ; python_version >= "3.9" and python_version < "3.13" +certifi==2023.7.22 ; python_version >= "3.9" and python_version < "3.13" +charset-normalizer==3.2.0 ; python_version >= "3.9" and python_version < "3.13" +click==8.1.6 ; python_version >= "3.9" and python_version < "3.13" +cmake==3.27.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "3.13" +colorama==0.4.6 ; python_version >= "3.9" and python_version < "3.13" and (sys_platform == "win32" or platform_system == "Windows") +deprecated==1.2.14 ; python_version >= "3.9" and python_version < "3.13" +einops==0.6.1 ; python_version >= "3.9" and python_version < "3.13" +filelock==3.12.2 ; python_version >= "3.9" and python_version < "3.13" +fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "3.13" +googleapis-common-protos==1.60.0 ; python_version >= "3.9" and python_version < "3.13" +grpc-interceptor==0.15.2 ; python_version >= "3.9" and python_version < "3.13" +grpcio-reflection==1.56.2 ; python_version >= "3.9" and python_version < "3.13" +grpcio-status==1.56.2 ; python_version >= "3.9" and python_version < "3.13" +grpcio==1.56.2 ; python_version >= "3.9" and python_version < "3.13" +hf-transfer==0.1.3 ; python_version >= "3.9" and python_version < "3.13" +huggingface-hub==0.14.1 ; python_version >= "3.9" and python_version < "3.13" +idna==3.4 ; python_version >= "3.9" and python_version < "3.13" +jinja2==3.1.2 ; python_version >= "3.9" and python_version < "3.13" +lit==16.0.6 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "3.13" +loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13" +markupsafe==2.1.3 ; python_version >= "3.9" and python_version < "3.13" +mpmath==1.3.0 ; python_version >= "3.9" and python_version < "3.13" +networkx==3.1 ; python_version >= "3.9" and python_version < "3.13" +numpy==1.25.2 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-exporter-otlp==1.15.0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-instrumentation-grpc==0.36b0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-instrumentation==0.36b0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "3.13" +opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "3.13" +packaging==23.1 ; python_version >= "3.9" and python_version < "3.13" +peft==0.4.0 ; python_version >= "3.9" and python_version < "3.13" +protobuf==4.23.4 ; python_version >= "3.9" and python_version < "3.13" +psutil==5.9.5 ; python_version >= "3.9" and python_version < "3.13" +pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "3.13" +regex==2023.6.3 ; python_version >= "3.9" and python_version < "3.13" +requests==2.31.0 ; python_version >= "3.9" and python_version < "3.13" +safetensors==0.3.1 ; python_version >= "3.9" and python_version < "3.13" +scipy==1.11.1 ; python_version >= "3.9" and python_version < "3.13" +sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13" +setuptools==68.0.0 ; python_version >= "3.9" and python_version < "3.13" +sympy==1.12 ; python_version >= "3.9" and python_version < "3.13" +tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "3.13" +torch==2.0.1+cu118 ; python_version >= "3.9" and python_version < "3.13" +tqdm==4.65.0 ; python_version >= "3.9" and python_version < "3.13" +transformers==4.29.2 ; python_version >= "3.9" and python_version < "3.13" +triton==2.0.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_version < "3.13" +typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13" +typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "3.13" +urllib3==2.0.4 ; python_version >= "3.9" and python_version < "3.13" +win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "3.13" and sys_platform == "win32" +wrapt==1.15.0 ; python_version >= "3.9" and python_version < "3.13" diff --git a/server/text_generation_server/cli.py b/server/text_generation_server/cli.py index eba807bc..459ba8c4 100644 --- a/server/text_generation_server/cli.py +++ b/server/text_generation_server/cli.py @@ -14,6 +14,8 @@ app = typer.Typer() class Quantization(str, Enum): bitsandbytes = "bitsandbytes" + bitsandbytes_nf4 = "bitsandbytes-nf4" + bitsandbytes_fp4 = "bitsandbytes-fp4" gptq = "gptq" diff --git a/server/text_generation_server/models/__init__.py b/server/text_generation_server/models/__init__.py index e9260eed..71efcab7 100644 --- a/server/text_generation_server/models/__init__.py +++ b/server/text_generation_server/models/__init__.py @@ -255,7 +255,10 @@ def get_model( raise ValueError( "gptq quantization is not supported for AutoModel, you can try to quantize it with `text-generation-server quantize ORIGINAL_MODEL_ID NEW_MODEL_ID`" ) - + elif (quantize == "bitsandbytes-fp4") or (quantize == "bitsandbytes-nf4"): + raise ValueError( + "4bit quantization is not supported for AutoModel" + ) if model_type in modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES: return CausalLM( model_id, diff --git a/server/text_generation_server/utils/layers.py b/server/text_generation_server/utils/layers.py index d7b4c0cc..97257f95 100644 --- a/server/text_generation_server/utils/layers.py +++ b/server/text_generation_server/utils/layers.py @@ -9,7 +9,7 @@ from typing import List HAS_BITS_AND_BYTES = True try: import bitsandbytes as bnb - from bitsandbytes.nn import Int8Params + from bitsandbytes.nn import Int8Params, Params4bit except ImportError: HAS_BITS_AND_BYTES = False @@ -140,6 +140,39 @@ class Linear8bitLt(nn.Module): return out +class Linear4bit(nn.Module): + def __init__(self, weight, bias, quant_type): + super().__init__() + self.weight = Params4bit( + weight.data, requires_grad=False, compress_statistics=True, quant_type=quant_type + ) + self.compute_dtype = None + self.weight.cuda(weight.device) + self.bias = bias + + def forward(self, x: torch.Tensor): + # weights are cast automatically as Int8Params, but the bias has to be cast manually + if self.bias is not None and self.bias.dtype != x.dtype: + self.bias.data = self.bias.data.to(x.dtype) + + if getattr(self.weight, "quant_state", None) is None: + print( + "FP4 quantization state not initialized. Please call .cuda() or .to(device) on the LinearFP4 layer first." + ) + inp_dtype = x.dtype + if self.compute_dtype is not None: + x = x.to(self.compute_dtype) + + bias = None if self.bias is None else self.bias.to(self.compute_dtype) + out = bnb.matmul_4bit( + x, self.weight.t(), bias=bias, quant_state=self.weight.quant_state + ) + + out = out.to(inp_dtype) + + return out + + def get_linear(weight, bias, quantize): if quantize is None: linear = FastLinear(weight, bias) @@ -152,6 +185,18 @@ def get_linear(weight, bias, quantize): ) if bias is not None: linear.bias = nn.Parameter(bias) + elif quantize == "bitsandbytes-fp4": + linear = Linear4bit( + weight, + bias, + quant_type="fp4", + ) + elif quantize == "bitsandbytes-nf4": + linear = Linear4bit( + weight, + bias, + quant_type="nf4", + ) elif quantize == "gptq": try: qweight, qzeros, scales, g_idx, bits, groupsize, use_exllama = weight From 891e19cc5126a53375a1908312da4e7cedd763e0 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Mon, 7 Aug 2023 12:28:19 +0200 Subject: [PATCH 13/18] Fix dynamic rope. (#783) # What does this PR do? Typo Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- server/text_generation_server/utils/layers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/server/text_generation_server/utils/layers.py b/server/text_generation_server/utils/layers.py index 97257f95..c2a340b2 100644 --- a/server/text_generation_server/utils/layers.py +++ b/server/text_generation_server/utils/layers.py @@ -543,7 +543,7 @@ try: or self._cos_cached.dtype != dtype ): if seqlen > self.max_position_embeddings: - newbase = self.base * ((self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1)) ** (self.dim / (self.dim - 2)) + newbase = self.base * ((self.scaling_factor * seqlen / self.max_position_embeddings) - (self.scaling_factor - 1)) ** (self.dim / (self.dim - 2)) self.inv_freq = _create_inv_freq(self.dim, newbase, self.inv_freq.device) self._seq_len_cached = seqlen t = torch.arange(seqlen, device=device, dtype=self.inv_freq.dtype) From 1fdc88ee908beb8ae0afe17810a17b9b4d8848e2 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Mon, 7 Aug 2023 13:02:00 +0200 Subject: [PATCH 14/18] Fixing non 4bits quantization. (#785) # What does this PR do? Fixes # (issue) Fixes #784 ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- server/text_generation_server/utils/gptq/quant_linear.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/server/text_generation_server/utils/gptq/quant_linear.py b/server/text_generation_server/utils/gptq/quant_linear.py index 54fa2014..bfc91c00 100644 --- a/server/text_generation_server/utils/gptq/quant_linear.py +++ b/server/text_generation_server/utils/gptq/quant_linear.py @@ -263,7 +263,7 @@ class QuantLinear(nn.Module): self.groupsize = groupsize self.outfeatures = qweight.shape[1] - self.infeatures = qweight.shape[0] * 32 // 4 + self.infeatures = qweight.shape[0] * 32 // bits @classmethod def new(cls, bits, groupsize, infeatures, outfeatures, bias): From c4dac9f3dceceb0e6a54de4e797c1ccdb00ed8a4 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Tue, 8 Aug 2023 12:09:51 +0200 Subject: [PATCH 15/18] Update __init__.py (#794) # What does this PR do? Fixes #787 Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- server/text_generation_server/models/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/server/text_generation_server/models/__init__.py b/server/text_generation_server/models/__init__.py index 71efcab7..621652e8 100644 --- a/server/text_generation_server/models/__init__.py +++ b/server/text_generation_server/models/__init__.py @@ -89,7 +89,7 @@ def get_model( revision, quantize=quantize, dtype=dtype, - dtypetrust_remote_code=trust_remote_code, + trust_remote_code=trust_remote_code, ) if model_id.startswith("bigcode/"): From 0e8b47811e711b46fe80e6b4f5304186f83744d6 Mon Sep 17 00:00:00 2001 From: Nicolas Patry Date: Tue, 8 Aug 2023 13:43:40 +0200 Subject: [PATCH 16/18] Llama change. (#793) # What does this PR do? Reflecting https://github.com/huggingface/transformers/pull/24998 Current status wants to make sure integration tests *are* broken with this. Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. --- .../models/custom_modeling/flash_llama_modeling.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py b/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py index 2c22ea46..d0185ede 100644 --- a/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py +++ b/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py @@ -185,8 +185,11 @@ class FlashLlamaAttention(torch.nn.Module): self.hidden_size = config.hidden_size self.head_size = self.hidden_size // self.num_heads - self.rotary_emb = PositionRotaryEmbedding.load( - config=config, prefix=f"{prefix}.rotary_emb", weights=weights + # self.rotary_emb = PositionRotaryEmbedding.load( + # config=config, prefix=f"{prefix}.rotary_emb", weights=weights + # ) + self.rotary_emb = PositionRotaryEmbedding.static( + config=config, dim=self.head_size, base=10000.0, device=weights.device ) self.softmax_scale = self.head_size**-0.5 From 647ae7a7d32ae64e6b64956d83e7c5a96e854283 Mon Sep 17 00:00:00 2001 From: Merve Noyan Date: Thu, 10 Aug 2023 11:24:52 +0300 Subject: [PATCH 17/18] Setup for doc-builder and docs for TGI (#740) I added ToC for docs v1 & started setting up for doc-builder. cc @Narsil @osanseviero --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: osanseviero Co-authored-by: Mishig --- .github/workflows/build_documentation.yml | 19 +++++ .github/workflows/build_pr_documentation.yml | 17 +++++ .github/workflows/delete_doc_comment.yml | 12 ++++ .github/workflows/upload_pr_documentation.yml | 16 +++++ docs/source/_toctree.yml | 18 +++++ docs/source/basic_tutorials/consuming_tgi.md | 57 +++++++++++++++ .../basic_tutorials/gated_model_access.md | 5 ++ .../source/basic_tutorials/preparing_model.md | 22 ++++++ docs/source/index.md | 27 +++++++ docs/source/installation.md | 71 +++++++++++++++++++ docs/source/quicktour.md | 34 +++++++++ docs/source/supported_models.md | 40 +++++++++++ 12 files changed, 338 insertions(+) create mode 100644 .github/workflows/build_documentation.yml create mode 100644 .github/workflows/build_pr_documentation.yml create mode 100644 .github/workflows/delete_doc_comment.yml create mode 100644 .github/workflows/upload_pr_documentation.yml create mode 100644 docs/source/_toctree.yml create mode 100644 docs/source/basic_tutorials/consuming_tgi.md create mode 100644 docs/source/basic_tutorials/gated_model_access.md create mode 100644 docs/source/basic_tutorials/preparing_model.md create mode 100644 docs/source/index.md create mode 100644 docs/source/installation.md create mode 100644 docs/source/quicktour.md create mode 100644 docs/source/supported_models.md diff --git a/.github/workflows/build_documentation.yml b/.github/workflows/build_documentation.yml new file mode 100644 index 00000000..9d130ebb --- /dev/null +++ b/.github/workflows/build_documentation.yml @@ -0,0 +1,19 @@ +name: Build documentation + +on: + push: + branches: + - main + - doc-builder* + - v*-release + +jobs: + build: + uses: huggingface/doc-builder/.github/workflows/build_main_documentation.yml@main + with: + commit_sha: ${{ github.sha }} + package: text-generation-inference + additional_args: --not_python_module + secrets: + token: ${{ secrets.HUGGINGFACE_PUSH }} + hf_token: ${{ secrets.HF_DOC_BUILD_PUSH }} \ No newline at end of file diff --git a/.github/workflows/build_pr_documentation.yml b/.github/workflows/build_pr_documentation.yml new file mode 100644 index 00000000..e608c74a --- /dev/null +++ b/.github/workflows/build_pr_documentation.yml @@ -0,0 +1,17 @@ +name: Build PR Documentation + +on: + pull_request: + +concurrency: + group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }} + cancel-in-progress: true + +jobs: + build: + uses: huggingface/doc-builder/.github/workflows/build_pr_documentation.yml@main + with: + commit_sha: ${{ github.event.pull_request.head.sha }} + pr_number: ${{ github.event.number }} + package: text-generation-inference + additional_args: --not_python_module diff --git a/.github/workflows/delete_doc_comment.yml b/.github/workflows/delete_doc_comment.yml new file mode 100644 index 00000000..1cad807b --- /dev/null +++ b/.github/workflows/delete_doc_comment.yml @@ -0,0 +1,12 @@ +name: Delete doc comment + +on: + pull_request: + types: [ closed ] + + +jobs: + delete: + uses: huggingface/doc-builder/.github/workflows/delete_doc_comment_trigger.yml@main + with: + pr_number: ${{ github.event.number }} \ No newline at end of file diff --git a/.github/workflows/upload_pr_documentation.yml b/.github/workflows/upload_pr_documentation.yml new file mode 100644 index 00000000..b984ead2 --- /dev/null +++ b/.github/workflows/upload_pr_documentation.yml @@ -0,0 +1,16 @@ +name: Upload PR Documentation + +on: + workflow_run: + workflows: ["Build PR Documentation"] + types: + - completed + +jobs: + build: + uses: huggingface/doc-builder/.github/workflows/upload_pr_documentation.yml@main + with: + package_name: text-generation-inference + secrets: + hf_token: ${{ secrets.HF_DOC_BUILD_PUSH }} + comment_bot_token: ${{ secrets.COMMENT_BOT_TOKEN }} \ No newline at end of file diff --git a/docs/source/_toctree.yml b/docs/source/_toctree.yml new file mode 100644 index 00000000..8ee20eb0 --- /dev/null +++ b/docs/source/_toctree.yml @@ -0,0 +1,18 @@ +- sections: + - local: index + title: Text Generation Inference + - local: quicktour + title: Quick Tour + - local: installation + title: Installation + - local: supported_models + title: Supported Models and Hardware + title: Getting started +- sections: + - local: basic_tutorials/consuming_tgi + title: Consuming TGI + - local: basic_tutorials/preparing_model + title: Preparing Model for Serving + - local: basic_tutorials/gated_model_access + title: Serving Private & Gated Models + title: Tutorials diff --git a/docs/source/basic_tutorials/consuming_tgi.md b/docs/source/basic_tutorials/consuming_tgi.md new file mode 100644 index 00000000..619e0a31 --- /dev/null +++ b/docs/source/basic_tutorials/consuming_tgi.md @@ -0,0 +1,57 @@ +# Consuming Text Generation Inference + +There are many ways you can consume Text Generation Inference server in your applications. After launching, you can use the `/generate` route and make a `POST` request to get results from the server. You can also use the `/generate_stream` route if you want TGI to return a stram of tokens. You can make the requests using the tool of your preference, such as curl, Python or TypeScrpt. For a final end-to-end experience, we also open-sourced ChatUI, a chat interface for open-source models. + +## curl + +After the launch, you can query the model using either the `/generate` or `/generate_stream` routes: + +```shell +curl 127.0.0.1:8080/generate \ + -X POST \ + -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \ + -H 'Content-Type: application/json' +``` + + +## Inference Client + +[`huggingface-hub`](https://huggingface.co/docs/huggingface_hub/main/en/index) is a Python library to interact with the Hugging Face Hub, including its endpoints. It provides a nice high-level class, [`~huggingface_hub.InferenceClient`], which makes it easy to make calls to a TGI endpoint. `InferenceClient` also takes care of parameter validation and provides a simple to-use interface. + +You can simply install `huggingface-hub` package with pip. + +```python +pip install huggingface-hub +``` + +Once you start the TGI server, instantiate `InferenceClient()` with the URL to the endpoint serving the model. You can then call `text_generation()` to hit the endpoint through Python. + +```python + +from huggingface_hub import InferenceClient + +client = InferenceClient(model=URL_TO_ENDPOINT_SERVING_TGI) +client.text_generation(prompt="Write a code for snake game", model=URL_TO_ENDPOINT_SERVING_TGI) +``` + +You can check out the details of the function [here](https://huggingface.co/docs/huggingface_hub/main/en/package_reference/inference_client#huggingface_hub.InferenceClient.text_generation). + + +## ChatUI + +ChatUI is an open-source interface built for LLM serving. It offers many customization options, such as web search with SERP API and more. ChatUI can automatically consume the TGI server and even provides an option to switch between different TGI endpoints. You can try it out at [Hugging Chat](https://huggingface.co/chat/), or use the [ChatUI Docker Space](https://huggingface.co/new-space?template=huggingchat/chat-ui-template) to deploy your own Hugging Chat to Spaces. + +To serve both ChatUI and TGI in same environment, simply add your own endpoints to the `MODELS` variable in `.env.local` file inside the `chat-ui` repository. Provide the endpoints pointing to where TGI is served. + +``` +{ +// rest of the model config here +"endpoints": [{"url": "https://HOST:PORT/generate_stream"}] +} +``` + +TODO: Add screenshot + +## API documentation + +You can consult the OpenAPI documentation of the `text-generation-inference` REST API using the `/docs` route. The Swagger UI is also available [here](https://huggingface.github.io/text-generation-inference). diff --git a/docs/source/basic_tutorials/gated_model_access.md b/docs/source/basic_tutorials/gated_model_access.md new file mode 100644 index 00000000..f5858dc4 --- /dev/null +++ b/docs/source/basic_tutorials/gated_model_access.md @@ -0,0 +1,5 @@ +# Serving Private & Gated Models + +If the model you wish to serve is behind gated access or the model repository on Hugging Face Hub is private, and you have access to the model, you can provide your Hugging Face Hub access token. You can generate and copy a read token from [Hugging Face Hub tokens page](https://huggingface.co/settings/tokens) + +If you're using the CLI, set the `HUGGING_FACE_HUB_TOKEN` environment variable. diff --git a/docs/source/basic_tutorials/preparing_model.md b/docs/source/basic_tutorials/preparing_model.md new file mode 100644 index 00000000..65a2a197 --- /dev/null +++ b/docs/source/basic_tutorials/preparing_model.md @@ -0,0 +1,22 @@ +# Preparing the Model + +Text Generation Inference improves the model in several aspects. + +## Quantization + +TGI supports [bits-and-bytes](https://github.com/TimDettmers/bitsandbytes#bitsandbytes) and [GPT-Q](https://arxiv.org/abs/2210.17323) quantization. To speed up inference with quantization, simply set `quantize` flag to `bitsandbytes` or `gptq` depending on the quantization technique you wish to use. When using GPT-Q quantization, you need to point to one of the models [here](https://huggingface.co/models?search=gptq). + + +## RoPE Scaling + +RoPE scaling can be used to increase the sequence length of the model during the inference time without necessarily fine-tuning it. To enable RoPE scaling, simply pass `--rope-scaling`, `--max-input-length` and `--rope-factors` flags when running through CLI. `--rope-scaling` can take the values `linear` or `dynamic`. If your model is not fine-tuned to a longer sequence length, use `dynamic`. `--rope-factor` is the ratio between the intended max sequence length and the model's original max sequence length. Make sure to pass `--max-input-length` to provide maximum input length for extension. + + + +We recommend using `dynamic` RoPE scaling. + + + +## Safetensors + +[Safetensors](https://github.com/huggingface/safetensors) is a fast and safe persistence format for deep learning models, and is required for tensor parallelism. TGI supports `safetensors` model loading under the hood. By default, given a repository with `safetensors` and `pytorch` weights, TGI will always load `safetensors`. If there's no `pytorch` weights, TGI will convert the weights to `safetensors` format. diff --git a/docs/source/index.md b/docs/source/index.md new file mode 100644 index 00000000..097217ad --- /dev/null +++ b/docs/source/index.md @@ -0,0 +1,27 @@ +# Text Generation Inference + +Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation for the most popular open-source LLMs, including Llama, Falcon, StarCoder, BLOOM, GPT-NeoX, and T5. + +![Text Generation Inference](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/TGI.png) + +Text Generation Inference implements many optimizations and features, such as: + +- Simple launcher to serve most popular LLMs +- Production ready (distributed tracing with Open Telemetry, Prometheus metrics) +- Tensor Parallelism for faster inference on multiple GPUs +- Token streaming using Server-Sent Events (SSE) +- Continuous batching of incoming requests for increased total throughput +- Optimized transformers code for inference using [Flash Attention](https://github.com/HazyResearch/flash-attention) and [Paged Attention](https://github.com/vllm-project/vllm) on the most popular architectures +- Quantization with [bitsandbytes](https://github.com/TimDettmers/bitsandbytes) and [GPT-Q](https://arxiv.org/abs/2210.17323) +- [Safetensors](https://github.com/huggingface/safetensors) weight loading +- Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226) +- Logits warper (temperature scaling, top-p, top-k, repetition penalty) +- Stop sequences +- Log probabilities + + +Text Generation Inference is used in production by multiple projects, such as: + +- [Hugging Chat](https://github.com/huggingface/chat-ui), an open-source interface for open-access models, such as Open Assistant and Llama +- [OpenAssistant](https://open-assistant.io/), an open-source community effort to train LLMs in the open +- [nat.dev](http://nat.dev/), a playground to explore and compare LLMs. diff --git a/docs/source/installation.md b/docs/source/installation.md new file mode 100644 index 00000000..4105acf4 --- /dev/null +++ b/docs/source/installation.md @@ -0,0 +1,71 @@ +# Installation + +This section explains how to install the CLI tool as well as installing TGI from source. **The strongly recommended approach is to use Docker, as it does not require much setup. Check [the Quick Tour](./quicktour) to learn how to run TGI with Docker.** + +## Install CLI + +TODO + + +## Local Installation from Source + +Before you start, you will need to setup your environment, and install Text Generation Inference. Text Generation Inference is tested on **Python 3.9+**. + +Text Generation Inference is available on pypi, conda and GitHub. + +To install and launch locally, first [install Rust](https://rustup.rs/) and create a Python virtual environment with at least +Python 3.9, e.g. using conda: + +```shell +curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh + +conda create -n text-generation-inference python=3.9 +conda activate text-generation-inference +``` + +You may also need to install Protoc. + +On Linux: + +```shell +PROTOC_ZIP=protoc-21.12-linux-x86_64.zip +curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP +sudo unzip -o $PROTOC_ZIP -d /usr/local bin/protoc +sudo unzip -o $PROTOC_ZIP -d /usr/local 'include/*' +rm -f $PROTOC_ZIP +``` + +On MacOS, using Homebrew: + +```shell +brew install protobuf +``` + +Then run to install Text Generation Inference: + +```shell +BUILD_EXTENSIONS=True make install # Install repository and HF/transformer fork with CUDA kernels +``` + + + +On some machines, you may also need the OpenSSL libraries and gcc. On Linux machines, run: + +```shell +sudo apt-get install libssl-dev gcc -y +``` + + + +Once installation is done, simply run: + +```shell +make run-falcon-7b-instruct +``` + +This will serve Falcon 7B Instruct model from the port 8080, which we can query. + +To see all options to serve your models, check in the [codebase](https://github.com/huggingface/text-generation-inference/blob/main/launcher/src/main.rs) or the CLI: +``` +text-generation-launcher --help +``` diff --git a/docs/source/quicktour.md b/docs/source/quicktour.md new file mode 100644 index 00000000..31185a2d --- /dev/null +++ b/docs/source/quicktour.md @@ -0,0 +1,34 @@ +# Quick Tour + +The easiest way of getting started is using the official Docker container. Install Docker following [their installation instructions](https://docs.docker.com/get-docker/). + +Let's say you want to deploy [Falcon-7B Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct) model with TGI. Here is an example on how to do that: + +```shell +model=tiiuae/falcon-7b-instruct +volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run + +docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:1.0.0 --model-id $model +``` + + + +To use GPUs, you need to install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) . We also recommend using NVIDIA drivers with CUDA version 11.8 or higher. + + + +Once TGI is running, you can use the `generate` endpoint by doing requests. To learn more about how to query the endpoints, check the [Consuming TGI](./basic_tutorials/consuming_tgi) section. + +```shell +curl 127.0.0.1:8080/generate -X POST -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' -H 'Content-Type: application/json' +``` + + + +To see all possible flags and options, you can use the `--help` flag. It's possible to configure the number of shards, quantization, generation parameters, and more. + +```shell +docker run ghcr.io/huggingface/text-generation-inference:1.0.0 --help +``` + + \ No newline at end of file diff --git a/docs/source/supported_models.md b/docs/source/supported_models.md new file mode 100644 index 00000000..d997c8d8 --- /dev/null +++ b/docs/source/supported_models.md @@ -0,0 +1,40 @@ +# Supported Models and Hardware + +Text Generation Inference enables serving optimized models on specific hardware for the highest performance. The following sections list which models are hardware are supported. + +## Supported Models + +The following models are optimized and can be served with TGI, which uses custom CUDA kernels for better inference. You can add the flag `--disable-custom-kernels` at the end of the `docker run` command if you wish to disable them. + +- [BLOOM](https://huggingface.co/bigscience/bloom) +- [FLAN-T5](https://huggingface.co/google/flan-t5-xxl) +- [Galactica](https://huggingface.co/facebook/galactica-120b) +- [GPT-Neox](https://huggingface.co/EleutherAI/gpt-neox-20b) +- [Llama](https://github.com/facebookresearch/llama) +- [OPT](https://huggingface.co/facebook/opt-66b) +- [SantaCoder](https://huggingface.co/bigcode/santacoder) +- [Starcoder](https://huggingface.co/bigcode/starcoder) +- [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b) +- [Falcon 40B](https://huggingface.co/tiiuae/falcon-40b) +- [MPT](https://huggingface.co/mosaicml/mpt-30b) +- [Llama V2](https://huggingface.co/meta-llama) + +If the above list lacks the model you would like to serve, depending on the model's pipeline type, you can try to initialize and serve the model anyways to see how well it performs, but performance isn't guaranteed for non-optimized models: + +```python +# for causal LMs/text-generation models +AutoModelForCausalLM.from_pretrained(, device_map="auto")` +# or, for text-to-text generation models +AutoModelForSeq2SeqLM.from_pretrained(, device_map="auto") +``` + + +## Supported Hardware + +TGI optimized models are supported on NVIDIA [A100](https://www.nvidia.com/en-us/data-center/a100/), [A10G](https://www.nvidia.com/en-us/data-center/products/a10-gpu/) and [T4](https://www.nvidia.com/en-us/data-center/tesla-t4/) GPUs with CUDA 11.8+. Note that you have to install [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) to use it. For other hardware, continuous batching will still apply, but some operations like flash attention and paged attention will not be executed. + +TGI is also supported on the following AI hardware accelerators: +- *Habana first-gen Gaudi and Gaudi2:* check out this [example](https://github.com/huggingface/optimum-habana/tree/main/text-generation-inference) how to serve models with TGI on Gaudi and Gaudi2 with [Optimum Habana](https://huggingface.co/docs/optimum/habana/index) + + + From 8bdb16ee9a658b33cc9def5d3062c63c9865163d Mon Sep 17 00:00:00 2001 From: ivarflakstad <69173633+ivarflakstad@users.noreply.github.com> Date: Thu, 10 Aug 2023 10:52:50 +0200 Subject: [PATCH 18/18] Use destructuring in router arguments to avoid '.0' (#798) # What does this PR do? This is purely code style - not anything important. Instead of writing `req.0` all over we can use [descructuring](https://doc.rust-lang.org/rust-by-example/flow_control/match/destructuring/destructure_structures.html) to access the contained value that we actually want. (Destructuring in function parameters [here](https://doc.rust-lang.org/reference/items/functions.html#function-parameters)) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. @OlivierDehaene --- router/src/server.rs | 54 +++++++++++++++++++++----------------------- 1 file changed, 26 insertions(+), 28 deletions(-) diff --git a/router/src/server.rs b/router/src/server.rs index 9af94951..e609821c 100644 --- a/router/src/server.rs +++ b/router/src/server.rs @@ -54,15 +54,13 @@ example = json ! ({"error": "Incomplete generation"})), )] #[instrument(skip(infer, req))] async fn compat_generate( - default_return_full_text: Extension, + Extension(default_return_full_text): Extension, infer: Extension, - req: Json, + Json(mut req): Json, ) -> Result)> { - let mut req = req.0; - // default return_full_text given the pipeline_tag if req.parameters.return_full_text.is_none() { - req.parameters.return_full_text = Some(default_return_full_text.0) + req.parameters.return_full_text = Some(default_return_full_text) } // switch on stream @@ -71,9 +69,9 @@ async fn compat_generate( .await .into_response()) } else { - let (headers, generation) = generate(infer, Json(req.into())).await?; + let (headers, Json(generation)) = generate(infer, Json(req.into())).await?; // wrap generation inside a Vec to match api-inference - Ok((headers, Json(vec![generation.0])).into_response()) + Ok((headers, Json(vec![generation])).into_response()) } } @@ -135,7 +133,7 @@ example = json ! ({"error": "Incomplete generation"})), #[instrument( skip_all, fields( -parameters = ? req.0.parameters, +parameters = ? req.parameters, total_time, validation_time, queue_time, @@ -146,29 +144,29 @@ seed, )] async fn generate( infer: Extension, - req: Json, + Json(req): Json, ) -> Result<(HeaderMap, Json), (StatusCode, Json)> { let span = tracing::Span::current(); let start_time = Instant::now(); metrics::increment_counter!("tgi_request_count"); - tracing::debug!("Input: {}", req.0.inputs); + tracing::debug!("Input: {}", req.inputs); - let compute_characters = req.0.inputs.chars().count(); + let compute_characters = req.inputs.chars().count(); let mut add_prompt = None; - if req.0.parameters.return_full_text.unwrap_or(false) { - add_prompt = Some(req.0.inputs.clone()); + if req.parameters.return_full_text.unwrap_or(false) { + add_prompt = Some(req.inputs.clone()); } - let details = req.0.parameters.details || req.0.parameters.decoder_input_details; + let details = req.parameters.details || req.parameters.decoder_input_details; // Inference - let (response, best_of_responses) = match req.0.parameters.best_of { + let (response, best_of_responses) = match req.parameters.best_of { Some(best_of) if best_of > 1 => { - let (response, best_of_responses) = infer.generate_best_of(req.0, best_of).await?; + let (response, best_of_responses) = infer.generate_best_of(req, best_of).await?; (response, Some(best_of_responses)) } - _ => (infer.generate(req.0).await?, None), + _ => (infer.generate(req).await?, None), }; // Token details @@ -321,7 +319,7 @@ content_type = "text/event-stream"), #[instrument( skip_all, fields( -parameters = ? req.0.parameters, +parameters = ? req.parameters, total_time, validation_time, queue_time, @@ -331,8 +329,8 @@ seed, ) )] async fn generate_stream( - infer: Extension, - req: Json, + Extension(infer): Extension, + Json(req): Json, ) -> ( HeaderMap, Sse>>, @@ -341,9 +339,9 @@ async fn generate_stream( let start_time = Instant::now(); metrics::increment_counter!("tgi_request_count"); - tracing::debug!("Input: {}", req.0.inputs); + tracing::debug!("Input: {}", req.inputs); - let compute_characters = req.0.inputs.chars().count(); + let compute_characters = req.inputs.chars().count(); let mut headers = HeaderMap::new(); headers.insert("x-compute-type", "gpu+optimized".parse().unwrap()); @@ -359,24 +357,24 @@ async fn generate_stream( let mut error = false; let mut add_prompt = None; - if req.0.parameters.return_full_text.unwrap_or(false) { - add_prompt = Some(req.0.inputs.clone()); + if req.parameters.return_full_text.unwrap_or(false) { + add_prompt = Some(req.inputs.clone()); } - let details = req.0.parameters.details; + let details = req.parameters.details; - let best_of = req.0.parameters.best_of.unwrap_or(1); + let best_of = req.parameters.best_of.unwrap_or(1); if best_of != 1 { let err = InferError::from(ValidationError::BestOfStream); metrics::increment_counter!("tgi_request_failure", "err" => "validation"); tracing::error!("{err}"); yield Ok(Event::from(err)); - } else if req.0.parameters.decoder_input_details { + } else if req.parameters.decoder_input_details { let err = InferError::from(ValidationError::PrefillDetailsStream); metrics::increment_counter!("tgi_request_failure", "err" => "validation"); tracing::error!("{err}"); yield Ok(Event::from(err)); } else { - match infer.generate_stream(req.0).instrument(info_span!(parent: &span, "async_stream")).await { + match infer.generate_stream(req).instrument(info_span!(parent: &span, "async_stream")).await { // Keep permit as long as generate_stream lives Ok((_permit, mut response_stream)) => { // Server-Sent Event stream