From 7816a47697fdcc4a21b257197fd4695adb5f20d4 Mon Sep 17 00:00:00 2001 From: OlivierDehaene <23298448+OlivierDehaene@users.noreply.github.com> Date: Thu, 6 Apr 2023 17:07:58 +0200 Subject: [PATCH] fix llama tokenizer --- server/poetry.lock | 57 ++++++++++++++++++- server/pyproject.toml | 1 + .../models/flash_llama.py | 25 +++++--- .../models/flash_santacoder.py | 8 +++ 4 files changed, 83 insertions(+), 8 deletions(-) diff --git a/server/poetry.lock b/server/poetry.lock index e04ae75c..49b9d39d 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -538,6 +538,19 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-g testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy 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transformers.models.llama import LlamaTokenizer +from typing import Optional, List from text_generation_server.models import FlashCausalLM from text_generation_server.models.custom_modeling.flash_llama_modeling import ( @@ -37,7 +38,7 @@ class FlashLlama(FlashCausalLM): if quantize: raise NotImplementedError("FlashLlama does not support quantization") - tokenizer = AutoTokenizer.from_pretrained( + tokenizer = LlamaTokenizer.from_pretrained( model_id, revision=revision, padding_side="left" ) @@ -59,8 +60,10 @@ class FlashLlama(FlashCausalLM): self.load_weights( model, filenames, + device, + dtype ) - self.model = model.eval().to(device).to(dtype) + self.model = model.eval() super(FlashCausalLM, self).__init__( tokenizer=tokenizer, @@ -71,10 +74,14 @@ class FlashLlama(FlashCausalLM): def load_weights( model, filenames: List[Path], + device: torch.device, + dtype: torch.dtype, ): for filename in filenames: state_dict = torch.load(filename, map_location="cpu") for key, value in state_dict.items(): + value = value.to(device).to(dtype) + layer_name = ".".join(key.split(".")[:4]) # Fused qkv @@ -130,6 +137,8 @@ class FlashLlama(FlashCausalLM): else: module._buffers[param_name] = value + del value + torch.cuda.empty_cache() model.post_load_weights() @@ -149,7 +158,7 @@ class FlashLlamaSharded(FlashLlama): if quantize: raise NotImplementedError("FlashLlama does not support quantization") - tokenizer = AutoTokenizer.from_pretrained( + tokenizer = LlamaTokenizer.from_pretrained( model_id, revision=revision, padding_side="left" ) @@ -169,10 +178,11 @@ class FlashLlamaSharded(FlashLlama): filenames, quantize=quantize, device=device, + dtype=dtype, rank=self.rank, world_size=self.world_size, ) - self.model = model.eval().to(dtype) + self.model = model.eval() torch.distributed.barrier(group=self.process_group) super(FlashCausalLM, self).__init__( tokenizer=tokenizer, @@ -185,6 +195,7 @@ class FlashLlamaSharded(FlashLlama): filenames: List[str], quantize: bool, device: torch.device, + dtype: torch.dtype, rank: int, world_size: int, ): @@ -240,7 +251,7 @@ class FlashLlamaSharded(FlashLlama): except: tensor = f.get_tensor(name) - tensor = tensor.contiguous() + tensor = tensor.contiguous().to(dtype) try: current_parameter_tensor = module._parameters[param_name] diff --git a/server/text_generation_server/models/flash_santacoder.py b/server/text_generation_server/models/flash_santacoder.py index f0207d55..106195c2 100644 --- a/server/text_generation_server/models/flash_santacoder.py +++ b/server/text_generation_server/models/flash_santacoder.py @@ -56,6 +56,8 @@ class FlashSantacoder(FlashCausalLM): self.load_weights( model, filenames, + device, + dtype, ) self.model = model.eval().to(device).to(dtype) @@ -68,10 +70,14 @@ class FlashSantacoder(FlashCausalLM): def load_weights( model: FlashSantacoderForCausalLM, filenames: List[Path], + device: torch.device, + dtype: torch.dtype, ): for filename in filenames: state_dict = torch.load(filename, map_location="cpu") for key, value in state_dict.items(): + value = value.to(device).to(dtype) + layer_name = ".".join(key.split(".")[:4]) # Fused qkv @@ -141,6 +147,8 @@ class FlashSantacoder(FlashCausalLM): else: module._buffers[param_name] = value + del value + torch.cuda.empty_cache() model.post_load_weights()