Set default dtype to half
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de0fabbc5c
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@ -1,3 +1,6 @@
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from typing import Union
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import torch
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import torch.nn as nn
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from cacheflow.models.opt import OPTForCausalLM
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@ -6,9 +9,23 @@ MODEL_CLASSES = {
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'opt': OPTForCausalLM,
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}
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STR_DTYPE_TO_TORCH_DTYPE = {
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'half': torch.half,
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'float': torch.float,
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'float16': torch.float16,
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'float32': torch.float32,
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}
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def get_model(model_name: str) -> nn.Module:
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def get_model(
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model_name: str,
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dtype: Union[torch.dtype, str],
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) -> nn.Module:
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if isinstance(dtype, str):
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torch_dtype = STR_DTYPE_TO_TORCH_DTYPE[dtype.lower()]
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else:
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torch_dtype = dtype
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for model_class, model in MODEL_CLASSES.items():
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if model_class in model_name:
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return model.from_pretrained(model_name)
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return model.from_pretrained(model_name, torch_dtype=torch_dtype)
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raise ValueError(f'Invalid model name: {model_name}')
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@ -14,6 +14,7 @@ class Controller:
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block_size: int,
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num_gpu_blocks: int,
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num_cpu_blocks: int,
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dtype: str = 'half',
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) -> None:
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self.node_id = node_id
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self.num_workers = num_workers
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@ -35,6 +36,7 @@ class Controller:
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block_size=block_size,
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num_gpu_blocks=num_gpu_blocks,
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num_cpu_blocks=num_cpu_blocks,
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dtype=dtype,
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)
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self.workers.append(worker)
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@ -17,6 +17,7 @@ class Worker:
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block_size: int,
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num_gpu_blocks: int,
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num_cpu_blocks: int,
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dtype: str,
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) -> None:
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self.worker_id = worker_id
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self.gpu_id = gpu_id
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@ -26,7 +27,7 @@ class Worker:
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# Initialize the model.
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# FIXME(woosuk): This is a hack.
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self.model = get_model(model_name).to(device=gpu_id)
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self.model = get_model(model_name, dtype=dtype).to(device=self.device)
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self.num_layers = self.model.config.num_hidden_layers
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self.num_heads = self.model.config.num_attention_heads
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self.head_size = self.model.config.hidden_size // self.num_heads
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