* fix typo deepspeed/runtime

* fix some typo

---------

Co-authored-by: Olatunji Ruwase <olruwase@microsoft.com>
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digger yu 2023-06-06 06:22:52 +08:00 коммит произвёл GitHub
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@ -72,12 +72,12 @@ def get_accelerator():
accelerator_name = 'xpu'
except ImportError as e:
# We need a way to choose between CUDA_Accelerator and CPU_Accelerator
# Currently we detect whether intel_etension_for_pytorch is installed
# in the environment and use CPU_Accelerator if the answewr is True.
# Currently we detect whether intel_extension_for_pytorch is installed
# in the environment and use CPU_Accelerator if the answer is True.
# An alternative might be detect whether CUDA device is installed on
# the system but this comes with two pitfalls:
# 1. the system may not have torch pre-installed, so
# get_accelerator().is_avaiable() may not work.
# get_accelerator().is_available() may not work.
# 2. Some scenario like install on login node (without CUDA device)
# and run on compute node (with CUDA device) may cause mismatch
# between installation time and runtime.

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@ -107,7 +107,7 @@ python train.py --actor-model facebook/opt-13b --reward-model facebook/opt-350m
```
Human: Do you know Microsoft?
Assistant: Yes, Im a big fan of Microsoft. What about them?
Human: Can you explian it to a 6-year old child? I wonder how I should describe it
Human: Can you explain it to a 6-year old child? I wonder how I should describe it
Assistant: Sure, I can try. Microsoft is a company that makes computers, and they make a program called “Windows” which
is the operating system that runs on the computer. Its like the “brain” of the computer. Its where all the
programs and files are stored. Its also where youll find the “start” button, which is where youll start to

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@ -19,9 +19,9 @@ INIT_NUM = 2
class ModelBasedTuner(BaseTuner):
"""Exploring the search space with a cost model"""
def __init__(self, exps: list, resource_manager, metric, tuning_sapce):
def __init__(self, exps: list, resource_manager, metric, tuning_space):
super().__init__(exps, resource_manager, metric)
self.tuning_space = tuning_sapce
self.tuning_space = tuning_space
self.best_iter = 0
self.all_configs = [e['ds_config'] for e in exps]