Simplication of GPU allocation for Tensorflow2
Project description
tf_alloc
Simpliying GPU allocation for Tensorflow
⭐️ Why tf_alloc? Problems?
- Compare to pytorch, tensorflow allocate all GPU memory to single training.
- However, it is too much waste because, some training does not use whole GPU memory.
- To solve this problem, TF engineers use two methods.
- Limit to use only single GPU
- Limit the use of only a certain percentage of GPUs.
- However, these methods require complex code and memory management.
⭐️ Why tf_alloc? How to solve?
tf_alloc simplfy and automate GPU allocation using two methods.
⭐️ How to allocate?
- Before using tf_alloc, you have to install tensorflow fits for your environment.
- This library does not install specific tensorflow version.
# On the top of the code
from tf_alloc import allocate as talloc
talloc(gpu=1, percentage=0.5)
import tensorflow as tf
""" your code"""
It is only code for allocating GPU in certain percentage.
Parameters:
- gpu = which gpu you want to use (if you have two gpu than [0, 1] is possible)
- percentage = the percentage of memory usage on single gpu. 1.0 for maximum use.
⭐️ Additional Function.
GET GPU Objects
gpu_objs = get_gpu_objects()
- To use this code, you can get gpu objects that contains gpu information.
- You can set GPU backend by using this function.
GET CURRENT STATE
Defualt
current(
gpu_id = False,
total_memory=False,
used = False,
free = False,
percentage_of_use = False,
percentage_of_free = False,
)
- You can use this functions to see current GPU state and possible maximum allocation percentage.
- Without any parameters, than it only visualize possible maximum allocation percentage.
- It is cmd line visualizer. It doesn't return values.
Parameters
- gpu_id = visualize the gpu id number
- total_memory = visualize the total memory of GPU
- used = visualize the used memory of GPU
- free = visualize the free memory of GPU
- percentage_of_used = visualize the percentage of used memory of GPU
- percentage_of_free = visualize the percentage of free memory of GPU
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