To set gpu memory rate manually when using keras

from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession
config = ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.8
session = InteractiveSession(config=config)

텐서플로, 케라스 GPU 사용하는지 확인

https://rfriend.tistory.com/425


import numpy as np
import pandas as pd
import keras
import tensorflow as tf
from IPython.display import display
import PIL #Pillow

# How to check if the code is running on GPU or CPU?
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())

tf.test.is_gpu_available(
    cuda_only=False,
    min_cuda_compute_capability=None
)
# Returns:
# True if a GPU device of the requested kind is available.