有没有在GPU上运行Tensorflow代码？

Question

这是我的代码，我想使用GPU作为我的代码。目前它正在CPU上运行

    elf.graph = tf.Graph()
    with self.graph.as_default():
        self.face_graph = tf.GraphDef()
        fid=tf.gfile.GFile(self.facenet_model, 'rb')
        serialized_graph = fid.read()
        self.face_graph.ParseFromString(serialized_graph)
        tf.import_graph_def(self.face_graph, name='')
        self.facenet_sess = tf.Session(graph=self.graph)
        self.images_placeholder = self.graph.get_tensor_by_name("input:0")
        self.embeddings = self.graph.get_tensor_by_name("embeddings:0")

Answer 1

tensorflow的网站上有一个完整的指南：https://www.tensorflow.org/guide/gpu

确认tf可以看到您的gpu：

import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))

查看您的GPU名称：

from tensorflow.python.client import device_lib
device_lib.list_local_devices()

进行一些手动放置：

tf.debugging.set_log_device_placement(True)

gpus = tf.config.experimental.list_logical_devices('GPU')
if gpus:
  # Replicate your computation on multiple GPUs
  c = []
  for gpu in gpus:
    with tf.device(gpu.name):
      a = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
      b = tf.constant([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
      c.append(tf.matmul(a, b))

  with tf.device('/CPU:0'):
    matmul_sum = tf.add_n(c)

  print(matmul_sum)

Answer 2

把它包起来

with tf.device('/GPU:0'):
    ....