Question

我正在大型数据库上训练ResNet-50网络。当检查我的GPU的使用百分比时，我发现它的变化范围在0％和4％之间！虽然我正在使用tensorflow-GPU。这是我的CPU和GPU使用率：

当我运行以下两个命令行时：

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

我明白了

 [name: "/device:CPU:0"
 device_type: "CPU"
 memory_limit: 268435456
 locality {
  }
 incarnation: 4622338339054789933
 , name: "/device:GPU:0"
 device_type: "GPU"
 memory_limit: 13594420839
 locality {
 bus_id: 1
 links {
 }
 }
 incarnation: 17927686236275886371
 physical_device_desc: "device: 0, name: Quadro 
 P5000, pci bus id: 0000:01:00.0, compute 
 capability: 6.1"
 ]

当我跑步时英伟达我懂了

任何人都可以通过简单的说明帮助我，如何正确，完全利用我的GPU？我必须提到的是，我在训练期间使用ImageDataGenerator对象及其两个方法flow_from_directory和fit_generator，因此我可以设置特定的参数（例如worker参数）来提高GPU的使用率。这是我使用ImageDataGenerator的方式

  input_imgen = ImageDataGenerator()
  train_it = input_imgen.flow_from_directory(directory=data_path_l,target_size= 
  (224,224),
                                      color_mode="rgb",
                                      batch_size=batch_size,
                                      class_mode="categorical",
                                      shuffle=False,
                                      )

  valid_it = input_imgen.flow_from_directory(directory=test_data_path_l,target_size= 
  (224,224),
                                      color_mode="rgb",
                                      batch_size=batch_size,
                                      class_mode="categorical",
                                      shuffle=False,
                                      )

  model = resnet.ResnetBuilder.build_resnet_50((img_channels, img_rows, 
  img_cols), num_classes)
  model.compile(loss='categorical_crossentropy',
          optimizer='adam',
          metrics=['accuracy'])

  filepath=".\conv2D_models\weights-improvement-{epoch:02d}- 
  {val_acc:.2f}.hdf5"

  mc = ModelCheckpoint(filepath, save_weights_only=False, verbose=1, 
  monitor='loss', mode='min')

  history=model.fit_generator(train_it,
                    steps_per_epoch= train_images // batch_size,
                    validation_data = valid_it, 
                    validation_steps = val_images// batch_size,
                    epochs = epochs,callbacks=[mc],
                    shuffle=False)

如何确保我的代码使用GPU的全部容量？

0 个答案: