TensorFlowLaboratory issues

已经跑出tfrecords格式，接着用官网的train.py训练，报了下面的错误，请问是导出tfrecords格式有问题吗 tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP] [[Node: case/cond/decode_image/cond_jpeg/cond_png/cond_gif/Assert_1/Assert = Assert[T=[DT_STRING], summarize=3, _device="/job:localhost/replica:0/task:0/device:CPU:0"](case/cond/decode_image/cond_jpeg/cond_png/cond_gif/is_bmp, case/cond/decode_image/cond_jpeg/cond_png/cond_gif/Assert_1/Assert/data_0)]]

guandeng

tf.queueRunner 读取tfrecord数据在GPU下的效率

1

请问下有没有测过程序运行时GPU的使用效率？我自己在用tfrecord和queue方式读写数据进行训练的时候，如果： with tf.device('/gpu:0'): sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) 的话，GPU只使用了一点，20%，大部分仍然用了CPU去算；如果强制GPU的话 with tf.device('/gpu:0'): sess = tf.Session() 会报如下错误，应该时某些任务不支持GPU上算导致， InvalidArgumentError (see above for traceback): Cannot assign a device to node 'batch': Could not...

juventi