mean , variance = tf.nn.moments(X_train, axes = 1, keep_dims = True)
我正在尝试使用 tf.nn.moments() 获取均值和方差，如上所示。但是，我遇到了以下错误:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-43-fc383f99b15b> in <module>()
33 Y_train = Y_train.reshape(1,355)
34 X_mean = tf.reduce_mean(X_train, axis = 1, keepdims = True)
---> 35 mean , variance = tf.nn.moments(X_train, axes = 1, keep_dims = True)
36 X_train = tf.divide(tf.subtract(X_train,mean),tf.sqrt(variance))
37 #Y_train = Y_train/(Y_train.max(axis = 1, keepdims = True))
/Users/abhinandanchiney/anaconda2/lib/python2.7/site- packages/tensorflow/python/ops/nn_impl.pyc in moments(x, axes, shift, name, keep_dims)
664 # sufficient statistics. As a workaround we simply perform the operations
665 # on 32-bit floats before converting the mean and variance back to fp16
--> 666 y = math_ops.cast(x, dtypes.float32) if x.dtype == dtypes.float16 else x
667 # Compute true mean while keeping the dims for proper broadcasting.
668 mean = math_ops.reduce_mean(y, axes, keepdims=True, name="mean")
TypeError: data type not understood
请在我出错的地方提供帮助。
最佳答案
tf.nn.moments期待一个张量，而不是一个 numpy 数组:
Args:
x: A Tensor.
试试这个:
x = tf.convert_to_tensor(X_train)
mean , variance = tf.nn.moments(x, axes = 1, keep_dims = True)
关于python-2.7 - tensorflow 中不理解的数据类型，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/49137905/