张量流中不理解的数据类型

Question

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

请帮助我哪里出错了。

Answer 1

tf.nn.moments 需要张量，而不是 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)

张量流中不理解的数据类型

Data Type not understood in tensorflow

neural-network

python-2.7

tensorflow

deeplearning4j