TypeError：传递给参数'a'的值使DataType不在允许值列表中(TypeError: Value passed to parameter 'a' h

TypeError：传递给参数'a'的值使DataType不在允许值列表中(TypeError: Value passed to parameter 'a' has DataType not in list of allowed values)

我有以下代码：

_X = np.arange(1, 7).reshape((2, 3)) _Y = np.arange(1, 7).reshape((3, 2)) X = tf.convert_to_tensor(_X) Y = tf.convert_to_tensor(_Y) # Matrix multiplication out1 = tf.matmul(X, Y)

对于它，我收到此错误：

TypeError: Value passed to parameter 'a' has DataType int64 not in list of allowed values: float16, float32, float64, int32, complex64, complex128

我使用的是最新版本的Tensorflow。 可能是什么问题？

I have the following code:

_X = np.arange(1, 7).reshape((2, 3)) _Y = np.arange(1, 7).reshape((3, 2)) X = tf.convert_to_tensor(_X) Y = tf.convert_to_tensor(_Y) # Matrix multiplication out1 = tf.matmul(X, Y)

For it, I am getting this error:

TypeError: Value passed to parameter 'a' has DataType int64 not in list of allowed values: float16, float32, float64, int32, complex64, complex128

I am using the latest version of Tensorflow. What could be the issue?

最满意答案

输入到tf.matmul只接受这些dtypes：

a: Tensor of type float16, float32, float64, int32, complex64, complex128 and rank > 1.

将X和Y的dtype更改为上面的dtypes有效。

import tensorflow as tf import numpy as np _X = np.arange(1, 7).reshape((2, 3)) _Y = np.arange(1, 7).reshape((3, 2)) X = tf.convert_to_tensor(_X,dtype=tf.int32) Y = tf.convert_to_tensor(_Y,dtype=tf.int32) # Matrix multiplication out1 = tf.matmul(X, Y) sess = tf.Session() print(sess.run(out1))

Inputs to tf.matmul accepts only these dtypes :

a: Tensor of type float16, float32, float64, int32, complex64, complex128 and rank > 1.

Changing dtype of X and Y to above dtypes works.

import tensorflow as tf import numpy as np _X = np.arange(1, 7).reshape((2, 3)) _Y = np.arange(1, 7).reshape((3, 2)) X = tf.convert_to_tensor(_X,dtype=tf.int32) Y = tf.convert_to_tensor(_Y,dtype=tf.int32) # Matrix multiplication out1 = tf.matmul(X, Y) sess = tf.Session() print(sess.run(out1))