无法评估张量流中由复稀疏张量获得的稠密张量

Question

我无法评估/打印/运行张量流库中复杂稀疏张量获得的稠密张量。我目前在macosx中使用tensorflow的构建＃234（仅限cpu）。

import tensorflow as tf 

a = tf.SparseTensor(indices=[[0, 0, 0], [1, 2, 1]], values=[1.0+2j, 2.0], shape=[3, 4, 2]) 

b = tf.sparse_tensor_to_dense(a, default_value=0.0) 

sess = tf.Session() 

sess.run(b) 

返回以下错误：

InvalidArgumentError (see above for traceback): No OpKernel was registered to support Op 'SparseToDense' with these attrs. Registered kernels: 
device='CPU'; T in [DT_INT64]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_INT64]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_INT32]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_INT32]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_UINT16]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_UINT16]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_INT16]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_INT16]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_UINT8]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_UINT8]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_INT8]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_INT8]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_HALF]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_HALF]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_FLOAT]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_FLOAT]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_DOUBLE]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_DOUBLE]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_BOOL]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_BOOL]; Tindices in [DT_INT64] 
device='CPU'; T in [DT_STRING]; Tindices in [DT_INT32] 
device='CPU'; T in [DT_STRING]; Tindices in [DT_INT64] 

[[Node: SparseToDense_3 = SparseToDense[T=DT_COMPLEX128, Tindices=DT_INT64, validate_indices=true](SparseTensor_2/indices, SparseTensor_2/shape, SparseTensor_2/values, SparseToDense_3/default_value)]] 

我也试过：

br = tf.real(b) 

sess.run(br) 

然而，这给出了同样的错误如上。

但是请注意，下列工作正常：

x = tf.ones((3,3), dtype=tf.complex128) 

sess.run(x) 

感谢您的帮助提前！

Answer 1

看起来像tf.sparse_tensor_to_dense不支持复数。我曾尝试损失+ 2j组件，并且它工作正常。我认为错误转储试图告诉你，sparse_tensor_to_dense不支持复杂类型，并列出它支持的类型。