问在GPU上使用tensorflow训练模型，使用Adadelta优化器无法工作。但当我用Adam替换Adadelta时，似乎没有任何问题。

EN

InvalidArgumentError (see above for traceback): Cannot assign a device for operation 'embedding_matrix_de/read': Could not satisfy explicit device specification '' because the node was colocated with a group of nodes that required incompatible device '/job:localhost/replica:0/task:0/device:GPU:0'
Colocation Debug Info:
Colocation group had the following types and devices: 
UnsortedSegmentSum: GPU CPU 
Unique: GPU CPU 
Shape: GPU CPU 
Cast: GPU CPU 
StridedSlice: GPU CPU 
GatherV2: GPU CPU 
SparseApplyAdadelta: CPU 
Const: GPU CPU 
Identity: CPU 
VariableV2: GPU CPU 

Colocation members and user-requested devices:
  embedding_matrix_de (VariableV2) 
  embedding_matrix_de/read (Identity) 
  embedding_lookup/axis (Const) 
  embedding_lookup (GatherV2) 
  gradients/embedding_lookup_grad/Shape (Const) 
  gradients/embedding_lookup_grad/ToInt32 (Cast) 
  embedding_matrix_de/Adadelta (VariableV2) 
  embedding_matrix_de/Adadelta_1 (VariableV2) 
  Adadelta/update_embedding_matrix_de/Unique (Unique) 
  Adadelta/update_embedding_matrix_de/Shape (Shape) 
  Adadelta/update_embedding_matrix_de/strided_slice/stack (Const) 
  Adadelta/update_embedding_matrix_de/strided_slice/stack_1 (Const) 
  Adadelta/update_embedding_matrix_de/strided_slice/stack_2 (Const) 
  Adadelta/update_embedding_matrix_de/strided_slice (StridedSlice) 
  Adadelta/update_embedding_matrix_de/UnsortedSegmentSum         (UnsortedSegmentSum) 
  Adadelta/update_embedding_matrix_de/SparseApplyAdadelta (SparseApplyAdadelta) 

 [[Node: embedding_matrix_de/read = Identity[T=DT_FLOAT, _class=["loc:@embedding_matrix_de"]](embedding_matrix_de)]]

....
embedding_matrix_decode = tf.get_variable(
name="embedding_matrix_de",
shape=[trainVocabSize, embedding_size],
dtype=tf.float32)
....
optimizer = tf.train.AdadeltaOptimizer()
....