我通过设置sparse=True
构建了一个具有稀疏输入的模型,但是在输入稀疏张量时出现了错误。该模型已成功构建但无法运行。 keras现在真的支持稀疏输入吗?
环境:
输入代码:
Input(shape=(self.options.dim_feature[i],), name='input_{}'.format(i), dtype='float', sparse=True)
我提供的数据:
def convert_sparse_matrix_to_sparse_tensor(X):
coo = X.tocoo()
indices = np.mat([coo.row, coo.col]).transpose()
return SparseTensor(indices, coo.data, coo.shape)
完整代码:
完整引用:
Traceback (most recent call last):
File "*/src/hypergraph_embedding.py", line 175, in <module>
h.train(dataset)
File "*/src/hypergraph_embedding.py", line 88, in train
epochs=self.options.epochs_to_train, verbose=1)
File "*\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "*\site-packages\keras\engine\training.py", line 1419, in fit_generator
initial_epoch=initial_epoch)
File "*\site-packages\keras\engine\training_generator.py", line 217, in fit_generator
class_weight=class_weight)
File "*\site-packages\keras\engine\training.py", line 1218, in train_on_batch
outputs = self.train_function(ins)
File "*\site-packages\keras\backend\tensorflow_backend.py", line 2917, in __call__
'Feeding from symbolic tensors is not '
ValueError: Feeding from symbolic tensors is not supported with sparse inputs.