x=tf.compat.v1.sparse.placeholder(tf.float32)y=tf.sparse.reduce_sum(x)withtf.compat.v1.Session()assess:print(sess.run(y))# ERROR: will fail because x was not fed.indices=np.array([[3,2,0],[4,5,1]],dtype=np.int64)values=np.array([1.0,2.0],dtype=np.float32)shape=np.array([7,9,2],dtype=np.int64)print(sess.run(y,feed_dict={x:tf.compat.v1.SparseTensorValue(indices,values,shape)}))# Willsucceed.print(sess.run(y,feed_dict={x:(indices,values,shape)}))# Will succeed.sp=tf.sparse.SparseTensor(indices=indices,values=values,dense_shape=shape)sp_value=sp.eval(session=sess)print(sess.run(y,feed_dict={x:sp_value}))# Will succeed.
@compatibility{eager} Placeholders are not compatible with eager execution.
Args
dtype
The type of values elements in the tensor to be fed.
shape
The shape of the tensor to be fed (optional). If the shape is not
specified, you can feed a sparse tensor of any shape.
name
A name for prefixing the operations (optional).
Returns
A SparseTensor that may be used as a handle for feeding a value, but not
evaluated directly.