tf.compat.v1.scatter

Serialize N-minibatch SparseTensor into an [N, 3] Tensor.

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Compat aliases for migration

tf.compat.v1.io.serialize_many_sparse

tf.compat.v1.serialize_many_sparse(
    sp_input, name=None, out_type=tf.dtypes.string
)

The SparseTensor must have rank R greater than 1, and the first dimension is treated as the minibatch dimension. Elements of the SparseTensor must be sorted in increasing order of this first dimension. The serialized SparseTensor objects going into each row of the output Tensor will have rank R-1.

The minibatch size N is extracted from sparse_shape[0].

Args
`sp_input`	The input rank `R` `SparseTensor`.
`name`	A name prefix for the returned tensors (optional).
`out_type`	The `dtype` to use for serialization.

Returns
A matrix (2-D `Tensor`) with `N` rows and `3` columns. Each column represents serialized `SparseTensor`'s indices, values, and shape (respectively).

Raises
`TypeError`	If `sp_input` is not a `SparseTensor`.

TensorFlow

tf.compat / v1 / v1.scatter_update

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TensorFlow

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tf.compat / v1 / v1.scatter_update

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