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tf.ragged.map_flat_values

TensorFlow 2.0 version View source on GitHub

Applies op to the values of one or more RaggedTensors.

Aliases:

  • tf.compat.v1.ragged.map_flat_values
  • tf.compat.v2.ragged.map_flat_values
tf.ragged.map_flat_values(
    op,
    *args,
    **kwargs
)

Replaces any RaggedTensor in args or kwargs with its flat_values tensor, and then calls op. Returns a RaggedTensor that is constructed from the input RaggedTensors' nested_row_splits and the value returned by the op.

If the input arguments contain multiple RaggedTensors, then they must have identical nested_row_splits.

Examples:

>>> rt = ragged.constant([[1, 2, 3], [], [4, 5], [6]])
>>> ragged.map_flat_values(tf.ones_like, rt).eval().tolist()
[[1, 1, 1], [], [1, 1], [1]]
>>> ragged.map_flat_values(tf.multiply, rt, rt).eval().tolist()
[[1, 4, 9], [], [16, 25], [36]]
>>> ragged.map_flat_values(tf.add, rt, 5).eval().tolist()
[[6, 7, 8], [], [9, 10], [11]]

Args:

  • op: The operation that should be applied to the RaggedTensor flat_values. op is typically an element-wise operation (such as math_ops.add), but any operation that preserves the size of the outermost dimension can be used. I.e., shape[0] of the value returned by op must match shape[0] of the RaggedTensors' flat_values tensors.
  • *args: Arguments for op.
  • **kwargs: Keyword arguments for op.

Returns:

A RaggedTensor whose ragged_rank matches the ragged_rank of all input RaggedTensors.

Raises:

  • ValueError: If args contains no RaggedTensors, or if the nested_splits of the input RaggedTensors are not identical.