tf.ragged.range | TensorFlow v2.16.1 (original) (raw)
tf.ragged.range
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Returns a RaggedTensor
containing the specified sequences of numbers.
View aliases
Compat aliases for migration
SeeMigration guide for more details.
tf.ragged.range(
starts,
limits=None,
deltas=1,
dtype=None,
name=None,
row_splits_dtype=tf.dtypes.int64
)
Used in the notebooks
Used in the guide |
---|
Ragged tensors |
Each row of the returned RaggedTensor
contains a single sequence:
ragged.range(starts, limits, deltas)[i] ==
tf.range(starts[i], limits[i], deltas[i])
If start[i] < limits[i] and deltas[i] > 0
, then output[i]
will be an empty list. Similarly, if start[i] > limits[i] and deltas[i] < 0
, thenoutput[i]
will be an empty list. This behavior is consistent with the Python range
function, but differs from the tf.range op, which returns an error for these cases.
Examples:
tf.ragged.range([3, 5, 2]).to_list()
[[0, 1, 2], [0, 1, 2, 3, 4], [0, 1]]
tf.ragged.range([0, 5, 8], [3, 3, 12]).to_list()
[[0, 1, 2], [], [8, 9, 10, 11]]
tf.ragged.range([0, 5, 8], [3, 3, 12], 2).to_list()
[[0, 2], [], [8, 10]]
The input tensors starts
, limits
, and deltas
may be scalars or vectors. The vector inputs must all have the same size. Scalar inputs are broadcast to match the size of the vector inputs.
Args | |
---|---|
starts | Vector or scalar Tensor. Specifies the first entry for each range if limits is not None; otherwise, specifies the range limits, and the first entries default to 0. |
limits | Vector or scalar Tensor. Specifies the exclusive upper limits for each range. |
deltas | Vector or scalar Tensor. Specifies the increment for each range. Defaults to 1. |
dtype | The type of the elements of the resulting tensor. If not specified, then a value is chosen based on the other args. |
name | A name for the operation. |
row_splits_dtype | dtype for the returned RaggedTensor's row_splitstensor. One of tf.int32 or tf.int64. |
Returns |
---|
A RaggedTensor of type dtype with ragged_rank=1. |