map_prensor.md

description: Arbitrary operations from sparse and ragged tensors to a leaf field.

Module: expression_impl.map_prensor

View source on GitHub

Arbitrary operations from sparse and ragged tensors to a leaf field.

There are two public methods of note right now: map_sparse_tensor and map_ragged_tensor.

Assume expr is:

session: {
  event: {
    val_a: 10
    val_b: 1
  }
  event: {
    val_a: 20
    val_b: 2
  }
  event: {
  }
  event: {
    val_a: 40
  }
  event: {
    val_b: 5
  }
}

Either of the following alternatives will add val_a and val_b to create val_sum.

map_sparse_tensor converts val_a and val_b to sparse tensors, and then add them to produce val_sum.

new_root = map_prensor.map_sparse_tensor(
    expr,
    path.Path(["event"]),
    [path.Path(["val_a"]), path.Path(["val_b"])],
    lambda x,y: x + y,
    False,
    tf.int32,
    "val_sum")

map_ragged_tensor converts val_a and val_b to ragged tensors, and then add them to produce val_sum.

new_root = map_prensor.map_ragged_tensor(
    expr,
    path.Path(["event"]),
    [path.Path(["val_a"]), path.Path(["val_b"])],
    lambda x,y: x + y,
    False,
    tf.int32,
    "val_sum")

The result of either is:

session: {
  event: {
    val_a: 10
    val_b: 1
    val_sum: 11
  }
  event: {
    val_a: 20
    val_b: 2
    val_sum: 22
  }
  event: {
  }
  event: {
    val_a: 40
    val_sum: 40
  }
  event: {
    val_b: 5
    val_sum: 5
  }
}

Functions

map_ragged_tensor(...): Map a ragged tensor.

map_sparse_tensor(...): Maps a sparse tensor.