# tf.raw_ops.SegmentProdV2

Computes the product along segments of a tensor.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.SegmentProdV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SegmentProdV2)

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    tf.raw_ops.SegmentProdV2(
        data, segment_ids, num_segments, name=None
    )

Read
[the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation)
for an explanation of segments.

Computes a tensor such that
\\(output_i = \\prod_j data_j\\) where the product is over `j` such
that `segment_ids[j] == i`.

If the product is empty for a given segment ID `i`, `output[i] = 1`.

> [!NOTE]
> **Note:** That this op is currently only supported with jit_compile=True.

The only difference with SegmentProd is the additional input `num_segments`.
This helps in evaluating the output shape in compile time.
`num_segments` should be consistent with segment_ids.
e.g. Max(segment_ids) - 1 should be equal to `num_segments` for a 1-d segment_ids
With inconsistent num_segments, the op still runs. only difference is,
the output takes the size of num_segments irrespective of size of segment_ids and data.
for num_segments less than expected output size, the last elements are ignored
for num_segments more than the expected output size, last elements are assigned 1.

#### For example:

    @tf.function(jit_compile=True)
    def test(c):
      return tf.raw_ops.SegmentProdV2(data=c, segment_ids=tf.constant([0, 0, 1]), num_segments=2)
    c = tf.constant([[1,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
    test(c).numpy()
    array([[4, 6, 6, 4],
           [5, 6, 7, 8]], dtype=int32)

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| ## Args ||
|---|---|
| `data` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `qint16`, `quint16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. |
| `segment_ids` | A `Tensor`. Must be one of the following types: `int32`, `int64`. A 1-D tensor whose size is equal to the size of `data`'s first dimension. Values should be sorted and can be repeated. The values must be less than `num_segments`. <br /> > [!CAUTION] > **Caution:** The values are always validated to be sorted on CPU, never validated on GPU. |
| `num_segments` | A `Tensor`. Must be one of the following types: `int32`, `int64`. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A `Tensor`. Has the same type as `data`. ||

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