# SegmentMin

public final class SegmentMin

Computes the minimum along segments of a tensor.

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 = \min_j(data_j)\$$ where min is over j such that segment_ids[j] == i.

If the min is empty for a given segment ID i, output[i] = 0.

For example:

c = tf.constant([[1,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.segment_min(c, tf.constant([0, 0, 1]))
# ==> [[1, 2, 2, 1],
#      [5, 6, 7, 8]]


### Constants

 String OP_NAME The name of this op, as known by TensorFlow core engine

### Public Methods

 Output () Returns the symbolic handle of the tensor. static SegmentMin ( Scope scope, Operand data, Operand segmentIds) Factory method to create a class wrapping a new SegmentMin operation. Output () Has same shape as data, except for dimension 0 which has size k, the number of segments.

## Constants

#### public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "SegmentMin"

## Public Methods

#### public Output <T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

#### public static SegmentMin <T> create ( Scope scope, Operand <T> data, Operand <? extends TNumber > segmentIds)

Factory method to create a class wrapping a new SegmentMin operation.

##### Parameters
 scope current scope A 1-D tensor whose size is equal to the size of data's first dimension. Values should be sorted and can be repeated.
##### Returns
• a new instance of SegmentMin

#### public Output <T> output ()

Has same shape as data, except for dimension 0 which has size k, the number of segments.

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