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Computes the minimum of elements across dimensions of a tensor.

tf.math.reduce_min( input_tensor, axis=None, keepdims=False, name=None )

Reduces `input_tensor`

along the dimensions given in `axis`

. Unless `keepdims`

is true, the rank of the tensor is reduced by 1 for each of the entries in `axis`

, which must be unique. If `keepdims`

is true, the reduced dimensions are retained with length 1.

If `axis`

is None, all dimensions are reduced, and a tensor with a single element is returned.

Args | |
---|---|

`input_tensor` | The tensor to reduce. Should have real numeric type. |

`axis` | The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(input_tensor), rank(input_tensor))` . |

`keepdims` | If true, retains reduced dimensions with length 1. |

`name` | A name for the operation (optional). |

Returns | |
---|---|

The reduced tensor. |

a = tf.constant([[1, 2], [3, 4]]) tf.reduce_min(a) <tf.Tensor: shape=(), dtype=int32, numpy=1>

Equivalent to np.min

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/math/reduce_min