# tf.compat.v1.reduce_min

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.14.0/tensorflow/python/ops/math_ops.py#L2992-L3053) |

Computes the [`tf.math.minimum`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/math/minimum) of elements across dimensions of a tensor. (deprecated arguments)

#### View aliases


**Compat aliases for migration**

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

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

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    tf.compat.v1.reduce_min(
        input_tensor,
        axis=None,
        keepdims=None,
        name=None,
        reduction_indices=None,
        keep_dims=None
    )

> [!WARNING]
> **Deprecated:** SOME ARGUMENTS ARE DEPRECATED: `(keep_dims)`. They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead

This is the reduction operation for the elementwise [`tf.math.minimum`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/math/minimum) op.

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.

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| ## Usage example ||
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| <br /> >>> x = tf.constant([5, 1, 2, 4]) >>> tf.reduce_min(x) <tf.Tensor: shape=(), dtype=int32, numpy=1> >>> x = tf.constant([-5, -1, -2, -4]) >>> tf.reduce_min(x) <tf.Tensor: shape=(), dtype=int32, numpy=-5> >>> x = tf.constant([4, float('nan')]) >>> tf.reduce_min(x) <tf.Tensor: shape=(), dtype=float32, numpy=nan> >>> x = tf.constant([float('nan'), float('nan')]) >>> tf.reduce_min(x) <tf.Tensor: shape=(), dtype=float32, numpy=nan> >>> x = tf.constant([float('-inf'), float('inf')]) >>> tf.reduce_min(x) <tf.Tensor: shape=(), dtype=float32, numpy=-inf> <br /> ||

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See the numpy docs for `np.amin` and `np.nanmin` behavior.

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| ## Args ||
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| `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). |
| `reduction_indices` | The old (deprecated) name for axis. |
| `keep_dims` | Deprecated alias for `keepdims`. |

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| ## Returns ||
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| The reduced tensor. ||

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