# W3cubDocs

/TensorFlow Python

# tf.reduce_min

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

Defined in `tensorflow/python/ops/math_ops.py`.

See the guide: Math > Reduction

Computes the minimum of elements across dimensions of a tensor. (deprecated arguments)

SOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead

Reduces `input_tensor` along the dimensions given in `axis`. Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each entry in `axis`. If `keepdims` is true, the reduced dimensions are retained with length 1.

If `axis` has no entries, all dimensions are reduced, and a tensor with a single element is returned.

#### Args:

• `input_tensor`: The tensor to reduce. Should have 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`.

#### Returns:

The reduced tensor.

#### Numpy Compatibility

Equivalent to np.min