|  TensorFlow 2 version |  View source on GitHub | 
Computes the minimum of elements across dimensions of a tensor. (deprecated arguments)
tf.math.reduce_min(
    input_tensor, axis=None, keepdims=None, name=None, reduction_indices=None,
    keep_dims=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
entry in axis. 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). | 
| reduction_indices | The old (deprecated) name for axis. | 
| keep_dims | Deprecated alias for keepdims. | 
| Returns | |
|---|---|
| The reduced tensor. | 
Numpy Compatibility
Equivalent to np.min