TensorFlow 1 version
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View source on GitHub
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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
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). |
Returns | |
|---|---|
| The reduced tensor. |
For example:
a = tf.constant([[1, 2], [3, 4]]) tf.reduce_min(a)
Numpy Compatibility
Equivalent to np.min