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
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. |
For example:
a = tf.constant([[1, 2], [3, 4]])tf.reduce_min(a)<tf.Tensor: shape=(), dtype=int32, numpy=1>
Numpy Compatibility
Equivalent to np.min