tf.math.reduce

Computes the minimum of elements across dimensions of a tensor.

View aliases

Main aliases

tf.reduce_min

tf.math.reduce_min(
    input_tensor, axis=None, keepdims=False, name=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Ragged tensors	Integrated gradients Intro to Autoencoders

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

TensorFlow

tf.math / reduce_max

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Used in the notebooks

Args

Returns

For example:

Numpy Compatibility

TensorFlow

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tf.math / reduce_max

View aliases

Used in the notebooks

Args

Returns

For example:

Numpy Compatibility