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.
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
.The reduced tensor.
Equivalent to np.min
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/reduce_min