{ }
View source on GitHub |
Computes the tf.math.minimum
of elements across dimensions of a tensor. (deprecated arguments)
tf.compat.v1.reduce_min(
input_tensor,
axis=None,
keepdims=None,
name=None,
reduction_indices=None,
keep_dims=None
)
Used in the notebooks
Used in the tutorials |
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This is the reduction operation for the elementwise tf.math.minimum
op.
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.
Usage example | |
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|
See the numpy docs for np.amin
and np.nanmin
behavior.
Returns | |
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The reduced tensor. |