tf.compat.v1.reduce_min
Computes the 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
)
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). |
reduction_indices | The old (deprecated) name for axis. |
keep_dims | Deprecated alias for keepdims. |
| Returns | |
|---|---|
| The reduced tensor. |
Numpy Compatibility
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/versions/r2.3/api_docs/python/tf/compat/v1/reduce_min