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tf.compat.v1.reduce_min

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Computes the minimum of elements across dimensions of a tensor. (deprecated arguments)

Aliases:

  • tf.compat.v1.math.reduce_min
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