tf.compat.v2.reduce_min

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Computes the minimum of elements across dimensions of a tensor.

Aliases:

tf.compat.v2.reduce_min(
    input_tensor,
    axis=None,
    keepdims=False,
    name=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).

Returns:

The reduced tensor.

Numpy Compatibility

Equivalent to np.min