(axis=-1, keepdims=False)
return Fn('Min', lambda x: jnp.min(x, axis, keepdims=keepdims))
Returns a layer that applies min along one tensor axis.

  Args:
    axis: Axis along which values are grouped for computing minimum.
    keepdims: If `True`, keep the resulting size 1 axis as a separate tensor
        axis; else, remove that axis.
Returns a layer that applies min along one tensor axis.
Returns a layer that applies min along one tensor axis .
def Min(axis=-1, keepdims=False):
  """Returns a layer that applies min along one tensor axis.

  Args:
    axis: Axis along which values are grouped for computing minimum.
    keepdims: If `True`, keep the resulting size 1 axis as a separate tensor
        axis; else, remove that axis.
  """
  return Fn('Min', lambda x: jnp.min(x, axis, keepdims=keepdims))
def Min ( axis = - 1 , keepdims = False ) : return Fn ( 'Min' , lambda x : jnp . min ( x , axis , keepdims = keepdims ) )