code: def jax_funcify_ScalarOp(op, node, **kwargs):
      """Return JAX function that implements the same computation as the Scalar Op.
  
      This dispatch is expected to return a JAX function that works on Array inputs as Elemwise does,
      even though it's dispatched on the Scalar Op.
      """
  
      # We dispatch some PyTensor operators to Python operators
      # whenever the inputs are all scalars.
      if all_inputs_are_scalar(node):
          jax_func = jax_funcify_scalar_op_via_py_operators(op)
          if jax_func is not None:
              return jax_func
  
      nfunc_spec = getattr(op, "nfunc_spec", None)
      if nfunc_spec is None:
          raise NotImplementedError(
              f"Dispatch not implemented for Scalar Op {op}"
          )
  
      func_name = nfunc_spec[0]
      if "." in func_name:
          jax_func = functools.reduce(
              getattr, [jax] + func_name.split(".")
          )
      else:
          jax_func = getattr(jnp, func_name)
  
      if len(node.inputs) > op.nfunc_spec[1]:
          # Some Scalar Ops accept multiple number of inputs, behaving as a variadic function,
          # even though the base Op from `func_name` is specified as a binary Op.
          # This happens with `Add`, which can work as a `Sum` for multiple scalars.
          jax_variadic_func = getattr(jnp, op.nfunc_variadic, None)
          if not jax_variadic_func:
              raise NotImplementedError(
                  f"Dispatch not implemented for Scalar Op {op} with {len(node.inputs)} inputs"
              )
  
          def jax_func(*args):
              return jax_variadic_func(
                  jnp.stack(jnp.broadcast_arrays(*args), axis=0), axis=0
              )
  
      return jax_func
  
imports: import functools
  import typing
  from typing import Callable, Optional
  import jax
  import jax.numpy
  from pytensor.link.jax.dispatch.basic import jax_funcify
  from pytensor.scalar import Softplus
  from pytensor.scalar.basic import Add, Cast, Clip, Composite, Identity, IntDiv, Mod, Mul, ScalarOp, Second, Sub
  from pytensor.scalar.math import BetaIncInv, Erf, Erfc, Erfcinv, Erfcx, Erfinv, GammaIncCInv, GammaIncInv, Iv, Ive, Log1mexp, Psi, TriGamma
label_desc: Use image node_id 3 for calling a global function with example usage: jax_funcify_ScalarOp(op, node) and returns: jax_func, jax_func, jax_variadic_func