code: def verify_mixed_precision_output_close(
      mod: tvm.runtime.Module,
      mod_params: Dict[str, Any],
      mixed_precision_dtype="float16",
      rtol: float = 1e-3,
      atol: float = 0,
      keep_orig_output_dtype=False,
  ) -> tvm.runtime.Module:
      mod = InferType()(mod)
      result_fp32 = run_module(mod, mod_params)
  
      if not keep_orig_output_dtype:
          amp_mod = ToMixedPrecision(mixed_precision_dtype)(mod)
          result_amp = run_module(amp_mod, mod_params)
      else:
          with tvm.transform.PassContext(
              config={
                  "relay.ToMixedPrecision.keep_orig_output_dtype": True
              }
          ):
              amp_mod = ToMixedPrecision(mixed_precision_dtype)(mod)
              result_amp = run_module(amp_mod, mod_params)
  
      # Ensure the results are close
      if mixed_precision_dtype != "bfloat16":
          for fp32, amp in zip(result_fp32, result_amp):
              np.testing.assert_allclose(
                  fp32, amp, rtol=rtol, atol=atol
              )
  
      if keep_orig_output_dtype:
          assert (
              np.array(result_amp).dtype == np.array(result_fp32).dtype
          ), "output type and original type mismatch"
  
      return amp_mod
  
imports: from typing import Any, Dict, List
  import numpy
  import pytest
  import tvm
  from tvm import relay
  from tvm.relay.testing import lstm
  from tvm.relay.transform import InferType, ToMixedPrecision, mixed_precision
label_desc: Use image node_id 2 for calling a global function with example usage: verify_mixed_precision_output_close(mod, mod_params, mixed_precision_dtype, rtol, atol, keep_orig_output_dtype) and returns: amp_mod