code: def _determine_source_dialect(model, exact_source):
      source_dialect = None
      if exact_source == "pytorch":
          if _HAS_TORCH_EXPORT_API and isinstance(
              model, ExportedProgram
          ):
              return f"TorchExport::{model.dialect}"
          else:
              return "TorchScript"
  
      return source_dialect
  
imports: import collections
  import gc
  import os
  from typing import List, Optional, Text, Union
  from coremltools import _LOWEST_ALLOWED_SPECIFICATION_VERSION_FOR_MILPROGRAM, _LOWEST_ALLOWED_SPECIFICATION_VERSION_FOR_NEURALNETWORK
  from coremltools import ComputeUnit
  from coremltools import __version__
  from coremltools import _logger
  from coremltools._deps import _HAS_TF_1, _HAS_TF_2, _HAS_TORCH, _HAS_TORCH_EXPORT_API
  from coremltools.converters._profile_utils import _profile
  from coremltools.converters.mil._deployment_compatibility import AvailableTarget, check_deployment_compatibility
  from coremltools.converters.mil.converter import mil_convert
  from coremltools.converters.mil.input_types import ClassifierConfig, EnumeratedShapes, ImageType, InputType, RangeDim, Shape, TensorType
  from coremltools.converters.mil.mil import Program, types
  from coremltools.converters.mil.mil.passes.defs.quantization import ComputePrecision
  from coremltools.converters.mil.mil.passes.defs.quantization import FP16ComputePrecision
  from coremltools.converters.mil.mil.passes.graph_pass import PassOption
  from coremltools.converters.mil.mil.passes.pass_pipeline import PassPipeline
  from coremltools.models import _METADATA_SOURCE, _METADATA_SOURCE_DIALECT, _METADATA_VERSION
  from coremltools.models.utils import _MLPACKAGE_EXTENSION
label_desc: Use image node_id 7 for calling a global function with example usage: _determine_source_dialect(model, exact_source) and returns: source_dialect, str, model, str