class_docstr: A utility class to hold evaluation metrics
class_docstr_tok: ["A","utility","class","to","hold","evaluation","metrics"]
code: def __init__(self, spec):
      self.model_metrics = {}
      for output in spec.description.output:
          output_type = output.type.WhichOneof("Type")
          self.model_metrics[output.name] = OutputMetric(
              output.name, output_type
          )
  
imports: from os import listdir
  from sys import stdout
  import numpy
  from coremltools import ComputeUnit, _logger
  from coremltools._deps import _HAS_KMEANS1D, _kmeans1d
  from coremltools.models import _QUANTIZATION_MODE_CUSTOM_LOOKUP_TABLE, _QUANTIZATION_MODE_DEQUANTIZE, _QUANTIZATION_MODE_LINEAR_QUANTIZATION, _QUANTIZATION_MODE_LINEAR_SYMMETRIC, _QUANTIZATION_MODE_LOOKUP_TABLE_KMEANS, _QUANTIZATION_MODE_LOOKUP_TABLE_LINEAR, _SUPPORTED_QUANTIZATION_MODES, MLModel
  from ...None import _MINIMUM_FP16_SPEC_VERSION, _MINIMUM_QUANTIZED_MODEL_SPEC_VERSION, _SPECIFICATION_VERSION_IOS_14
  from ..utils import _get_model, _macos_version, _wp_to_fp16wp
  from .optimization_utils import _optimize_nn
label_desc: Use image node_id 1 to create a new ModelMetrics object  with example: obj = ModelMetrics(spec)