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 __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from sys import stdout
  from os import listdir
  from six import string_types
  from .optimization_utils import _optimize_nn
  from coremltools.models import _SUPPORTED_QUANTIZATION_MODES, _QUANTIZATION_MODE_DEQUANTIZE, _QUANTIZATION_MODE_LOOKUP_TABLE_LINEAR, _QUANTIZATION_MODE_LOOKUP_TABLE_KMEANS, _QUANTIZATION_MODE_CUSTOM_LOOKUP_TABLE, _QUANTIZATION_MODE_LINEAR_QUANTIZATION, _QUANTIZATION_MODE_LINEAR_SYMMETRIC, _LUT_BASED_QUANTIZATION
  from ..utils import _get_nn_layers, _wp_to_fp16wp, _get_model, _macos_version
  from ..._deps import _HAS_SKLEARN
  from ...None import _MINIMUM_QUANTIZED_MODEL_SPEC_VERSION, _MINIMUM_FP16_SPEC_VERSION, _SPECIFICATION_VERSION_IOS_14
label_desc: Use image node_id 1 to create a new ModelMetrics object  with example: obj = ModelMetrics(spec)