def _makeEvalResults(self):
result_a = model_eval_lib.EvalResult(
slicing_metrics=self._makeTestData(),
plots=None,
config=config.EvalConfig(),
data_location=self.data_location_1,
file_format='tfrecords',
model_location=self.model_location_1)
result_b = model_eval_lib.EvalResult(
slicing_metrics=[self.result_c2],
plots=None,
config=config.EvalConfig(),
data_location=self.full_data_location_2,
file_format='tfrecords',
model_location=self.full_model_location_2)
return model_eval_lib.EvalResults([result_a, result_b],
constants.MODEL_CENTRIC_MODE)
def _makeEvalResults(self):
result_a = model_eval_lib.EvalResult(
slicing_metrics=self._makeTestData(),
plots=None,
config=model_eval_lib.EvalConfig(
example_weight_metric_key=None,
slice_spec=None,
data_location=self.data_location_1,
model_location=self.model_location_1))
result_b = model_eval_lib.EvalResult(
slicing_metrics=[self.result_c2],
plots=None,
config=model_eval_lib.EvalConfig(
example_weight_metric_key=None,
slice_spec=None,
data_location=self.full_data_location_2,
model_location=self.full_model_location_2))
return model_eval_lib.EvalResults([result_a, result_b],
constants.MODEL_CENTRIC_MODE)
def _makeEvalResult(self,
slices=((), (('slice', '1'), )),
metrics_names=('metrics1', 'metrics2')):
metrics = {'': {'': {}}}
for metrics_name in metrics_names:
metrics[''][''][metrics_name] = {'double_value': {'value': 0.5}}
slicing_metrics = [(s, metrics) for s in slices]
return model_eval_lib.EvalResult(slicing_metrics=slicing_metrics,
plots=None,
config=None)
def _makeEvalResults(self):
result_a = model_eval_lib.EvalResult(
slicing_metrics=self._makeTestData(),
plots=None,
config=config.EvalConfig(
input_data_specs=[
config.InputDataSpec(location=self.data_location_1)
],
model_specs=[config.ModelSpec(location=self.model_location_1)
]))
result_b = model_eval_lib.EvalResult(
slicing_metrics=[self.result_c2],
plots=None,
config=config.EvalConfig(
input_data_specs=[
config.InputDataSpec(location=self.full_data_location_2)
],
model_specs=[
config.ModelSpec(location=self.full_model_location_2)
]))
return model_eval_lib.EvalResults([result_a, result_b],
constants.MODEL_CENTRIC_MODE)
