Change the e2e tests to use out-of-graph metrics other than in-graph …

…ones due to TF2.2 will stop exposing in-graph metrics APIs. PiperOrigin-RevId: 312108536
m2kar · May 18, 2020 · 4518409 · 4518409
1 parent 62ba786
commit 4518409
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Showing 2 changed files with 20 additions and 20 deletions.
diff --git a/tfx/examples/chicago_taxi_pipeline/taxi_pipeline_native_keras.py b/tfx/examples/chicago_taxi_pipeline/taxi_pipeline_native_keras.py
@@ -122,16 +122,16 @@ def _create_pipeline(pipeline_name: Text, pipeline_root: Text, data_root: Text,
       model_specs=[tfma.ModelSpec(label_key='tips')],
       slicing_specs=[tfma.SlicingSpec()],
       metrics_specs=[
-          tfma.MetricsSpec(
-              thresholds={
-                  'binary_accuracy':
-                      tfma.config.MetricThreshold(
-                          value_threshold=tfma.GenericValueThreshold(
-                              lower_bound={'value': 0.6}),
-                          change_threshold=tfma.GenericChangeThreshold(
-                              direction=tfma.MetricDirection.HIGHER_IS_BETTER,
-                              absolute={'value': -1e-10}))
-              })
+          tfma.MetricsSpec(metrics=[
+              tfma.MetricConfig(
+                  class_name='BinaryAccuracy',
+                  threshold=tfma.MetricThreshold(
+                      value_threshold=tfma.GenericValueThreshold(
+                          lower_bound={'value': 0.6}),
+                      change_threshold=tfma.GenericChangeThreshold(
+                          direction=tfma.MetricDirection.HIGHER_IS_BETTER,
+                          absolute={'value': -1e-10})))
+          ])
       ])
   evaluator = Evaluator(
       examples=example_gen.outputs['examples'],

diff --git a/tfx/examples/iris/iris_pipeline_native_keras.py b/tfx/examples/iris/iris_pipeline_native_keras.py
@@ -120,16 +120,16 @@ def _create_pipeline(pipeline_name: Text, pipeline_root: Text, data_root: Text,
       model_specs=[tfma.ModelSpec(label_key='variety')],
       slicing_specs=[tfma.SlicingSpec()],
       metrics_specs=[
-          tfma.MetricsSpec(
-              thresholds={
-                  'sparse_categorical_accuracy':
-                      tfma.config.MetricThreshold(
-                          value_threshold=tfma.GenericValueThreshold(
-                              lower_bound={'value': 0.6}),
-                          change_threshold=tfma.GenericChangeThreshold(
-                              direction=tfma.MetricDirection.HIGHER_IS_BETTER,
-                              absolute={'value': -1e-10}))
-              })
+          tfma.MetricsSpec(metrics=[
+              tfma.MetricConfig(
+                  class_name='SparseCategoricalAccuracy',
+                  threshold=tfma.MetricThreshold(
+                      value_threshold=tfma.GenericValueThreshold(
+                          lower_bound={'value': 0.6}),
+                      change_threshold=tfma.GenericChangeThreshold(
+                          direction=tfma.MetricDirection.HIGHER_IS_BETTER,
+                          absolute={'value': -1e-10})))
+          ])
       ])
   evaluator = Evaluator(
       examples=example_gen.outputs['examples'],