[GitHub] [beam] yeandy commented on a diff in pull request #21781: Sklearn Mnist example and IT test

[GitBox <gi...@apache.org>]

yeandy commented on code in PR #21781:
URL: https://github.com/apache/beam/pull/21781#discussion_r897973071


##########
sdks/python/apache_beam/ml/inference/sklearn_inference_it_test.py:
##########
@@ -0,0 +1,51 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""End-to-End test for Sklearn Inference"""
+
+import logging
+import pytest
+import unittest
+import uuid
+
+from apache_beam.io.filesystems import FileSystems
+from apache_beam.examples.inference import sklearn_mnist_classification
+from apache_beam.testing.test_pipeline import TestPipeline
+
+
+class SklearnInference(unittest.TestCase):
+  @pytest.mark.it_postcommit
+  def test_predictions_output_file(self):
+    test_pipeline = TestPipeline(is_integration_test=True)
+    input_file = 'gs://apache-beam-ml/testing/inputs/it_mnist_data.csv'

Review Comment:
   Shouldn't this go under `apache-beam-ml/datasets/`?



##########
sdks/python/apache_beam/examples/inference/sklearn_mnist_classification.py:
##########
@@ -0,0 +1,95 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""A pipeline that uses RunInference API to perform image classification."""
+
+import argparse
+from typing import Dict
+from typing import Iterable
+from typing import List
+from typing import Tuple
+
+import apache_beam as beam
+from apache_beam.ml.inference.api import PredictionResult
+from apache_beam.ml.inference.api import RunInference
+from apache_beam.ml.inference.sklearn_inference import ModelFileType
+from apache_beam.ml.inference.sklearn_inference import SklearnModelLoader
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import SetupOptions
+
+
+def process_input(row: str) -> Tuple[int, List[int]]:
+  data = row.split(',')
+  label, pixels = int(data[0]), data[1:]
+  pixels = [int(pixel) for pixel in pixels]
+  return label, pixels
+
+
+class PostProcessor(beam.DoFn):
+  def process(self, element: Tuple[int, PredictionResult]) -> Iterable[Dict]:
+    label, prediction_result = element
+    prediction = prediction_result.inference
+    yield {label: prediction}
+
+
+def parse_known_args(argv):
+  """Parses args for the workflow."""
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--input_file',
+      dest='input',
+      help='CSV file with row containing label and pixel values.')
+  parser.add_argument(
+      '--output', dest='output', help='Path to save output predictions.')
+  parser.add_argument(
+      '--model_path',
+      dest='model_path',
+      help='Path to load the Sklearn model for Inference.')
+  return parser.parse_known_args(argv)
+
+
+def run(argv=None, save_main_session=True):
+  """Entry point. Defines and runs the pipeline."""
+  known_args, pipeline_args = parse_known_args(argv)
+  pipeline_options = PipelineOptions(pipeline_args)
+  pipeline_options.view_as(SetupOptions).save_main_session = save_main_session
+
+  model_loader = SklearnModelLoader(
+      model_file_type=ModelFileType.PICKLE, model_uri=known_args.model_path)
+
+  with beam.Pipeline(options=pipeline_options) as p:
+    label_pixel_tuple = (
+        p
+        | "ReadFromInput" >> beam.io.ReadFromText(
+            known_args.input, skip_header_lines=1)
+        | "Process inputs" >> beam.Map(process_input))
+
+    predictions = (
+        label_pixel_tuple
+        | "RunInference" >> RunInference(model_loader).with_output_types(
+            Tuple[int, PredictionResult])
+        | "PostProcessor" >> beam.ParDo(PostProcessor()))
+
+    if known_args.output:

Review Comment:
   Make output required. Remove if statement.



##########
sdks/python/apache_beam/examples/inference/sklearn_mnist_classification.py:
##########
@@ -0,0 +1,95 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""A pipeline that uses RunInference API to perform image classification."""
+
+import argparse
+from typing import Dict
+from typing import Iterable
+from typing import List
+from typing import Tuple
+
+import apache_beam as beam
+from apache_beam.ml.inference.api import PredictionResult
+from apache_beam.ml.inference.api import RunInference
+from apache_beam.ml.inference.sklearn_inference import ModelFileType
+from apache_beam.ml.inference.sklearn_inference import SklearnModelLoader
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import SetupOptions
+
+
+def process_input(row: str) -> Tuple[int, List[int]]:
+  data = row.split(',')
+  label, pixels = int(data[0]), data[1:]
+  pixels = [int(pixel) for pixel in pixels]
+  return label, pixels
+
+
+class PostProcessor(beam.DoFn):
+  def process(self, element: Tuple[int, PredictionResult]) -> Iterable[Dict]:
+    label, prediction_result = element
+    prediction = prediction_result.inference
+    yield {label: prediction}
+
+
+def parse_known_args(argv):
+  """Parses args for the workflow."""
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--input_file',
+      dest='input',
+      help='CSV file with row containing label and pixel values.')
+  parser.add_argument(
+      '--output', dest='output', help='Path to save output predictions.')

Review Comment:
   Add `required=True`



##########
sdks/python/apache_beam/examples/inference/sklearn_mnist_classification.py:
##########
@@ -0,0 +1,95 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""A pipeline that uses RunInference API to perform image classification."""
+
+import argparse
+from typing import Dict
+from typing import Iterable
+from typing import List
+from typing import Tuple
+
+import apache_beam as beam
+from apache_beam.ml.inference.api import PredictionResult
+from apache_beam.ml.inference.api import RunInference
+from apache_beam.ml.inference.sklearn_inference import ModelFileType
+from apache_beam.ml.inference.sklearn_inference import SklearnModelLoader
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import SetupOptions
+
+
+def process_input(row: str) -> Tuple[int, List[int]]:
+  data = row.split(',')
+  label, pixels = int(data[0]), data[1:]
+  pixels = [int(pixel) for pixel in pixels]
+  return label, pixels
+
+
+class PostProcessor(beam.DoFn):
+  def process(self, element: Tuple[int, PredictionResult]) -> Iterable[Dict]:
+    label, prediction_result = element
+    prediction = prediction_result.inference
+    yield {label: prediction}
+
+
+def parse_known_args(argv):
+  """Parses args for the workflow."""
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--input_file',
+      dest='input',

Review Comment:
   Add `required=True`



##########
sdks/python/apache_beam/examples/inference/sklearn_mnist_classification.py:
##########
@@ -0,0 +1,95 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""A pipeline that uses RunInference API to perform image classification."""
+
+import argparse
+from typing import Dict
+from typing import Iterable
+from typing import List
+from typing import Tuple
+
+import apache_beam as beam
+from apache_beam.ml.inference.api import PredictionResult
+from apache_beam.ml.inference.api import RunInference
+from apache_beam.ml.inference.sklearn_inference import ModelFileType
+from apache_beam.ml.inference.sklearn_inference import SklearnModelLoader
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import SetupOptions
+
+
+def process_input(row: str) -> Tuple[int, List[int]]:
+  data = row.split(',')
+  label, pixels = int(data[0]), data[1:]
+  pixels = [int(pixel) for pixel in pixels]
+  return label, pixels
+
+
+class PostProcessor(beam.DoFn):
+  def process(self, element: Tuple[int, PredictionResult]) -> Iterable[Dict]:
+    label, prediction_result = element
+    prediction = prediction_result.inference
+    yield {label: prediction}
+
+
+def parse_known_args(argv):
+  """Parses args for the workflow."""
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--input_file',
+      dest='input',
+      help='CSV file with row containing label and pixel values.')
+  parser.add_argument(
+      '--output', dest='output', help='Path to save output predictions.')
+  parser.add_argument(
+      '--model_path',
+      dest='model_path',

Review Comment:
   Add `required=True`



-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: github-unsubscribe@beam.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org