AnandInguva commented on code in PR #22088: URL: https://github.com/apache/beam/pull/22088#discussion_r919664232
########## sdks/python/apache_beam/examples/inference/sklearn_japanese_housing_regression.py: ########## @@ -0,0 +1,164 @@ +# +# 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 on a regression about housing prices. + +This example uses the japanese housing data from kaggle. +https://www.kaggle.com/datasets/nishiodens/japan-real-estate-transaction-prices + +Since the data has missing fields, this example illustrates how to split +data and assign it to the models that are trained on different subsets of +features. The predictions are then recombined. + +In order to set this example up, you will need two things. +1. Build models (or use ours) and reference those via the model directory. Review Comment: We need to have a regression test for every example to catch any early bugs/regressions in the transform. Can you create one regression test with a smaller data and add that one to this [class](https://github.com/apache/beam/blob/2c8e7eb7a39cbe3a1678a5c6b8b3f8700d4d8706/sdks/python/apache_beam/ml/inference/sklearn_inference_it_test.py#L41]) ########## sdks/python/apache_beam/examples/inference/sklearn_japanese_housing_regression.py: ########## @@ -0,0 +1,164 @@ +# +# 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 on a regression about housing prices. + +This example uses the japanese housing data from kaggle. +https://www.kaggle.com/datasets/nishiodens/japan-real-estate-transaction-prices + +Since the data has missing fields, this example illustrates how to split +data and assign it to the models that are trained on different subsets of +features. The predictions are then recombined. + +In order to set this example up, you will need two things. +1. Build models (or use ours) and reference those via the model directory. Review Comment: We need to have a regression test for every example to catch any early bugs/regressions in the transform. Can you create one regression test with a smaller data and add that one to this [class](https://github.com/apache/beam/blob/2c8e7eb7a39cbe3a1678a5c6b8b3f8700d4d8706/sdks/python/apache_beam/ml/inference/sklearn_inference_it_test.py#L41])? -- 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
