riteshghorse commented on code in PR #25368: URL: https://github.com/apache/beam/pull/25368#discussion_r1102038754
########## sdks/python/apache_beam/ml/inference/tensorflow_inference_test.py: ########## @@ -0,0 +1,148 @@ +# +# 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. +# + +# pytype: skip-file + +import unittest + +import numpy +import pytest + +try: + import tensorflow as tf + from apache_beam.ml.inference.sklearn_inference_test import _compare_prediction_result + from apache_beam.ml.inference.base import KeyedModelHandler, PredictionResult + from apache_beam.ml.inference.tensorflow_inference import TFModelHandlerNumpy, TFModelHandlerTensor +except ImportError: + raise unittest.SkipTest('Tensorflow dependencies are not installed') + + +class FakeTFNumpyModel: + def predict(self, input: numpy.ndarray): + return numpy.multiply(input, 10) + + +class FakeTFTensorModel: + def predict(self, input: tf.Tensor, add=False): + if add: + return tf.math.add(tf.math.multiply(input, 10), 10) + return tf.math.multiply(input, 10) + + +def _compare_tensor_prediction_result(x, y): + return tf.math.equal(x.inference, y.inference) + + +class TFRunInferenceTest(unittest.TestCase): + def test_predict_numpy(self): + fake_model = FakeTFNumpyModel() + inference_runner = TFModelHandlerNumpy(model_uri='unused') + batched_examples = [numpy.array([1]), numpy.array([10]), numpy.array([100])] + expected_predictions = [ + PredictionResult(numpy.array([1]), 10), + PredictionResult(numpy.array([10]), 100), + PredictionResult(numpy.array([100]), 1000) + ] + inferences = inference_runner.run_inference(batched_examples, fake_model) + for actual, expected in zip(inferences, expected_predictions): + self.assertTrue(_compare_prediction_result(actual, expected)) + + @pytest.mark.uses_tf Review Comment: Done. -- 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]
