AnandInguva commented on code in PR #17462: URL: https://github.com/apache/beam/pull/17462#discussion_r880957064
########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): + image_file_name = os.path.join(path_to_dir, image_file_name) + with FileSystems().open(image_file_name, 'r') as file: + data = Image.open(io.BytesIO(file.read())).convert('RGB') + return image_file_name, data + + +def preprocess_data(data): Review Comment: Done ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): + image_file_name = os.path.join(path_to_dir, image_file_name) + with FileSystems().open(image_file_name, 'r') as file: + data = Image.open(io.BytesIO(file.read())).convert('RGB') + return image_file_name, data + + +def preprocess_data(data): + image_size = (224, 224) + normalize = transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) Review Comment: done ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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 Review Comment: Done. ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): + image_file_name = os.path.join(path_to_dir, image_file_name) + with FileSystems().open(image_file_name, 'r') as file: + data = Image.open(io.BytesIO(file.read())).convert('RGB') + return image_file_name, data + + +def preprocess_data(data): + image_size = (224, 224) + normalize = transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + transform = transforms.Compose([ + transforms.Resize(image_size), + transforms.ToTensor(), + normalize, + ]) + return transform(data) + + +class PostProcessor(beam.DoFn): + """Post process PredictionResult to output filename and + prediction using torch.""" Review Comment: Reworded the docstring ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): + image_file_name = os.path.join(path_to_dir, image_file_name) + with FileSystems().open(image_file_name, 'r') as file: + data = Image.open(io.BytesIO(file.read())).convert('RGB') + return image_file_name, data + + +def preprocess_data(data): + image_size = (224, 224) + normalize = transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + transform = transforms.Compose([ + transforms.Resize(image_size), + transforms.ToTensor(), + normalize, + ]) + return transform(data) + + +class PostProcessor(beam.DoFn): + """Post process PredictionResult to output filename and + prediction using torch.""" + def process(self, element): + filename, prediction_result = element + prediction = torch.argmax(prediction_result.inference, dim=0) + yield filename + ',' + str(int(prediction)) Review Comment: without int, it outputted `tensor(value)`. So to get the value, i converted to int, so when writing to a text file, it will write as <value> instead of <tensor(value)>. But looking more into it, torch has a method called tensor.item() which would provide the value(might be int, float) etc. ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): Review Comment: Done. I added them for most of the methods. ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): + image_file_name = os.path.join(path_to_dir, image_file_name) + with FileSystems().open(image_file_name, 'r') as file: + data = Image.open(io.BytesIO(file.read())).convert('RGB') + return image_file_name, data + + +def preprocess_data(data): + image_size = (224, 224) + normalize = transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + transform = transforms.Compose([ + transforms.Resize(image_size), + transforms.ToTensor(), + normalize, + ]) + return transform(data) + + +class PostProcessor(beam.DoFn): + """Post process PredictionResult to output filename and + prediction using torch.""" + def process(self, element): + filename, prediction_result = element + prediction = torch.argmax(prediction_result.inference, dim=0) + yield filename + ',' + str(int(prediction)) + + +def run_pipeline(options: PipelineOptions, args=None): + """Sets up PyTorch RunInference pipeline""" + model_class = torchvision.models.mobilenet_v2 + model_params = {'pretrained': False} Review Comment: this change is made here https://github.com/apache/beam/pull/17494 ########## build.gradle.kts: ########## @@ -312,25 +312,26 @@ tasks.register("python37PostCommit") { dependsOn(":sdks:python:test-suites:dataflow:py37:spannerioIT") dependsOn(":sdks:python:test-suites:direct:py37:spannerioIT") dependsOn(":sdks:python:test-suites:portable:py37:xlangSpannerIOIT") + dependsOn(":sdks:python:test-suites:dataflow:py37:torchTests") + } tasks.register("python38PostCommit") { dependsOn(":sdks:python:test-suites:dataflow:py38:postCommitIT") dependsOn(":sdks:python:test-suites:direct:py38:postCommitIT") dependsOn(":sdks:python:test-suites:direct:py38:hdfsIntegrationTest") dependsOn(":sdks:python:test-suites:portable:py38:postCommitPy38") + dependsOn(":sdks:python:test-suites:dataflow:py38:torchTests") Review Comment: Makes sense. ########## sdks/python/apache_beam/ml/inference/pytorch_it_test.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. +# + +# pylint: skip-file + +"""End-to-End test for Pytorch Inference""" + +import logging +import unittest +import uuid + +import pytest + +from apache_beam.io.filesystems import FileSystems +from apache_beam.testing.test_pipeline import TestPipeline + +try: + import torch + from apache_beam.examples.inference import pytorch_image_classification +except ImportError as e: + torch = None + +_EXPECTED_OUTPUTS = { + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005001.JPEG': '681', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005002.JPEG': '333', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005003.JPEG': '711', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005004.JPEG': '286', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005005.JPEG': '433', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005006.JPEG': '290', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005007.JPEG': '890', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005008.JPEG': '592', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005009.JPEG': '406', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005010.JPEG': '996', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005011.JPEG': '327', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005012.JPEG': '573' +} + + +def process_outputs(filepath): + with FileSystems().open(filepath) as f: + lines = f.readlines() + lines = [l.decode('utf-8').strip('\n') for l in lines] + return lines + + [email protected]( + torch is None, + 'Missing dependencies. ' + 'Test depends on torch, torchvision and pillow') +class PyTorchInference(unittest.TestCase): + @pytest.mark.uses_pytorch + @pytest.mark.it_postcommit + def test_predictions_output_file(self): + test_pipeline = TestPipeline(is_integration_test=True) + output_file_dir = 'gs://apache-beam-ml/temp_storage_end_to_end_testing/outputs' + output_file = '/'.join([output_file_dir, str(uuid.uuid4()), 'result.txt']) + file_of_image_names = 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/imagenet_samples.csv' Review Comment: Yes, I will update it soon(last step of this PR) once I clean the bucket ########## sdks/python/apache_beam/ml/inference/pytorch_it_test.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. +# + +# pylint: skip-file + +"""End-to-End test for Pytorch Inference""" + +import logging +import unittest +import uuid + +import pytest + +from apache_beam.io.filesystems import FileSystems +from apache_beam.testing.test_pipeline import TestPipeline + +try: + import torch + from apache_beam.examples.inference import pytorch_image_classification +except ImportError as e: + torch = None + +_EXPECTED_OUTPUTS = { + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005001.JPEG': '681', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005002.JPEG': '333', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005003.JPEG': '711', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005004.JPEG': '286', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005005.JPEG': '433', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005006.JPEG': '290', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005007.JPEG': '890', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005008.JPEG': '592', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005009.JPEG': '406', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005010.JPEG': '996', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005011.JPEG': '327', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005012.JPEG': '573' +} + + +def process_outputs(filepath): + with FileSystems().open(filepath) as f: + lines = f.readlines() + lines = [l.decode('utf-8').strip('\n') for l in lines] + return lines + + [email protected]( + torch is None, + 'Missing dependencies. ' + 'Test depends on torch, torchvision and pillow') Review Comment: Done ########## sdks/python/apache_beam/ml/inference/torch_tests_requirements.txt: ########## @@ -0,0 +1,20 @@ +# +# 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. +# + +torch>=1.7.1 +torchvision>=0.8.2 +pillow>=8.0.0 # bump the version to support Python 3.10 later Review Comment: I added the comment when I had a range between lower and upper but when I changed to the current code, forgot to remove the comment. Thanks for catching ########## sdks/python/apache_beam/examples/inference/pytorch_image_classification.py: ########## @@ -0,0 +1,122 @@ +# +# 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. +# + +import argparse +import io +import os +from functools import partial + +import apache_beam as beam +import torch +import torchvision +from apache_beam.io.filesystems import FileSystems +from apache_beam.ml.inference.api import RunInference +from apache_beam.ml.inference.pytorch import PytorchModelLoader +from apache_beam.options.pipeline_options import PipelineOptions +from apache_beam.options.pipeline_options import SetupOptions +from PIL import Image +from torchvision import transforms + + +def read_image(image_file_name: str, path_to_dir: str): + image_file_name = os.path.join(path_to_dir, image_file_name) + with FileSystems().open(image_file_name, 'r') as file: + data = Image.open(io.BytesIO(file.read())).convert('RGB') + return image_file_name, data + + +def preprocess_data(data): + image_size = (224, 224) + normalize = transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) + transform = transforms.Compose([ + transforms.Resize(image_size), + transforms.ToTensor(), + normalize, + ]) + return transform(data) + + +class PostProcessor(beam.DoFn): + """Post process PredictionResult to output filename and + prediction using torch.""" + def process(self, element): + filename, prediction_result = element + prediction = torch.argmax(prediction_result.inference, dim=0) + yield filename + ',' + str(int(prediction)) + + +def run_pipeline(options: PipelineOptions, args=None): + """Sets up PyTorch RunInference pipeline""" + model_class = torchvision.models.mobilenet_v2 + model_params = {'pretrained': False} Review Comment: This is how we pass a torch model class definition and the `model_params` are the params that are passed to the torch model class constructor. Note: here `torchvision.models.mobilenet_v2` is a torch Module class definition and this is used in RunInference API to create a torch Module object by passing `model_params` to Module's constructor ########## sdks/python/apache_beam/ml/inference/pytorch_it_test.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. +# + +# pylint: skip-file + +"""End-to-End test for Pytorch Inference""" + +import logging +import unittest +import uuid + +import pytest + +from apache_beam.io.filesystems import FileSystems +from apache_beam.testing.test_pipeline import TestPipeline + +try: + import torch + from apache_beam.examples.inference import pytorch_image_classification +except ImportError as e: + torch = None + +_EXPECTED_OUTPUTS = { + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005001.JPEG': '681', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005002.JPEG': '333', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005003.JPEG': '711', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005004.JPEG': '286', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005005.JPEG': '433', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005006.JPEG': '290', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005007.JPEG': '890', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005008.JPEG': '592', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005009.JPEG': '406', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005010.JPEG': '996', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005011.JPEG': '327', + 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/ILSVRC2012_val_00005012.JPEG': '573' +} + + +def process_outputs(filepath): + with FileSystems().open(filepath) as f: + lines = f.readlines() + lines = [l.decode('utf-8').strip('\n') for l in lines] + return lines + + [email protected]( + torch is None, + 'Missing dependencies. ' + 'Test depends on torch, torchvision and pillow') +class PyTorchInference(unittest.TestCase): + @pytest.mark.uses_pytorch + @pytest.mark.it_postcommit + def test_predictions_output_file(self): + test_pipeline = TestPipeline(is_integration_test=True) + output_file_dir = 'gs://apache-beam-ml/temp_storage_end_to_end_testing/outputs' + output_file = '/'.join([output_file_dir, str(uuid.uuid4()), 'result.txt']) + file_of_image_names = 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/imagenet_samples.csv' + base_output_files_dir = 'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs' + + model_path = 'gs://apache-beam-ml/temp_storage_end_to_end_testing/models/mobilenet_v2.pt' + extra_opts = { + 'input': file_of_image_names, + 'output': output_file, + 'model_path': model_path, Review Comment: Makes sense -- 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. 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