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https://issues.apache.org/jira/browse/BEAM-14068?focusedWorklogId=771599&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-771599
]
ASF GitHub Bot logged work on BEAM-14068:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 17/May/22 21:07
Start Date: 17/May/22 21:07
Worklog Time Spent: 10m
Work Description: AnandInguva commented on code in PR #17462:
URL: https://github.com/apache/beam/pull/17462#discussion_r875262724
##########
sdks/python/apache_beam/ml/inference/pytorch_it_test.py:
##########
@@ -0,0 +1,99 @@
+#
+# 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.ml.inference.examples 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
+ @pytest.mark.sickbay_direct
+ @pytest.mark.sickbay_spark
+ @pytest.mark.sickbay_flink
+ 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 = '/'.join([output_file_dir, str(uuid.uuid4()), 'result'])
+ input_file_dir =
'gs://apache-beam-ml/temp_storage_end_to_end_testing/inputs/imagenet_samples.csv'
Review Comment:
Yes.
Issue Time Tracking
-------------------
Worklog Id: (was: 771599)
Time Spent: 4h 20m (was: 4h 10m)
> RunInference Benchmarking tests
> -------------------------------
>
> Key: BEAM-14068
> URL: https://issues.apache.org/jira/browse/BEAM-14068
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Anand Inguva
> Assignee: Anand Inguva
> Priority: P2
> Time Spent: 4h 20m
> Remaining Estimate: 0h
>
> RunInference benchmarks will evaluate performance of Pipelines, which
> represent common use cases of Beam + Dataflow in Pytorch, sklearn and
> possibly TFX. These benchmarks would be the integration tests that exercise
> several software components using Beam, PyTorch, Scikit learn and TensorFlow
> extended.
> we would use the datasets that's available publicly (Eg; Kaggle).
> Size: small / 10 GB / 1 TB etc
> The default execution runner would be Dataflow unless specified otherwise.
> These tests would be run very less frequently(every release cycle).
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