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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2022/08/25 20:55:24 UTC
[GitHub] [beam] ryanthompson591 commented on a diff in pull request #21738: Inference benchmark tests
ryanthompson591 commented on code in PR #21738:
URL: https://github.com/apache/beam/pull/21738#discussion_r955381674
##########
.test-infra/jenkins/LoadTestsBuilder.groovy:
##########
@@ -43,7 +43,7 @@ class LoadTestsBuilder {
static void loadTest(context, String title, Runner runner, SDK sdk, Map<String, ?> options,
- String mainClass, List<String> jobSpecificSwitches = null) {
+ String mainClass, List<String> jobSpecificSwitches = null, String requirementsFile = null) {
Review Comment:
is the requirements file the same as a requirements.txt file? Optional- call it requirementsTxtFile then and I think it should be clear to beam devs.
##########
.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy:
##########
@@ -0,0 +1,170 @@
+/*
+ * 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 CommonJobProperties as commonJobProperties
+import LoadTestsBuilder as loadTestsBuilder
+import PhraseTriggeringPostCommitBuilder
+import CronJobBuilder
+
+def now = new Date().format("MMddHHmmss", TimeZone.getTimeZone('UTC'))
+
+def loadTestConfigurations = {
+ ->
+ [
+ // Benchmark test config. Add multiple configs for multiple models.
+ // (TODO): Add model name to experiments once decided on which models to use.
+ [
+ title : 'Pytorch Vision Classification with Resnet 101',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-imagenet-python' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
Review Comment:
is this a good tmp location? Maybe make a gs://temp-storage-for-perf-tests/tmp directory?
##########
.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy:
##########
@@ -0,0 +1,170 @@
+/*
+ * 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 CommonJobProperties as commonJobProperties
+import LoadTestsBuilder as loadTestsBuilder
+import PhraseTriggeringPostCommitBuilder
+import CronJobBuilder
+
+def now = new Date().format("MMddHHmmss", TimeZone.getTimeZone('UTC'))
+
+def loadTestConfigurations = {
+ ->
+ [
+ // Benchmark test config. Add multiple configs for multiple models.
+ // (TODO): Add model name to experiments once decided on which models to use.
+ [
+ title : 'Pytorch Vision Classification with Resnet 101',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-imagenet-python' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ requirements_file : 'apache_beam/ml/inference/torch_tests_requirements.txt',
+ experiments : 'no_use_multiple_sdk_containers',
+ publish_to_big_query : true,
+ metrics_dataset : 'beam_run_inference',
+ metrics_table : 'torch_inference_imagenet_results_resnet101',
+ input_options : '{}', // this option is not required for RunInference tests.
+ influx_measurement : 'torch_inference_imagenet_resnet101',
+ influx_db_name : InfluxDBCredentialsHelper.InfluxDBDatabaseName,
+ influx_hostname : InfluxDBCredentialsHelper.InfluxDBHostUrl,
+ // args defined in the performance test
+ pretrained_model_name : 'resnet101',
+ // args defined in the example.
+ input : 'gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt',
+ // TODO: make sure the model_state_dict_path weights are accurate.
+ model_state_dict_path : 'gs://apache-beam-ml/models/torchvision.models.resnet101.pth',
+ output : 'gs://temp-storage-for-end-to-end-tests/torch/result_' + now + '.txt'
+ ]
+ ],
+ [
+ title : 'Pytorch Imagenet Classification with Resnet 152',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-imagenet-python' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ requirements_file : 'apache_beam/ml/inference/torch_tests_requirements.txt',
+ experiments : 'no_use_multiple_sdk_containers',
+ publish_to_big_query : true,
+ metrics_dataset : 'beam_run_inference',
+ metrics_table : 'torch_inference_imagenet_results_resnet152',
+ input_options : '{}', // this option is not required for RunInference tests.
+ influx_measurement : 'torch_inference_imagenet_resnet152',
+ influx_db_name : InfluxDBCredentialsHelper.InfluxDBDatabaseName,
+ influx_hostname : InfluxDBCredentialsHelper.InfluxDBHostUrl,
+ // args defined in the performance test
+ pretrained_model_name : 'resnet152',
+ // args defined in the example.
+ input : 'gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt',
+ // TODO: make sure the model_state_dict_path weights are accurate.
+ model_state_dict_path : 'gs://apache-beam-ml/models/torchvision.models.resnet152.pth',
+ output : 'gs://temp-storage-for-end-to-end-tests/torch/result_' + now + '.txt'
+ ]
+ ],
+ // Pytorch language modeling test using HuggingFace BERT models
+ [
+ title : 'Pytorch Lanugaue Modeling using Hugging face bert-base-uncased model',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_language_modeling_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-language-modeling-bert-base-uncased' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ requirements_file : 'apache_beam/ml/inference/torch_tests_requirements.txt',
+ pickle_library : 'cloudpickle',
+ experiments : 'no_use_multiple_sdk_containers',
+ publish_to_big_query : true,
+ metrics_dataset : 'beam_run_inference',
+ metrics_table : 'torch_language_modeling_bert_base_uncased',
+ input_options : '{}', // this option is not required for RunInference tests.
+ influx_measurement : 'torch_language_modeling_bert_base_uncased',
+ influx_db_name : InfluxDBCredentialsHelper.InfluxDBDatabaseName,
+ influx_hostname : InfluxDBCredentialsHelper.InfluxDBHostUrl,
+ // args defined in the example.
+ input : 'gs://apache-beam-ml/testing/inputs/sentences_50k.txt',
+ // TODO: make sure the model_state_dict_path weights are accurate.
+ bert_tokenizer : 'bert-base-uncased',
+ model_state_dict_path : 'gs://apache-beam-ml/models/huggingface.BertForMaskedLM.bert-base-uncased.pth',
+ output : 'gs://temp-storage-for-end-to-end-tests/torch/result_' + now + '.txt',
+ ]
+ ],
+ [
+ title : 'Pytorch Langauge Modeling using Hugging Face bert-large-uncased model',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_language_modeling_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-language-modeling-bert-large-cased' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ requirements_file : 'apache_beam/ml/inference/torch_tests_requirements.txt',
+ pickle_library : 'cloudpickle',
+ experiments : 'no_use_multiple_sdk_containers',
+ publish_to_big_query : true,
+ metrics_dataset : 'beam_run_inference',
+ metrics_table : 'torch_language_modeling_bert_large_uncased',
+ input_options : '{}', // this option is not required for RunInference tests.
+ influx_measurement : 'torch_language_modeling_bert_large_uncased',
+ influx_db_name : InfluxDBCredentialsHelper.InfluxDBDatabaseName,
+ influx_hostname : InfluxDBCredentialsHelper.InfluxDBHostUrl,
+ // args defined in the example.
+ input : 'gs://apache-beam-ml/testing/inputs/sentences_50k.txt',
+ // TODO: make sure the model_state_dict_path weights are accurate.
+ bert_tokenizer : 'bert-large-uncased',
+ model_state_dict_path : 'gs://apache-beam-ml/models/huggingface.BertForMaskedLM.bert-large-uncased.pth',
+ output : 'gs://temp-storage-for-end-to-end-tests/torch/result_' + now + '.txt'
+ ]
+ ],
+ ]
+}
+
+def loadTestJob = { scope ->
+ List<Map> testScenarios = loadTestConfigurations()
+ for (Map testConfig: testScenarios){
+ commonJobProperties.setTopLevelMainJobProperties(scope, 'master', 180)
+ loadTestsBuilder.loadTest(scope, testConfig.title, testConfig.runner, CommonTestProperties.SDK.PYTHON, testConfig.pipelineOptions, testConfig.test, null, testConfig.pipelineOptions.requirements_file)
+ }
+}
+
+PhraseTriggeringPostCommitBuilder.postCommitJob(
+ 'beam_Inference_Python_Benchmarks_Dataflow',
+ 'Run Inference Benchmarks',
+ 'Inference benchmarks on Dataflow(\"Run Inference Benchmarks"\"")',
+ this
+ ) {
+ loadTestJob(delegate)
+ }
+
+// TODO(anandinguva): Change the cron job to run once a day
+CronJobBuilder.cronJob(
+ 'beam_Inference_Python_Benchmarks_Dataflow', 'H 2 * * *',
Review Comment:
what is `H 2 * *`
##########
.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy:
##########
@@ -0,0 +1,170 @@
+/*
+ * 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 CommonJobProperties as commonJobProperties
+import LoadTestsBuilder as loadTestsBuilder
+import PhraseTriggeringPostCommitBuilder
+import CronJobBuilder
+
+def now = new Date().format("MMddHHmmss", TimeZone.getTimeZone('UTC'))
+
+def loadTestConfigurations = {
+ ->
+ [
+ // Benchmark test config. Add multiple configs for multiple models.
+ // (TODO): Add model name to experiments once decided on which models to use.
+ [
+ title : 'Pytorch Vision Classification with Resnet 101',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-imagenet-python' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ requirements_file : 'apache_beam/ml/inference/torch_tests_requirements.txt',
+ experiments : 'no_use_multiple_sdk_containers',
+ publish_to_big_query : true,
+ metrics_dataset : 'beam_run_inference',
+ metrics_table : 'torch_inference_imagenet_results_resnet101',
+ input_options : '{}', // this option is not required for RunInference tests.
+ influx_measurement : 'torch_inference_imagenet_resnet101',
+ influx_db_name : InfluxDBCredentialsHelper.InfluxDBDatabaseName,
+ influx_hostname : InfluxDBCredentialsHelper.InfluxDBHostUrl,
+ // args defined in the performance test
+ pretrained_model_name : 'resnet101',
+ // args defined in the example.
+ input : 'gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt',
+ // TODO: make sure the model_state_dict_path weights are accurate.
+ model_state_dict_path : 'gs://apache-beam-ml/models/torchvision.models.resnet101.pth',
+ output : 'gs://temp-storage-for-end-to-end-tests/torch/result_' + now + '.txt'
+ ]
+ ],
+ [
+ title : 'Pytorch Imagenet Classification with Resnet 152',
+ test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',
+ runner : CommonTestProperties.Runner.DATAFLOW,
+ pipelineOptions: [
+ job_name : 'benchmark-tests-pytorch-imagenet-python' + now,
+ project : 'apache-beam-testing',
+ region : 'us-central1',
+ staging_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ temp_location : 'gs://temp-storage-for-perf-tests/loadtests',
+ requirements_file : 'apache_beam/ml/inference/torch_tests_requirements.txt',
+ experiments : 'no_use_multiple_sdk_containers',
+ publish_to_big_query : true,
+ metrics_dataset : 'beam_run_inference',
+ metrics_table : 'torch_inference_imagenet_results_resnet152',
+ input_options : '{}', // this option is not required for RunInference tests.
+ influx_measurement : 'torch_inference_imagenet_resnet152',
+ influx_db_name : InfluxDBCredentialsHelper.InfluxDBDatabaseName,
+ influx_hostname : InfluxDBCredentialsHelper.InfluxDBHostUrl,
+ // args defined in the performance test
+ pretrained_model_name : 'resnet152',
+ // args defined in the example.
+ input : 'gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt',
+ // TODO: make sure the model_state_dict_path weights are accurate.
+ model_state_dict_path : 'gs://apache-beam-ml/models/torchvision.models.resnet152.pth',
+ output : 'gs://temp-storage-for-end-to-end-tests/torch/result_' + now + '.txt'
Review Comment:
will this output conflict with the output from the other tests since it has the same name?
##########
.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy:
##########
@@ -0,0 +1,170 @@
+/*
+ * 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 CommonJobProperties as commonJobProperties
+import LoadTestsBuilder as loadTestsBuilder
+import PhraseTriggeringPostCommitBuilder
+import CronJobBuilder
+
+def now = new Date().format("MMddHHmmss", TimeZone.getTimeZone('UTC'))
+
+def loadTestConfigurations = {
+ ->
+ [
+ // Benchmark test config. Add multiple configs for multiple models.
+ // (TODO): Add model name to experiments once decided on which models to use.
Review Comment:
If possible have an issue with the todo.
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