ML pipelines: RunInference - OSS Image Object detection, OSS Image Captioning, OSS Image Classification

.github/workflows/load-tests-pipeline-options/beam_Inference_Python_Benchmarks_Dataflow_Pytorch_Image_Captioning.txt

@@ -0,0 +1,37 @@
+#  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.
+
+--region=us-central1
+--worker_machine_type=n1-standard-4
+--num_workers=50
+--disk_size_gb=50
+--autoscaling_algorithm=NONE
+--staging_location=gs://temp-storage-for-perf-tests/loadtests
+--temp_location=gs://temp-storage-for-perf-tests/loadtests
+--requirements_file=apache_beam/ml/inference/pytorch_image_captioning_requirements.txt
+--publish_to_big_query=true
+--metrics_dataset=beam_run_inference
+--input_options={}
+--influx_measurement=result_torch_inference_image_captioning
+--input=gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt
+--blip_model_name=Salesforce/blip-image-captioning-base
+--blip_batch_size=4
+--num_captions=5
+--max_new_tokens=30
+--num_beams=5
+--clip_model_name=openai/clip-vit-base-patch32
+--clip_batch_size=8
+--clip_score_normalize=false
+--runner=DataflowRunner
+--experiments=use_runner_v2

.github/workflows/load-tests-pipeline-options/beam_Inference_Python_Benchmarks_Dataflow_Pytorch_Image_Classification_Rightfit.txt

@@ -0,0 +1,41 @@
+#  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.
+
+--region=us-central1
+--machine_type=n1-standard-4
+--num_workers=50
+--disk_size_gb=50
+--autoscaling_algorithm=NONE
+--staging_location=gs://temp-storage-for-perf-tests/loadtests
+--temp_location=gs://temp-storage-for-perf-tests/loadtests
+--requirements_file=apache_beam/ml/inference/pytorch_rightfit_requirements.txt
+--publish_to_big_query=true
+--metrics_dataset=beam_run_inference
+--influx_measurement=torch_inference_imagenet_stream_rightfit
+--pretrained_model_name=efficientnet_b0
+--input_file=gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt
+--runner=DataflowRunner
+--mode=streaming
+--input_mode=gcs_uris
+--input_options={}
+--pubsub_topic=projects/apache-beam-testing/topics/images_topic
+--pubsub_subscription=projects/apache-beam-testing/subscriptions/images_subscription
+--model_state_dict_path=gs://apache-beam-ml/models/efficientnet_b0_state_dict.pth
+--image_size=224
+--top_k=5
+--inference_batch_size=auto
+--window_sec=60
+--trigger_proc_time_sec=30

.github/workflows/load-tests-pipeline-options/beam_Inference_Python_Benchmarks_Dataflow_Pytorch_Image_Object_Detection.txt

@@ -0,0 +1,37 @@
+#  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.
+
+--region=us-central1
+--worker_machine_type=n1-standard-4
+--num_workers=50
+--disk_size_gb=50
+--autoscaling_algorithm=NONE
+--staging_location=gs://temp-storage-for-perf-tests/loadtests
+--temp_location=gs://temp-storage-for-perf-tests/loadtests
+--requirements_file=apache_beam/ml/inference/pytorch_image_object_detection_requirements.txt
+--publish_to_big_query=true
+--metrics_dataset=beam_run_inference
+--input_options={}
+--influx_measurement=result_torch_inference_image_object_detection_batch
+--pretrained_model_name=fasterrcnn_resnet50_fpn
+--inference_batch_size=8
+--resize_shorter_side=800
+--score_threshold=0.5
+--max_detections=50
+--input=gs://apache-beam-ml/testing/inputs/openimage_50k_benchmark.txt
+--model_state_dict_path=gs://apache-beam-ml/models/torchvision.detection.fasterrcnn_resnet50_fpn.pth
+--runner=DataflowRunner
+--experiments=use_runner_v2

.test-infra/tools/refresh_looker_metrics.py

@@ -43,6 +43,25 @@
     ("82", ["263", "264", "265", "266", "267"]),  # PyTorch Sentiment Streaming DistilBERT base uncased
     ("85", ["268", "269", "270", "271", "272"]),  # PyTorch Sentiment Batch DistilBERT base uncased
     ("86", ["284", "285", "286", "287", "288"]),  # VLLM Batch Gemma
+
+    # PyTorch Image Classification EfficientNet-B0 Streaming (Right-fit) CPU
+    ("92", ["289", "290", "291", "292", "293"]),
+    ("97", ["306", "307", "308", "309", "310"]),
+    ("98", ["311", "312", "313", "314", "315"]),
+    ("99", ["316", "317", "318", "319", "320"]),
+
+    # PyTorch Image Object Detection Faster R-CNN ResNet-50 Batch CPU
+    ("93", ["294", "295", "296", "298", "299"]),
+    ("100", ["321", "322", "323", "324", "325"]),
+    ("101", ["326", "327", "328", "329", "330"]),
+    ("102", ["331", "332", "333", "334", "335"]),
+
+    # PyTorch Image Captioning BLIP + CLIP Batch CPU
+    ("94", ["297", "300", "301", "302", "303"]),
+    ("103", ["336", "337", "338", "339", "340"]),
+    ("104", ["341", "342", "343", "344", "345"]),
+    ("105", ["346", "347", "348", "349", "350"]),
+
     ("96", ["270", "304", "305", "353", "354"]),   # Table Row Inference Sklearn Batch
     ("106", ["355", "356", "357", "358", "359"])   # Table Row Inference Sklearn Streaming
 ]