ds lkey Suite
1.0.0
System
Test suite extracted from ds lkey.
pts/deepsparse-1.3.2
zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario async
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario sync
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:nlp/sentiment_analysis/bert-base/pytorch/huggingface/sst2/12layer_pruned90-none --scenario async
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:nlp/sentiment_analysis/bert-base/pytorch/huggingface/sst2/12layer_pruned90-none --scenario sync
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario async
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario sync
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario async
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario sync
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario async
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario sync
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario async
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario sync
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/pruned90-none --scenario async
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/pruned90-none --scenario sync
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario async
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario sync
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
pts/deepsparse-1.3.2
zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario async
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
pts/deepsparse-1.3.2
zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario sync
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
pts/keydb-1.4.0
-t get -c 50
Test: GET - Parallel Connections: 50
pts/keydb-1.4.0
-t set -c 50
Test: SET - Parallel Connections: 50
pts/keydb-1.4.0
-t get -c 100
Test: GET - Parallel Connections: 100
pts/keydb-1.4.0
-t get -c 500
Test: GET - Parallel Connections: 500
pts/keydb-1.4.0
-t get -c 900
Test: GET - Parallel Connections: 900
pts/keydb-1.4.0
-t lpop -c 50
Test: LPOP - Parallel Connections: 50
pts/keydb-1.4.0
-t sadd -c 50
Test: SADD - Parallel Connections: 50
pts/keydb-1.4.0
-t set -c 100
Test: SET - Parallel Connections: 100
pts/keydb-1.4.0
-t set -c 500
Test: SET - Parallel Connections: 500
pts/keydb-1.4.0
-t set -c 900
Test: SET - Parallel Connections: 900
pts/keydb-1.4.0
-t hmset -c 50
Test: HMSET - Parallel Connections: 50
pts/keydb-1.4.0
-t lpop -c 100
Test: LPOP - Parallel Connections: 100
pts/keydb-1.4.0
-t lpop -c 500
Test: LPOP - Parallel Connections: 500
pts/keydb-1.4.0
-t lpop -c 900
Test: LPOP - Parallel Connections: 900
pts/keydb-1.4.0
-t lpush -c 50
Test: LPUSH - Parallel Connections: 50
pts/keydb-1.4.0
-t sadd -c 100
Test: SADD - Parallel Connections: 100
pts/keydb-1.4.0
-t sadd -c 500
Test: SADD - Parallel Connections: 500
pts/keydb-1.4.0
-t sadd -c 900
Test: SADD - Parallel Connections: 900
pts/keydb-1.4.0
-t hmset -c 100
Test: HMSET - Parallel Connections: 100
pts/keydb-1.4.0
-t hmset -c 500
Test: HMSET - Parallel Connections: 500
pts/keydb-1.4.0
-t hmset -c 900
Test: HMSET - Parallel Connections: 900
pts/keydb-1.4.0
-t lpush -c 100
Test: LPUSH - Parallel Connections: 100
pts/keydb-1.4.0
-t lpush -c 500
Test: LPUSH - Parallel Connections: 500
pts/keydb-1.4.0
-t lpush -c 900
Test: LPUSH - Parallel Connections: 900