Fix time_tests runs when models_cache enabled (#5265)

* Set ``"additionalProperties": true` to enable 'use_model_cache' in time_tests

* Limit tests scope in desktop_test_config_cache.yml
This commit is contained in:
Vitaliy Urusovskij 2021-04-17 00:12:08 +03:00 committed by GitHub
parent d3504963cb
commit db2de2fb19
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2 changed files with 1 additions and 512 deletions

View File

@ -6,14 +6,6 @@
precision: FP16
framework: caffe2
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/resnet-50-pytorch/caffe2/FP16/resnet-50-pytorch.xml
name: resnet-50-pytorch
precision: FP16
framework: caffe2
use_model_cache: true
- device:
name: CPU
model:
@ -22,14 +14,6 @@
precision: FP16-INT8
framework: caffe2
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/resnet-50-pytorch/caffe2/FP16-INT8/resnet-50-pytorch.xml
name: resnet-50-pytorch
precision: FP16-INT8
framework: caffe2
use_model_cache: true
- device:
name: CPU
model:
@ -38,14 +22,6 @@
precision: FP16
framework: caffe2
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/mobilenet-v2/caffe2/FP16/mobilenet-v2.xml
name: mobilenet-v2
precision: FP16
framework: caffe2
use_model_cache: true
- device:
name: CPU
model:
@ -54,490 +30,3 @@
precision: FP16-INT8
framework: caffe2
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/mobilenet-v2/caffe2/FP16-INT8/mobilenet-v2.xml
name: mobilenet-v2
precision: FP16-INT8
framework: caffe2
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/faster_rcnn_resnet101_coco/tf/FP16/faster_rcnn_resnet101_coco.xml
name: faster_rcnn_resnet101_coco
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/faster_rcnn_resnet101_coco/tf/FP16/faster_rcnn_resnet101_coco.xml
name: faster_rcnn_resnet101_coco
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/faster_rcnn_resnet101_coco/tf/FP16-INT8/faster_rcnn_resnet101_coco.xml
name: faster_rcnn_resnet101_coco
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/faster_rcnn_resnet101_coco/tf/FP16-INT8/faster_rcnn_resnet101_coco.xml
name: faster_rcnn_resnet101_coco
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/faster-rcnn-resnet101-coco-sparse-60-0001/tf/FP16/faster-rcnn-resnet101-coco-sparse-60-0001.xml
name: faster-rcnn-resnet101-coco-sparse-60-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/faster-rcnn-resnet101-coco-sparse-60-0001/tf/FP16/faster-rcnn-resnet101-coco-sparse-60-0001.xml
name: faster-rcnn-resnet101-coco-sparse-60-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/faster-rcnn-resnet101-coco-sparse-60-0001/tf/FP16-INT8/faster-rcnn-resnet101-coco-sparse-60-0001.xml
name: faster-rcnn-resnet101-coco-sparse-60-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/faster-rcnn-resnet101-coco-sparse-60-0001/tf/FP16-INT8/faster-rcnn-resnet101-coco-sparse-60-0001.xml
name: faster-rcnn-resnet101-coco-sparse-60-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v1/tf/FP16/googlenet-v1.xml
name: googlenet-v1
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v1/tf/FP16/googlenet-v1.xml
name: googlenet-v1
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v1/tf/FP16-INT8/googlenet-v1.xml
name: googlenet-v1
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v1/tf/FP16-INT8/googlenet-v1.xml
name: googlenet-v1
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v3/tf/FP16/googlenet-v3.xml
name: googlenet-v3
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v3/tf/FP16/googlenet-v3.xml
name: googlenet-v3
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v3/tf/FP16-INT8/googlenet-v3.xml
name: googlenet-v3
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/googlenet-v3/tf/FP16-INT8/googlenet-v3.xml
name: googlenet-v3
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/ssd512/caffe/FP16/ssd512.xml
name: ssd512
precision: FP16
framework: caffe
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/ssd512/caffe/FP16/ssd512.xml
name: ssd512
precision: FP16
framework: caffe
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/ssd512/caffe/FP16-INT8/ssd512.xml
name: ssd512
precision: FP16-INT8
framework: caffe
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/ssd512/caffe/FP16-INT8/ssd512.xml
name: ssd512
precision: FP16-INT8
framework: caffe
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-0001/tf/FP16/yolo-v2-ava-0001.xml
name: yolo-v2-ava-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-0001/tf/FP16/yolo-v2-ava-0001.xml
name: yolo-v2-ava-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-0001/tf/FP16-INT8/yolo-v2-ava-0001.xml
name: yolo-v2-ava-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-0001/tf/FP16-INT8/yolo-v2-ava-0001.xml
name: yolo-v2-ava-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-35-0001/tf/FP16/yolo-v2-ava-sparse-35-0001.xml
name: yolo-v2-ava-sparse-35-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-35-0001/tf/FP16/yolo-v2-ava-sparse-35-0001.xml
name: yolo-v2-ava-sparse-35-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-35-0001/tf/FP16-INT8/yolo-v2-ava-sparse-35-0001.xml
name: yolo-v2-ava-sparse-35-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-35-0001/tf/FP16-INT8/yolo-v2-ava-sparse-35-0001.xml
name: yolo-v2-ava-sparse-35-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-70-0001/tf/FP16/yolo-v2-ava-sparse-70-0001.xml
name: yolo-v2-ava-sparse-70-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-70-0001/tf/FP16/yolo-v2-ava-sparse-70-0001.xml
name: yolo-v2-ava-sparse-70-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-70-0001/tf/FP16-INT8/yolo-v2-ava-sparse-70-0001.xml
name: yolo-v2-ava-sparse-70-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-ava-sparse-70-0001/tf/FP16-INT8/yolo-v2-ava-sparse-70-0001.xml
name: yolo-v2-ava-sparse-70-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-0001/tf/FP16/yolo-v2-tiny-ava-0001.xml
name: yolo-v2-tiny-ava-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-0001/tf/FP16/yolo-v2-tiny-ava-0001.xml
name: yolo-v2-tiny-ava-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-0001/tf/FP16-INT8/yolo-v2-tiny-ava-0001.xml
name: yolo-v2-tiny-ava-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-0001/tf/FP16-INT8/yolo-v2-tiny-ava-0001.xml
name: yolo-v2-tiny-ava-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-30-0001/tf/FP16/yolo-v2-tiny-ava-sparse-30-0001.xml
name: yolo-v2-tiny-ava-sparse-30-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-30-0001/tf/FP16/yolo-v2-tiny-ava-sparse-30-0001.xml
name: yolo-v2-tiny-ava-sparse-30-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-30-0001/tf/FP16-INT8/yolo-v2-tiny-ava-sparse-30-0001.xml
name: yolo-v2-tiny-ava-sparse-30-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-30-0001/tf/FP16-INT8/yolo-v2-tiny-ava-sparse-30-0001.xml
name: yolo-v2-tiny-ava-sparse-30-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-60-0001/tf/FP16/yolo-v2-tiny-ava-sparse-60-0001.xml
name: yolo-v2-tiny-ava-sparse-60-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-60-0001/tf/FP16/yolo-v2-tiny-ava-sparse-60-0001.xml
name: yolo-v2-tiny-ava-sparse-60-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-60-0001/tf/FP16-INT8/yolo-v2-tiny-ava-sparse-60-0001.xml
name: yolo-v2-tiny-ava-sparse-60-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/yolo-v2-tiny-ava-sparse-60-0001/tf/FP16-INT8/yolo-v2-tiny-ava-sparse-60-0001.xml
name: yolo-v2-tiny-ava-sparse-60-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/squeezenet1.1/caffe2/FP16/squeezenet1.1.xml
name: squeezenet1.1
precision: FP16
framework: caffe2
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/squeezenet1.1/caffe2/FP16/squeezenet1.1.xml
name: squeezenet1.1
precision: FP16
framework: caffe2
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/squeezenet1.1/caffe2/FP16-INT8/squeezenet1.1.xml
name: squeezenet1.1
precision: FP16-INT8
framework: caffe2
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/squeezenet1.1/caffe2/FP16-INT8/squeezenet1.1.xml
name: squeezenet1.1
precision: FP16-INT8
framework: caffe2
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-0001/tf/FP16/icnet-camvid-ava-0001.xml
name: icnet-camvid-ava-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-0001/tf/FP16/icnet-camvid-ava-0001.xml
name: icnet-camvid-ava-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-0001/tf/FP16-INT8/icnet-camvid-ava-0001.xml
name: icnet-camvid-ava-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-0001/tf/FP16-INT8/icnet-camvid-ava-0001.xml
name: icnet-camvid-ava-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-30-0001/tf/FP16/icnet-camvid-ava-sparse-30-0001.xml
name: icnet-camvid-ava-sparse-30-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-30-0001/tf/FP16/icnet-camvid-ava-sparse-30-0001.xml
name: icnet-camvid-ava-sparse-30-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-30-0001/tf/FP16-INT8/icnet-camvid-ava-sparse-30-0001.xml
name: icnet-camvid-ava-sparse-30-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-30-0001/tf/FP16-INT8/icnet-camvid-ava-sparse-30-0001.xml
name: icnet-camvid-ava-sparse-30-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-60-0001/tf/FP16/icnet-camvid-ava-sparse-60-0001.xml
name: icnet-camvid-ava-sparse-60-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-60-0001/tf/FP16/icnet-camvid-ava-sparse-60-0001.xml
name: icnet-camvid-ava-sparse-60-0001
precision: FP16
framework: tf
use_model_cache: true
- device:
name: CPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-60-0001/tf/FP16-INT8/icnet-camvid-ava-sparse-60-0001.xml
name: icnet-camvid-ava-sparse-60-0001
precision: FP16-INT8
framework: tf
use_model_cache: true
- device:
name: GPU
model:
path: ${VPUX_MODELS_PKG}/icnet-camvid-ava-sparse-60-0001/tf/FP16-INT8/icnet-camvid-ava-sparse-60-0001.xml
name: icnet-camvid-ava-sparse-60-0001
precision: FP16-INT8
framework: tf

View File

@ -207,7 +207,7 @@ def validate_test_case(request, test_info):
}
},
"required": ["device", "model"],
"additionalProperties": false
"additionalProperties": true
}
"""
schema = json.loads(schema)