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Cinn conver case 02 (#3046)
* fix cin converge case * fix cin converge case * fix cin converge case * fix cin converge case * fix cin converge case * fix pdx cinn case, test=model
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‎framework/e2e/cinn_converge/CLIP_vit_base_patch16_224_CINN.sh‎

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python main.py -c paddlex/configs/modules/image_classification/CLIP_vit_base_patch16_224.yaml -o Global.mode=train -o Train.num_classes=1000 -o Train.epochs_iters=50 -o Train.batch_size=64 -o Train.learning_rate=0.00015 -o Train.pretrain_weight_path=None -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.dataset_dir=../ILSVRC2012/ -o Global.output='./output/image_classification/CLIP_vit_base_patch16_224_CINN' -o Train.dy2st=True
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python main.py -c paddlex/configs/modules/image_classification/CLIP_vit_base_patch16_224.yaml -o Global.mode=train -o Train.num_classes=1000 -o Train.epochs_iters=50 -o Train.batch_size=64 -o Train.learning_rate=0.00015 -o Train.pretrain_weight_path=https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/foundation_models/CLIP_vit_base_patch16_224.pdparams -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.dataset_dir=../ILSVRC2012/ -o Global.output='./output/image_classification/CLIP_vit_base_patch16_224_CINN' -o Train.dy2st=True

‎framework/e2e/cinn_converge/CLIP_vit_base_patch16_224_dy.sh‎

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python main.py -c paddlex/configs/modules/image_classification/CLIP_vit_base_patch16_224.yaml -o Global.mode=train -o Train.num_classes=1000 -o Train.epochs_iters=50 -o Train.batch_size=64 -o Train.learning_rate=0.00015 -o Train.pretrain_weight_path=None -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.dataset_dir=../ILSVRC2012/ -o Global.output='./output/image_classification/CLIP_vit_base_patch16_224_dy'
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python main.py -c paddlex/configs/modules/image_classification/CLIP_vit_base_patch16_224.yaml -o Global.mode=train -o Train.num_classes=1000 -o Train.epochs_iters=50 -o Train.batch_size=64 -o Train.learning_rate=0.00015 -o Train.pretrain_weight_path=https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/foundation_models/CLIP_vit_base_patch16_224.pdparams -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.dataset_dir=../ILSVRC2012/ -o Global.output='./output/image_classification/CLIP_vit_base_patch16_224_dy'

‎framework/e2e/cinn_converge/Co-Deformable-DETR-R50_CINN.sh‎

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python main.py -c paddlex/configs/modules/object_detection/Co-Deformable-DETR-R50.yaml -o Global.mode=train -o Global.dataset_dir=../coco -o Train.num_classes=80 -o Train.epochs_iters=12 -o Train.batch_size=2 -o Train.learning_rate=0.0002 -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.output='./output/object_detection/Co-Deformable-DETR-R50_CINN' -o Train.dy2st=True
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python main.py -c paddlex/configs/modules/object_detection/Co-Deformable-DETR-R50.yaml -o Global.mode=train -o Global.dataset_dir=../coco -o Train.num_classes=80 -o Train.epochs_iters=12 -o Train.batch_size=2 -o Train.learning_rate=0.0002 -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Train.pretrain_weight_path=None -o Global.output='./output/object_detection/Co-Deformable-DETR-R50_CINN' -o Train.dy2st=True

‎framework/e2e/cinn_converge/Co-Deformable-DETR-R50_dy.sh‎

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python main.py -c paddlex/configs/modules/object_detection/Co-Deformable-DETR-R50.yaml -o Global.mode=train -o Global.dataset_dir=../coco -o Train.num_classes=80 -o Train.epochs_iters=12 -o Train.batch_size=2 -o Train.learning_rate=0.0002 -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.output='./output/object_detection/Co-Deformable-DETR-R50_dy'
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python main.py -c paddlex/configs/modules/object_detection/Co-Deformable-DETR-R50.yaml -o Global.mode=train -o Global.dataset_dir=../coco -o Train.num_classes=80 -o Train.epochs_iters=12 -o Train.batch_size=2 -o Train.learning_rate=0.0002 -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Train.pretrain_weight_path=None -o Global.output='./output/object_detection/Co-Deformable-DETR-R50_dy'

‎framework/e2e/cinn_converge/Deeplabv3-R50_CINN.sh‎

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python main.py -c paddlex/configs/modules/semantic_segmentation/Deeplabv3-R50.yaml \
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-o Global.mode=train -o Global.dataset_dir=../cityscapes \
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-o Train.num_classes=19 -o Train.epochs_iters=160000 -o Train.batch_size=1 \
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-o Train.warmup_steps=0 -o Train.learning_rate=0.005 \
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-o Global.device=gpu:0,1,2,3,4,5,6,7
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-o Global.output='./output/semantic_segmentation/Deeplabv3-R50_CINN'
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-o Train.num_classes=19 -o Train.epochs_iters=80000 -o Train.batch_size=4 \
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-o Train.warmup_steps=0 -o Train.learning_rate=0.04 \
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-o Global.device=gpu:0,1,2,3,4,5,6,7 \
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-o Global.output='./output/semantic_segmentation/Deeplabv3-R50_CINN' \
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-o Train.dy2st=True

‎framework/e2e/cinn_converge/Deeplabv3-R50_dy.sh‎

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python main.py -c paddlex/configs/modules/semantic_segmentation/Deeplabv3-R50.yaml \
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-o Global.mode=train -o Global.dataset_dir=../cityscapes \
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-o Train.num_classes=19 -o Train.epochs_iters=160000 -o Train.batch_size=1 \
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-o Train.warmup_steps=0 -o Train.learning_rate=0.005 \
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-o Global.device=gpu:0,1,2,3,4,5,6,7
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-o Train.num_classes=19 -o Train.epochs_iters=80000 -o Train.batch_size=4 \
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-o Train.warmup_steps=0 -o Train.learning_rate=0.04 \
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-o Global.device=gpu:0,1,2,3,4,5,6,7 \
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-o Global.output='./output/semantic_segmentation/Deeplabv3-R50_dy'

‎framework/e2e/cinn_converge/MaskFormer_small_CINN.sh‎

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-o Global.mode=train -o Global.dataset_dir=../ADEChallengeData2016 \
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-o Train.num_classes=150 -o Train.epochs_iters=160000 -o Train.batch_size=4 \
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-o Train.warmup_steps=1500 -o Train.learning_rate=0.00006 \
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-o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.output='./output/semantic_segmentation/MaskFormer_small_CINN' -o Train.dy2st=True
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-o Global.device=gpu:0,1,2,3,4,5,6,7 -o Train.pretrain_weight_path=None -o Global.output='./output/semantic_segmentation/MaskFormer_small_CINN' -o Train.dy2st=True

‎framework/e2e/cinn_converge/MaskFormer_small_dy.sh‎

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-o Global.mode=train -o Global.dataset_dir=../ADEChallengeData2016 \
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-o Train.num_classes=150 -o Train.epochs_iters=160000 -o Train.batch_size=4 \
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-o Train.warmup_steps=1500 -o Train.learning_rate=0.00006 \
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-o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.output='./output/semantic_segmentation/MaskFormer_small_dy'
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-o Global.device=gpu:0,1,2,3,4,5,6,7 -o Train.pretrain_weight_path=None -o Global.output='./output/semantic_segmentation/MaskFormer_small_dy'

‎framework/e2e/cinn_converge/MobileNetV2_x1_0_CINN.sh‎

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python main.py -c paddlex/configs/modules/image_classification/MobileNetV2_x1_0.yaml -o Global.mode=train -o Train.num_classes=1000 -o Train.epochs_iters=240 -o Train.batch_size=32 -o Train.learning_rate=0.045 -o Train.pretrain_weight_path=None -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.dataset_dir=../ILSVRC2012/ -o Global.output='./output/image_classification/MobileNetV2_x1_0_CINN' -o Train.dy2st=True

‎framework/e2e/cinn_converge/MobileNetV2_x1_0_dy.sh‎

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python main.py -c paddlex/configs/modules/image_classification/MobileNetV2_x1_0.yaml -o Global.mode=train -o Train.num_classes=1000 -o Train.epochs_iters=240 -o Train.batch_size=32 -o Train.learning_rate=0.045 -o Train.pretrain_weight_path=None -o Global.device=gpu:0,1,2,3,4,5,6,7 -o Global.dataset_dir=../ILSVRC2012/ -o Global.output='./output/image_classification/MobileNetV2_x1_0_dy'

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