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111 lines
2.5 KiB
111 lines
2.5 KiB
from towhee import ops
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from timm_image import TimmImage
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import torch
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f = open('torchscript.csv', 'a+')
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f.write('model_name,run_op,save_torchscript,check_result\n')
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# models = TimmImage.supported_model_names()[:1]
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models = [
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'vgg11',
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'resnet18',
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'resnetv2_50',
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'seresnet33ts',
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'skresnet18',
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'resnext26ts',
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'seresnext26d_32x4d',
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'skresnext50_32x4d',
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'convit_base',
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'inception_v4',
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'efficientnet_b0',
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'tf_efficientnet_b0',
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'swin_base_patch4_window7_224',
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'vit_base_patch8_224',
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'beit_base_patch16_224',
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'convnext_base',
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'crossvit_9_240',
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'convmixer_768_32',
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'coat_lite_mini',
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'inception_v3',
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'cait_m36_384',
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'cspdarknet53',
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'deit_base_distilled_patch16_224',
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'densenet121',
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'dla34',
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'dm_nfnet_f0',
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'nf_regnet_b1',
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'nf_resnet50',
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'dpn68',
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'ese_vovnet19b_dw',
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'fbnetc_100',
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'fbnetv3_b',
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'halonet26t',
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'eca_halonext26ts',
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'sehalonet33ts',
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'hardcorenas_a',
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'hrnet_w18',
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'jx_nest_base',
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'lcnet_050',
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'levit_128',
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'mixer_b16_224',
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'mixnet_s',
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'mnasnet_100',
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'mobilenetv2_050',
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'mobilenetv3_large_100',
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'nasnetalarge',
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'pit_b_224',
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'pnasnet5large',
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'regnetx_002',
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'repvgg_a2',
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'res2net50_14w_8s',
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'res2next50',
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'resmlp_12_224',
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'resnest14d',
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'rexnet_100',
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'selecsls42b',
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'semnasnet_075',
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'tinynet_a',
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'tnt_s_patch16_224',
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'tresnet_l',
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'twins_pcpvt_base',
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'visformer_small',
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'xception',
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'xcit_large_24_p8_224',
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'ghostnet_100',
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'gmlp_s16_224',
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'lambda_resnet26rpt_256',
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'spnasnet_100',
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]
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decoder = ops.image_decode()
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data = decoder('./towhee.jpeg')
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for name in models:
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f.write(f'{name},')
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try:
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op = TimmImage(model_name=name)
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out1 = op(data)
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f.write('success,')
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except Exception as e:
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f.write('fail')
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print(f'Fail to load op for {name}: {e}')
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continue
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try:
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op.save_model(format='torchscript')
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f.write('success,')
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except Exception as e:
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f.write('fail')
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print(f'Fail to save onnx for {name}: {e}')
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continue
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try:
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saved_name = name.replace('/', '-')
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op.model = torch.jit.load(f'saved/torchscript/{saved_name}.pt')
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out2 = op(data)
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assert (out1 == out2).all()
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f.write('success')
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except Exception as e:
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f.write('fail')
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print(f'Fail to check onnx for {name}: {e}')
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continue
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f.write('\n')
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print('Finished.')
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