from towhee import ops
from timm_image import TimmImage
import torch

f = open('torchscript.csv', 'a+')
f.write('model_name,run_op,save_torchscript,check_result\n')

# models = TimmImage.supported_model_names()[:1]
models = [
    'vgg11',
    'resnet18',
    'resnetv2_50',
    'seresnet33ts',
    'skresnet18',
    'resnext26ts',
    'seresnext26d_32x4d',
    'skresnext50_32x4d',
    'convit_base',
    'inception_v4',
    'efficientnet_b0',
    'tf_efficientnet_b0',
    'swin_base_patch4_window7_224',
    'vit_base_patch8_224',
    'beit_base_patch16_224',
    'convnext_base',
    'crossvit_9_240',
    'convmixer_768_32',
    'coat_lite_mini',
    'inception_v3',
    'cait_m36_384',
    'cspdarknet53',
    'deit_base_distilled_patch16_224',
    'densenet121',
    'dla34',
    'dm_nfnet_f0',
    'nf_regnet_b1',
    'nf_resnet50',
    'dpn68',
    'ese_vovnet19b_dw',
    'fbnetc_100',
    'fbnetv3_b',
    'halonet26t',
    'eca_halonext26ts',
    'sehalonet33ts',
    'hardcorenas_a',
    'hrnet_w18',
    'jx_nest_base',
    'lcnet_050',
    'levit_128',
    'mixer_b16_224',
    'mixnet_s',
    'mnasnet_100',
    'mobilenetv2_050',
    'mobilenetv3_large_100',
    'nasnetalarge',
    'pit_b_224',
    'pnasnet5large',
    'regnetx_002',
    'repvgg_a2',
    'res2net50_14w_8s',
    'res2next50',
    'resmlp_12_224',
    'resnest14d',
    'rexnet_100',
    'selecsls42b',
    'semnasnet_075',
    'tinynet_a',
    'tnt_s_patch16_224',
    'tresnet_l',
    'twins_pcpvt_base',
    'visformer_small',
    'xception',
    'xcit_large_24_p8_224',
    'ghostnet_100',
    'gmlp_s16_224',
    'lambda_resnet26rpt_256',
    'spnasnet_100',
]

decoder = ops.image_decode()
data = decoder('./towhee.jpeg')

for name in models:
    f.write(f'{name},')
    try:
        op = TimmImage(model_name=name)
        out1 = op(data)
        f.write('success,')
    except Exception as e:
        f.write('fail')
        print(f'Fail to load op for {name}: {e}')
        continue
    try:
        op.save_model(format='torchscript')
        f.write('success,')
    except Exception as e:
        f.write('fail')
        print(f'Fail to save onnx for {name}: {e}')
        continue
    try:
        saved_name = name.replace('/', '-')
        op.model = torch.jit.load(f'saved/torchscript/{saved_name}.pt')
        out2 = op(data)
        assert (out1 == out2).all()
        f.write('success')
    except Exception as e:
        f.write('fail')
        print(f'Fail to check onnx for {name}: {e}')
        continue
    f.write('\n')
print('Finished.')