Axel232

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testing

like 0

• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_36.BatchNorm2d",
• "__torch__.torch.nn.modules.container.___torch_mangle_14.Sequential",
• "__torch__.torch.nn.modules.container.Sequential",
• "__torch__.torch.nn.modules.container.___torch_mangle_10.Sequential",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_6.BatchNorm2d",
• "torch.LongStorage",
• "__torch__.torch.nn.modules.container.___torch_mangle_42.Sequential",
• "__torch__.torchvision.ops.misc.___torch_mangle_33.Conv2dNormActivation",
• "__torch__.torchvision.ops.misc.___torch_mangle_7.Conv2dNormActivation",
• "__torch__.torchvision.models.mobilenetv2.InvertedResidual",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_38.InvertedResidual",
• "__torch__.torch.nn.modules.container.___torch_mangle_27.Sequential",
• "__torch__.torch.ao.nn.quantized.modules.Quantize",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_24.InvertedResidual",
• "__torch__.torch.ao.nn.quantized.modules.linear.Linear",
• "__torch__.torch.ao.nn.quantized.modules.activation.ReLU6",
• "__torch__.torch.nn.modules.container.___torch_mangle_23.Sequential",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_25.BatchNorm2d",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_19.BatchNorm2d",
• "__torch__.torch.nn.modules.container.___torch_mangle_4.Sequential",
• "__torch__.torchvision.ops.misc.Conv2dNormActivation",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_39.BatchNorm2d",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_16.BatchNorm2d",
• "__torch__.torchvision.ops.misc.___torch_mangle_40.Conv2dNormActivation",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_9.InvertedResidual",
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• "__torch__.torchvision.ops.misc.___torch_mangle_13.Conv2dNormActivation",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_22.InvertedResidual",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_15.InvertedResidual",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_28.InvertedResidual",
• "torch.per_channel_affine",
• "torch._utils._rebuild_qtensor",
• "__torch__.torch.nn.modules.container.___torch_mangle_17.Sequential",
• "__torch__.torchvision.ops.misc.___torch_mangle_26.Conv2dNormActivation",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_1.BatchNorm2d",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_5.InvertedResidual",
• "__torch__.torch.nn.modules.container.___torch_mangle_8.Sequential",
• "__torch__.torch.ao.nn.quantized.modules.conv.Conv2d",
• "__torch__.torch.nn.modules.container.___torch_mangle_21.Sequential",
• "__torch__.torch.nn.modules.container.___torch_mangle_34.Sequential",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_11.InvertedResidual",
• "torch._utils._rebuild_tensor_v2",
• "__torch__.___torch_mangle_44.MobileNetV2Classifier",
• "__torch__.torch.ao.nn.quantized.modules.linear.LinearPackedParams",
• "__torch__.torch.ao.nn.quantized.modules.DeQuantize",
• "collections.OrderedDict",
• "__torch__.torchvision.models.mobilenetv2.MobileNetV2",
• "torch.FloatStorage",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.BatchNorm2d",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_18.InvertedResidual",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_0.BatchNorm2d",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_12.BatchNorm2d",
• "__torch__.torchvision.ops.misc.___torch_mangle_20.Conv2dNormActivation",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_29.BatchNorm2d",
• "__torch__.torch.classes.quantized.LinearPackedParamsBase",
• "__torch__.torch.nn.modules.container.___torch_mangle_37.Sequential",
• "torch.DoubleStorage",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_31.InvertedResidual",
• "__torch__.torch.ao.nn.quantized.modules.dropout.Dropout",
• "__torch__.torch.nn.modules.container.___torch_mangle_41.Sequential",
• "__torch__.torchvision.models.mobilenetv2.___torch_mangle_35.InvertedResidual",
• "torch.QInt8Storage",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_32.BatchNorm2d",
• "__torch__.torch.ao.nn.quantized.modules.batchnorm.___torch_mangle_3.BatchNorm2d",
• "__torch__.torchvision.ops.misc.___torch_mangle_2.Conv2dNormActivation"

How to fix it?