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esab

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malware_detection

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Running

• "fastai.data.core.TfmdLists",
• "collections.OrderedDict",
• "fastai.imports.noop",
• "fastai.torch_core.TensorCategory",
• "inspect.Parameter",
• "torch.LongStorage",
• "numpy.dtype",
• "torch.nn.modules.pooling.AdaptiveMaxPool2d",
• "torch._utils._rebuild_parameter",
• "torch._utils._rebuild_tensor_v2",
• "__builtin__.unicode",
• "numpy.core.multiarray.scalar",
• "fastcore.dispatch.TypeDispatch",
• "fastai.data.load._FakeLoader",
• "fastai.learner.AvgMetric",
• "inspect.Signature",
• "__builtin__.long",
• "fastai.data.transforms.IntToFloatTensor",
• "__builtin__.set",
• "fastai.vision.augment.Resize",
• "timm.models.resnet.ResNet",
• "fastai.data.transforms.Categorize",
• "torch.nn.modules.linear.Linear",
• "torch.device",
• "__builtin__.object",
• "fastai.data.core.DataLoaders",
• "__builtin__.tuple",
• "__builtin__.bytes",
• "timm.models.resnet.BasicBlock",
• "inspect._empty",
• "fastai.learner.Learner",
• "random.Random",
• "torch.Tensor",
• "fastai.layers.AdaptiveConcatPool2d",
• "pathlib.PosixPath",
• "fastai.vision.core.PILImage",
• "fastai.torch_core.TensorBase",
• "pathlib.Path",
• "PIL.Image.Image",
• "torch._tensor._rebuild_from_type_v2",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "inspect._ParameterKind",
• "torch.nn.modules.loss.CrossEntropyLoss",
• "torch.nn.modules.container.Sequential",
• "fastai.data.transforms.parent_label",
• "fastai.data.core.TfmdDL",
• "fastcore.transform.Pipeline",
• "PIL.Image.Resampling",
• "fastai.losses.CrossEntropyLossFlat",
• "fastai.learner.CastToTensor",
• "__builtin__.float",
• "fastai.data.core.Datasets",
• "torch.nn.modules.dropout.Dropout",
• "fastai.metrics.accuracy",
• "fastcore.basics.fastuple",
• "numpy.ndarray",
• "torch.FloatStorage",
• "torch.nn.modules.activation.ReLU",
• "fastai.data.transforms.Normalize",
• "fastai.optimizer.Adam",
• "fastcore.dispatch._TypeDict",
• "fastai.learner.Recorder",
• "fastai.data.transforms.CategoryMap",
• "fastai.data.load._wif",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "__builtin__.print",
• "fastai.layers.Flatten",
• "__builtin__.getattr",
• "fastai.torch_core.TensorImage",
• "torch.nn.modules.conv.Conv2d",
• "_codecs.encode",
• "torch.nn.modules.pooling.MaxPool2d",
• "fastai.callback.core.TrainEvalCallback",
• "fastai.vision.learner.TimmBody",
• "fastai.vision.learner.default_split",
• "fastcore.transform.Transform",
• "fastcore.foundation.L",
• "torch.nn.modules.flatten.Flatten",
• "fastai.callback.progress.ProgressCallback",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "fastai.learner.AvgLoss",
• "fastai.data.transforms.ToTensor",
• "fastai.learner.AvgSmoothLoss",
• "torch.nn.modules.batchnorm.BatchNorm2d"

How to fix it?

• "fastai.data.core.TfmdLists",
• "collections.OrderedDict",
• "fastai.imports.noop",
• "fastai.torch_core.TensorCategory",
• "inspect.Parameter",
• "torch.LongStorage",
• "numpy.dtype",
• "torch.nn.modules.pooling.AdaptiveMaxPool2d",
• "torch._utils._rebuild_parameter",
• "torch._utils._rebuild_tensor_v2",
• "__builtin__.unicode",
• "numpy.core.multiarray.scalar",
• "fastcore.dispatch.TypeDispatch",
• "fastai.data.load._FakeLoader",
• "fastai.learner.AvgMetric",
• "inspect.Signature",
• "__builtin__.long",
• "fastai.data.transforms.IntToFloatTensor",
• "__builtin__.set",
• "fastai.vision.augment.Resize",
• "timm.models.resnet.ResNet",
• "fastai.data.transforms.Categorize",
• "torch.nn.modules.linear.Linear",
• "torch.device",
• "__builtin__.object",
• "fastai.data.core.DataLoaders",
• "__builtin__.tuple",
• "__builtin__.bytes",
• "timm.models.resnet.BasicBlock",
• "inspect._empty",
• "fastai.learner.Learner",
• "random.Random",
• "torch.Tensor",
• "fastai.layers.AdaptiveConcatPool2d",
• "pathlib.PosixPath",
• "fastai.vision.core.PILImage",
• "fastai.torch_core.TensorBase",
• "pathlib.Path",
• "PIL.Image.Image",
• "torch._tensor._rebuild_from_type_v2",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "inspect._ParameterKind",
• "torch.nn.modules.loss.CrossEntropyLoss",
• "torch.nn.modules.container.Sequential",
• "fastai.data.transforms.parent_label",
• "fastai.data.core.TfmdDL",
• "fastcore.transform.Pipeline",
• "PIL.Image.Resampling",
• "fastai.losses.CrossEntropyLossFlat",
• "fastai.learner.CastToTensor",
• "__builtin__.float",
• "fastai.data.core.Datasets",
• "torch.nn.modules.dropout.Dropout",
• "fastai.metrics.accuracy",
• "fastcore.basics.fastuple",
• "numpy.ndarray",
• "torch.FloatStorage",
• "torch.nn.modules.activation.ReLU",
• "fastai.data.transforms.Normalize",
• "fastai.optimizer.Adam",
• "fastcore.dispatch._TypeDict",
• "fastai.learner.Recorder",
• "fastai.data.transforms.CategoryMap",
• "fastai.data.load._wif",
• "timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "__builtin__.print",
• "fastai.layers.Flatten",
• "__builtin__.getattr",
• "fastai.torch_core.TensorImage",
• "torch.nn.modules.conv.Conv2d",
• "_codecs.encode",
• "torch.nn.modules.pooling.MaxPool2d",
• "fastai.callback.core.TrainEvalCallback",
• "fastai.vision.learner.TimmBody",
• "fastai.vision.learner.default_split",
• "fastcore.transform.Transform",
• "fastcore.foundation.L",
• "torch.nn.modules.flatten.Flatten",
• "fastai.callback.progress.ProgressCallback",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "fastai.learner.AvgLoss",
• "fastai.data.transforms.ToTensor",
• "fastai.learner.AvgSmoothLoss",
• "torch.nn.modules.batchnorm.BatchNorm2d"

How to fix it?