Saumya-Mundra

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harmonization

like 0

• "model.backbone.baseline",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.pooling.MaxPool2d",
• "model.base.ih_model.DeepImageHarmonization",
• "model.base.basic_blocks.lineParams",
• "model.hrnetv2.ocr.SpatialGather_Module",
• "torch.nn.modules.container.Sequential",
• "torch._utils._rebuild_tensor_v2",
• "model.base.basic_blocks.ConvBlock",
• "torch._utils._rebuild_parameter",
• "model.base.conv_autoencoder.ConvEncoder",
• "torch.nn.modules.container.ParameterList",
• "model.base.ops.FeaturesConnector",
• "model.base.ops.ScaleLayer",
• "model.hrnetv2.ocr.ObjectAttentionBlock2D",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "model.build_model.build_model",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "model.base.ops.Predict_embed",
• "torch.FloatStorage",
• "torch.LongStorage",
• "model.base.conv_autoencoder.SEDeconvBlock",
• "model.hrnetv2.resnetv1b.BasicBlockV1b",
• "torch.nn.modules.conv.Conv2d",
• "model.hrnetv2.hrnet_ocr.HighResolutionNet",
• "model.base.basic_blocks.convParams",
• "model.hrnetv2.hrnet_ocr.HighResolutionModule",
• "torch.nn.modules.activation.ELU",
• "argparse.Namespace",
• "model.base.ops.CIPS_embed",
• "torch.nn.modules.activation.ReLU",
• "model.lut_transformation_net.build_lut_transform",
• "model.hrnetv2.resnetv1b.BottleneckV1b",
• "torch._utils._rebuild_parameter_with_state",
• "torch.nn.modules.upsampling.Upsample",
• "collections.OrderedDict",
• "model.backbone.HRNetV2",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.container.ModuleDict",
• "__builtin__.set",
• "model.base.conv_autoencoder.INRDecoder",
• "torch.nn.modules.dropout.Dropout2d",
• "model.hrnetv2.ocr.SpatialOCR_Module",
• "model.base.ops.ConstantInput",
• "torch.nn.modules.conv.ConvTranspose2d"

How to fix it?

• "model.base.conv_autoencoder.ConvEncoder",
• "torch.nn.modules.linear.Identity",
• "model.base.conv_autoencoder.INRDecoder",
• "model.lut_transformation_net.build_lut_transform",
• "collections.OrderedDict",
• "torch._utils._rebuild_tensor_v2",
• "model.base.basic_blocks.ConvBlock",
• "model.hrnetv2.resnetv1b.BottleneckV1b",
• "model.build_model.build_model",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "model.base.conv_autoencoder.SEDeconvBlock",
• "model.base.ops.ScaleLayer",
• "model.base.ops.CIPS_embed",
• "torch.nn.modules.linear.Linear",
• "model.backbone.baseline",
• "torch.nn.modules.upsampling.Upsample",
• "torch._utils._rebuild_parameter_with_state",
• "model.backbone.HRNetV2",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.Sequential",
• "model.hrnetv2.resnetv1b.BasicBlockV1b",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.activation.ELU",
• "argparse.Namespace",
• "model.base.ih_model.DeepImageHarmonization",
• "__builtin__.set",
• "model.base.basic_blocks.convParams",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.conv.Conv2d",
• "model.hrnetv2.hrnet_ocr.HighResolutionNet",
• "torch.FloatStorage",
• "model.hrnetv2.ocr.SpatialGather_Module",
• "torch.LongStorage",
• "model.hrnetv2.ocr.ObjectAttentionBlock2D",
• "torch.nn.modules.container.ParameterList",
• "torch.nn.modules.conv.ConvTranspose2d",
• "model.base.ops.ConstantInput",
• "model.hrnetv2.hrnet_ocr.HighResolutionModule",
• "model.base.ops.FeaturesConnector",
• "model.base.basic_blocks.lineParams",
• "model.hrnetv2.ocr.SpatialOCR_Module",
• "torch.nn.modules.container.ModuleDict",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "model.base.ops.Predict_embed",
• "torch.nn.modules.dropout.Dropout2d"

How to fix it?

• "model.base.conv_autoencoder.ConvEncoder",
• "torch.nn.modules.linear.Identity",
• "model.base.conv_autoencoder.INRDecoder",
• "model.lut_transformation_net.build_lut_transform",
• "collections.OrderedDict",
• "torch._utils._rebuild_tensor_v2",
• "model.base.basic_blocks.ConvBlock",
• "model.hrnetv2.resnetv1b.BottleneckV1b",
• "model.build_model.build_model",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "model.base.conv_autoencoder.SEDeconvBlock",
• "model.base.ops.ScaleLayer",
• "model.base.ops.CIPS_embed",
• "torch.nn.modules.linear.Linear",
• "model.backbone.baseline",
• "torch.nn.modules.upsampling.Upsample",
• "torch._utils._rebuild_parameter_with_state",
• "model.backbone.HRNetV2",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.Sequential",
• "model.hrnetv2.resnetv1b.BasicBlockV1b",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.activation.ELU",
• "argparse.Namespace",
• "model.base.ih_model.DeepImageHarmonization",
• "__builtin__.set",
• "model.base.basic_blocks.convParams",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.conv.Conv2d",
• "model.hrnetv2.hrnet_ocr.HighResolutionNet",
• "torch.FloatStorage",
• "model.hrnetv2.ocr.SpatialGather_Module",
• "torch.LongStorage",
• "model.hrnetv2.ocr.ObjectAttentionBlock2D",
• "torch.nn.modules.container.ParameterList",
• "torch.nn.modules.conv.ConvTranspose2d",
• "model.base.ops.ConstantInput",
• "model.hrnetv2.hrnet_ocr.HighResolutionModule",
• "model.base.ops.FeaturesConnector",
• "model.base.basic_blocks.lineParams",
• "model.hrnetv2.ocr.SpatialOCR_Module",
• "torch.nn.modules.container.ModuleDict",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "model.base.ops.Predict_embed",
• "torch.nn.modules.dropout.Dropout2d"

How to fix it?

• "models.lut_transformation_net.build_lut_transform",
• "models.hrnetv2.hrnet_ocr.HighResolutionNet",
• "models.backbone.baseline",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "torch.nn.modules.container.ParameterList",
• "models.hrnetv2.resnetv1b.BottleneckV1b",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.linear.Linear",
• "collections.OrderedDict",
• "models.base.ih_model.DeepImageHarmonization",
• "models.base.conv_autoencoder.INRDecoder",
• "models.build_model.build_model",
• "models.hrnetv2.ocr.ObjectAttentionBlock2D",
• "torch._utils._rebuild_tensor_v2",
• "models.hrnetv2.hrnet_ocr.HighResolutionModule",
• "argparse.Namespace",
• "models.base.ops.ConstantInput",
• "torch.nn.modules.dropout.Dropout2d",
• "torch.nn.modules.linear.Identity",
• "models.base.ops.ScaleLayer",
• "torch.nn.modules.activation.ReLU",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.nn.modules.activation.ELU",
• "models.base.basic_blocks.ConvBlock",
• "models.base.conv_autoencoder.ConvEncoder",
• "models.base.ops.FeaturesConnector",
• "models.base.ops.CIPS_embed",
• "torch.nn.modules.container.ModuleDict",
• "models.hrnetv2.ocr.SpatialOCR_Module",
• "torch.nn.modules.conv.Conv2d",
• "models.hrnetv2.resnetv1b.BasicBlockV1b",
• "torch.nn.modules.upsampling.Upsample",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.Sequential",
• "__builtin__.set",
• "models.base.conv_autoencoder.SEDeconvBlock",
• "models.base.ops.Predict_embed",
• "torch.nn.modules.conv.ConvTranspose2d",
• "models.backbone.HRNetV2",
• "torch._utils._rebuild_parameter_with_state",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "models.hrnetv2.ocr.SpatialGather_Module",
• "models.base.basic_blocks.convParams",
• "models.base.basic_blocks.lineParams",
• "torch.FloatStorage",
• "torch.LongStorage"

How to fix it?