molinamarc

/

syntheva

like 0

• "numpy.ndarray",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.activation.ReLU6",
• "numpy.dtype",
• "collections.OrderedDict",
• "pg_modules.blocks.DownBlock",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.normalization.LayerNorm",
• "dill._dill._create_cell",
• "torch.nn.modules.container.Sequential",
• "timm.models.layers.conv2d_same.Conv2dSame",
• "pg_modules.discriminator.MultiScaleD",
• "torch.nn.utils.spectral_norm.SpectralNormStateDictHook",
• "torch.nn.utils.spectral_norm.SpectralNormLoadStateDictPreHook",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch_utils.persistence._reconstruct_persistent_obj",
• "torch.nn.modules.linear.Identity",
• "builtins.setattr",
• "pg_modules.projector.F_RandomProj",
• "dill._dill._create_function",
• "torch.nn.quantized.modules.functional_modules.FloatFunctional",
• "timm.models.efficientnet_blocks.DepthwiseSeparableConv",
• "torch.nn.modules.conv.ConvTranspose2d",
• "torch.nn.modules.container.ModuleDict",
• "torch.nn.modules.module.Module",
• "builtins.getattr",
• "timm.models.vision_transformer.Attention",
• "numpy.core.multiarray._reconstruct",
• "dill._dill._create_code",
• "torch.nn.modules.activation.LeakyReLU",
• "feature_networks.vit.Transpose",
• "torch.nn.modules.conv.Conv2d",
• "timm.models.vision_transformer.VisionTransformer",
• "torch.nn.utils.spectral_norm.SpectralNorm",
• "torch._utils._rebuild_tensor_v2",
• "torch._utils._rebuild_parameter",
• "pg_modules.blocks.FeatureFusionBlock",
• "pg_modules.discriminator.ProjectedDiscriminator",
• "timm.models.efficientnet_blocks.InvertedResidual",
• "torch.Size",
• "feature_networks.vit.__dict__",
• "dill._shims._dill",
• "torch.storage._load_from_bytes",
• "timm.models.layers.patch_embed.PatchEmbed",
• "timm.models.vision_transformer.Block",
• "torch.nn.modules.activation.GELU",
• "feature_networks.vit.Slice",
• "numpy.core.multiarray.scalar",
• "torch.nn.modules.flatten.Unflatten",
• "pg_modules.discriminator.SingleDiscCond",
• "timm.models.layers.mlp.Mlp",
• "torch.nn.modules.sparse.Embedding"

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