blazar

Hello, if I run your experiment directly in the Ubuntu terminal without using Nvidia PyTorch Docker containers, can I reproduce the experiment? Also, if I only want to use the...

Hello, I've installed the relevant packages and am ready to start experimenting. I have a question regarding the Monarch Mixer MLP layer that I referenced in the following code: python...

Hello, I have modified the MLP layer you provided as follows: python Copy code class FeedForward(nn.Module): """Applies the MLP.""" def __init__(self, dim, ffn_expansion_factor, bias): super().__init__() hidden_size = int(dim * 4)...

Something like that? dim = 48 hidden_size = dim * 4 = 192 self.linear = linear_cls(dim, hidden_size) self.act = nn.GELU(approximate='none') self.wo = linear_cls(hidden_size, dim)

Excuse me， this is my shape of linear.weight :torch.Size([4, 48, 12])

Hello, my deraining model architecture is based on an autoencoder. Attached is my model structure. Due to down-sampling and up-sampling at each level, the input dimensions vary. I would like...

Hello, in my situation, I believe that at least the linear layer of the first level should compile successfully without errors. My linear layer has input_feature = dim = 48,...

Here is the relevant information about the provided tensor x and some parameters: x.shape: torch.Size([2, 48, 128, 128]) Shape of the weight matrix, linear.size: torch.Size([4, 32, 12]) Shape of the...

Hello, thanks to your assistance, I have been able to train the model successfully! Here are the questions I would like to ask: My single image deraining model originally used...

Hello, I will further study what you mentioned above! Additionally, I would like to inquire about the class BertGatedLinearUnitMLP in m2/bert/src/bert_layers.py. What are the distinctive features of this class compared...