Comments (7)
Your error is in the line nn.Linear(1024, batch_size)
.
I believe this should be nn.Linear(1024, 8*8)
as the generator is trying to output 8x8 images.
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Also, the line x = x.view(-1, batch_size)
is an error. It should be x = x.view(batch_size, -1)
.
from pytorch-sentiment-analysis.
Your error is in the line
nn.Linear(1024, batch_size)
.I believe this should be
nn.Linear(1024, 8*8)
as the generator is trying to output 8x8 images.
Hello. Here 8*8 = 64 is the batch_size
from pytorch-sentiment-analysis.
Your error is in the line
nn.Linear(1024, batch_size)
.
I believe this should benn.Linear(1024, 8*8)
as the generator is trying to output 8x8 images.Hello. Here 8*8 = 64 is the batch_size
Right, but nn.Linear(1024, batch_size)
means it takes in a [batch size, 1024]
tensor and outputs a [batch size, batch size]
tensor, when it should be a [batch size, channels * height * width]
tensor and then the last dimension should be reshaped.
from pytorch-sentiment-analysis.
Okay. I have done that and now the error is : mat1 and mat2 shapes cannot be multiplied (64x304800 and 64x1024)
from pytorch-sentiment-analysis.
Which line is giving you that error? Tensor shape mismatching is a common bug in deep learning models, and the best way to solve it by making sure the shapes output by each layer is what you expect by printing out the tensor shapes out by each layer and seeing if it matches with what you expect it to be.
from pytorch-sentiment-analysis.
Your error is in the line
nn.Linear(1024, batch_size)
.I believe this should be
nn.Linear(1024, 8*8)
as the generator is trying to output 8x8 images.
I believe the error is here. The output of nn.Linear of Generator shouldn't be batch size. As you said, it should be channels × height× width. For my images, it is 1 × 160× 160, which is quite large to be an output.
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