Someone please point out whats the issue and how to solve it. tensor.view () reshapes the tensor (analogous to numpy.reshape) by reducing/expanding the size of each dimension (if one increases, the others must decrease). then why is it giving error that the input tensor dimension is 4? , tensor.permute () permutes the order of the axes of a tensor. its 3 which matches the length dimension. (x_similarity + y_similarity) / 2 * temperature, dim=-1 Parameters: permutation (Listint) A list defining where each Pauli should be permuted. The size of the returned tensor remains the same as that of the original. Y = self.text_encoder(y) #error on this line PyTorch torch.permute () rearranges the original tensor according to the desired ordering and returns a new multidimensional rotated tensor. encoded layers has size of 32,2 that is you have only 2 dimensions but in permute you are using 3 dimensions. Return torch.nn._sequence(batch, batch_first=True, padding_value=0)īatch = torch.stack(batch.float())īatch = pad_sequence(batch.long())ĭef _init_(self, num_classes: int = 10, bias=False): Combinations and Permutations Whats the Difference In English we use the word 'combination' loosely, without thinking if the order of things is important. The thing is, the labels are multiple for one image, so I am using a collate_fn with pad_sequence in the dataloader before feeding into the model. input.dim() = 4 is not equal to len(dims) = 3 RuntimeError: permute(sparse_coo): number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. Permuteexpr, gr returns the list of permuted forms. usr/local/lib/python3.10/dist-packages/clip/model.py in encode_text(self, text)ģ45 x = x + self.positional_embedding.type(self.dtype)ģ49 x = self.ln_final(x).type(self.dtype) Permuteexpr, perm permutes the positions of the elements of expr according to the permutation perm. But when I use the clip model's text encoder, it gives the following error: in forward(self, batch) Use the Permute panel to switch coordinates of model entities in the global coordinate system. A single variable is chosen to be permuted, and the permutation. So, I am using this clip model for some labelling task. permute performs permutation tests using Monte Carlo permutations or by enumeration of.
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