I’m trying to train a model on MNIST dataset in an unsupervised way to extract features. As part of the program, I have to convert a numpy array to a torch tensor. Here is the code and error:
current_offset = batch_idx*train_batch_size assigned_indices = indices[current_offset : current_offset + train_batch_size] #assigned_indices = np.array(assigned_indices,dtype='int32') assigned_targets = targets[assigned_indices] if(current_offset > 0): print('current offset: %d, next offset: %d' % (current_offset,current_offset+train_batch_size)) #print('assigned indices: ',assigned_indices.shape) print('assigned targets shape: ',assigned_targets.shape) #convert into Variable assigned_targets = assigned_targets.astype(float) assigned_targets_tens = torch.from_numpy(assigned_targets)
As it can be seen in the output, I’m printing out the shape of assigned_targets array and it doesn’t have zero dimensions. But the error shows up. I’m wondering if this is a bug in the from_numpy() method.