type or paste code hereclass CSVDataset(Dataset):
def __init__(self, path):
df = read_csv(path,usecols=[5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,30], header=None)
self.X = df.values[:, :-1]
self.y = df.values[:, -1]
self.X = self.X.astype('float32')
self.y = self.y.astype('float32')
self.y = self.y.reshape((len(self.y), 1))
def __len__(self):
return len(self.X)
def __getitem__(self, idx):
return [self.X[idx], self.y[idx]]
def get_splits(self, n_test=0.20): # spliting of dataset
test_size = int(round(n_test * len(self.X)))
train_size = int(len(self.X) - test_size)
return random_split(self, [train_size, test_size])
def prepare_data(path):
dataset = CSVDataset(path)
train, test = dataset.get_splits()
train_dl = DataLoader(train, batch_size=50, shuffle=False)
test_dl = DataLoader(test, batch_size=500, shuffle=False)
return train_dl, test_dl
Here I have assigned by datatype as “float32”. But when I try to change the dtype to double precision it shows some error.
Traceback (most recent call last):
File “./amplitude_signANN.py”, line 267, in
train_model(train_dl, model)
File “./amplitude_signANN.py”, line 147, in train_model
yhat = model(inputs)
File “/home/sumanta/.local/lib/python2.7/site-packages/torch/nn/modules/module.py”, line 532, in call
result = self.forward(*input, **kwargs)
File “./amplitude_signANN.py”, line 87, in forward
X = self.hidden1(X)
File “/home/sumanta/.local/lib/python2.7/site-packages/torch/nn/modules/module.py”, line 532, in call
result = self.forward(*input, **kwargs)
File “/home/sumanta/.local/lib/python2.7/site-packages/torch/nn/modules/linear.py”, line 87, in forward
return F.linear(input, self.weight, self.bias)
File “/home/sumanta/.local/lib/python2.7/site-packages/torch/nn/functional.py”, line 1370, in linear
ret = torch.addmm(bias, input, weight.t())
RuntimeError: Expected object of scalar type Float but got scalar type Double for argument #2 ‘mat1’ in call to _th_addmm
Can pytorch train the data with double precision ? If yes then how can that be fixed?