The following script:
import torch
import torch.nn.functional as F
from torch.autograd import Variable

output = Variable(torch.Tensor(
[-0.0226, -0.1922, 0.1461, -0.0481, -0.0526, -0.0449, 0.1586, -0.0980, 0.2177, 
0.0402, -0.1200, 0.0010, 0.0022, 0.0430, 0.1930, 0.2304, 0.0043, 0.0659, 0.2427, 
0.1580, -0.0449, -0.0477, 0.1961, 0.2336, -0.0308, 0.0648, 0.0669, 0.0072, 0.0353,
-0.2793, 0.0105, -0.1510, -0.0942, -0.1761, 0.0477, -0.0564, -0.1628, 0.0467, 
-0.0819, -0.2643, 0.1066, -0.0952, 0.0918, -0.0934, 0.1405, -0.1959, -0.0477,
-0.1138, -0.1032, -0.0622, -0.0658, 0.2957, -0.1170, -0.1541, 0.1663, 0.2635,
-0.1477, 0.2634, 0.0940, -0.0477, -0.1920, 0.0104, 0.3450, -0.0514, -0.1592, 0.2188,
-0.3998, -0.1696, -0.1194, -0.3216, -0.0702, 0.0074, -0.0223, 0.0597, 0.0329, 
-0.1500, 0.2207, 0.1900, -0.0688, 0.3510, 0.1114, -0.0829, 0.0919, -0.1787, 0.0266, 
-0.2059, 0.0821, -0.1061, 0.1190, 0.0090]), requires_grad=True)

target = Variable(torch.Tensor(
[0.3100, 0.0638, -0.1865, -0.4252, -0.6371, -0.8090, -0.9300, -0.9922, -0.9919, 
-0.9289, -0.8072, -0.6343, -0.4212, -0.1814, 0.0700, 0.3170, 0.5440, 0.7365, 0.8823,
0.9720, 0.9999, 0.9641, 0.8669, 0.7143, 0.5162, 0.2850, 0.0355, -0.2163, -0.4543, 
-0.6634, -0.8300, -0.9435, -0.9965, -0.9855, -0.9113, -0.7784, -0.5955, -0.3742,
-0.1287, 0.1252, 0.3711, 0.5931, 0.7769, 0.9105, 0.9854, 0.9965, 0.9431, 0.8286, 
0.6604, 0.4493, 0.2089, -0.0451, -0.2962, -0.5282, -0.7259, -0.8763, -0.9697, 
-1.0000, -0.9649, -0.8669, -0.7122, -0.5110, -0.2762, -0.0232, 0.2313, 0.4707, 
0.6794, 0.8435, 0.9523, 0.9986, 0.9792, 0.8954, 0.7526, 0.5602, 0.3308, 0.0794,
-0.1772, -0.4222, -0.6394, -0.8143, -0.9355, -0.9947, -0.9880, -0.9158, -0.7828,
-0.5979, -0.3731, -0.1234, 0.1345, 0.3836]))

train_loss1 = F.mse_loss(output, target, True)
train_loss2 = ((output - target)**2).mean()

gives
In [8]: train_loss1
Out[8]:
Variable containing:
 0.5171
[torch.FloatTensor of size (1,)]

In [9]: train_loss2
Out[9]:
Variable containing:
 0.5171
[torch.FloatTensor of size (1,)]

I’d also expect it to give the same on the gpu. Does your problem occur when your inputs are on the cpu?