Created
May 5, 2022 15:48
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import torch | |
import torch.nn as nn | |
from torchviz import make_dot | |
device = 'cuda' | |
# sending tensor to device at creation time | |
a = torch.randn(1, requires_grad=True, dtype=torch.float, device=device) | |
plot1 = make_dot(a) | |
# sending tensor to device immediately after creating it | |
a = torch.randn(1, requires_grad=True, dtype=torch.float).to(device) | |
plot2 = make_dot(a) | |
class ManualLinearRegression(nn.Module): | |
def __init__(self): | |
super().__init__() | |
# To make "a" and "b" real parameters of the model, we need to wrap them with nn.Parameter | |
self.a = nn.Parameter(torch.randn(1, requires_grad=True, dtype=torch.float)) | |
self.b = nn.Parameter(torch.randn(1, requires_grad=True, dtype=torch.float)) | |
def forward(self, x): | |
# Computes the outputs / predictions | |
return self.a + self.b * x | |
# sending model to device | |
model = ManualLinearRegression().to(device) | |
plot3 = make_dot(model.a) | |
# plots n.1 and n.3 will be exactly the same | |
# plot n.2, on the other hand, is different - the `to` operation created an unwanted computation graph |
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