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# Usage: python create_dummy_model.py <name_of_the_file>
import sys
import torch
from torch import nn
class NeuralNetwork(nn.Module):
def __init__(self) -> None:
super().__init__()
self.flatten = nn.Flatten()
self.linear_relu_stack = nn.Sequential(
nn.Linear(28 * 28, 512),
nn.ReLU(),
nn.Linear(512, 512),
nn.ReLU(),
nn.Linear(512, 10),
)
def forward(self, x):
x = self.flatten(x)
logits = self.linear_relu_stack(x)
return logits
if __name__ == "__main__":
jit_module = torch.jit.script(NeuralNetwork())
torch.jit.save(jit_module, sys.argv[1])
orig_module = nn.Sequential(
nn.Linear(28 * 28, 512),
nn.ReLU(),
nn.Linear(512, 512),
nn.ReLU(),
nn.Linear(512, 10),
)
torch.save(orig_module, sys.argv[1] + ".orig")
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