18 lines
516 B
Python
18 lines
516 B
Python
from tinygrad.tensor import Tensor
|
|
from tinygrad.nn import Conv2d, BatchNorm2d
|
|
from tinygrad.nn.state import get_parameters
|
|
|
|
if __name__ == "__main__":
|
|
with Tensor.train():
|
|
|
|
BS, C1, H, W = 4, 16, 224, 224
|
|
C2, K, S, P = 64, 7, 2, 1
|
|
|
|
x = Tensor.uniform(BS, C1, H, W)
|
|
conv = Conv2d(C1, C2, kernel_size=K, stride=S, padding=P)
|
|
bn = BatchNorm2d(C2, track_running_stats=False)
|
|
for t in get_parameters([x, conv, bn]): t.realize()
|
|
|
|
print("running network")
|
|
x.sequential([conv, bn]).numpy()
|