thank you for your reply, I have another problem.
test code:
a = torch.randn(1, 49920, 512)
c = torch.randn(1, 512, 49920)
#b = torch.randn(153000, 288, 3, 3)
#a = a.half()
#b = b.half()
if True:
device = torch.device(“cuda”)
else:
device = torch.device(“cpu”)
a = a.to(device)
#b = b.to(device)
c = c.to(device)
torch.cuda.synchronize()
start = time.process_time()
#torch.matmul(a, b)
#F.conv1d(a, c)
torch.matmul(a,c)
as I checked the input feature map size should be 49920x512x4 /1024/1024 = 97.5M
but when I run it in GPU (GTX1080ti), the top memory will cost more than 10G.
do you why for that, and how to avoid it.