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from torch._C._nvfuser import Fusion, FusionCache, FusionDefinition, DataType | |
import torch | |
import torch.nn.functional as F | |
import functorch | |
from functorch.compile import memory_efficient_fusion | |
from copy import deepcopy | |
from typing import List | |
import time | |
import functools | |
import random |
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import torch | |
import torch.nn as nn | |
from torch.autograd import Variable | |
torch.backends.cudnn.enabled=True | |
seq_size = 2 | |
hidden_size = 3 | |
inp_size = 4 | |
batch_size = 5 |
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import torch | |
import torch.nn as nn | |
from torch.autograd import Variable | |
import itertools | |
seq_size = 16 | |
batch_size = 32 | |
inp_size = 64 | |
hidden_size = 128 |
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from __future__ import print_function | |
import argparse | |
import numpy as np | |
import torch | |
import torch.nn as nn | |
import torch.nn.functional as F | |
import torch.optim as optim | |
from torch.autograd import Variable | |
import time |
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import time | |
import torch | |
from torch.autograd import Variable | |
import torchvision.models as models | |
import torch.backends.cudnn as cudnn | |
cudnn.benchmark = True | |
net = models.vgg19().cuda() |