Lyken17

import os, os.path as osp
import json
from copy import deepcopy


import numpy as np
from copy import deepcopy

import torch
import torch.nn as nn

Lyken17

from tokenize import group
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _single, _pair, _triple
import warnings

from torch.nn.grad import _grad_input_padding

@torch.no_grad()

Lyken17

import torch
import torch.nn as nn
import torch.nn.functional as F


def serialize(raw_idx):
    raw_idx = raw_idx.clone()
    # put 3 int10 into one int32
    d = raw_idx.view(-1, 3)
    d[:, 0] = d[:, 0] << 20

Lyken17

import os
import numpy as np

import torch
import torch.nn as nn
import torch.nn.functional as F

import tvm
from tvm import relay, autotvm, auto_scheduler
import tvm.relay.testing

Lyken17

import torch
import torch.nn as nn
import torch.nn.functional as F

# pytorch way
input = torch.randn(3, 5)
target = torch.randint(5, (3,), dtype=torch.int64)
loss1 = F.cross_entropy(input, target)

## equal with cross_entropy_with_logits

Lyken17

import pickle
import zlib

import sys
import numpy as np

import zmq

Lyken17

import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import autograd

net = nn.Sequential(
    nn.Linear(20, 30),
    nn.Linear(30, 40)
)

Lyken17

import torch
import torch.nn as nn
import torchvision
from torchvision import models

import numpy as np 

import tvm
from tvm import relay
from tvm.contrib import graph_executor

Lyken17

import torch
import torch.nn as nn
from torchvision import models
from torchvision.models.resnet import BasicBlock, ResNet


def remove_dropout(module):
    module_output = module
    if isinstance(module, (nn.Dropout)):
        print("removing dropout")

Lyken17

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srun --gres=gpu:4 -N 1 --mem=1T --time 1:00:00 -I --pty /bin/bash

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