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import asyncio | |
import aiofiles | |
tar_filenames = [f"/home/chenyaofo/datasets/imagenet-wds/train/{i:06d}.tar" for i in range(256)] | |
# tar_filenames = [f"/gpfs01/home/chenyaofo/imagenet-wds/train/{i:06d}.tar" for i in range(256)] | |
count = 0 | |
def async_reading(): | |
print("asyncio reading based on naive asyncio") |
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FROM nvidia/cuda:11.8.0-devel-ubuntu22.04 | |
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8 \ | |
PATH=/opt/conda/bin:$PATH \ | |
PYTHON_VERSION=3.10 | |
RUN APT_INSTALL="apt-get install -y --no-install-recommends --no-install-suggests" && \ | |
GIT_CLONE="git clone --depth 10" && \ | |
rm -rf /etc/apt/sources.list.d/cuda.list \ |
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FROM nvidia/cuda:11.8.0-devel-ubuntu22.04 | |
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8 \ | |
PATH=/opt/conda/bin:$PATH \ | |
TZ=Asia/Shanghai \ | |
PYTHON_VERSION=3.9 | |
RUN APT_INSTALL="apt-get install -y --no-install-recommends --no-install-suggests" && \ | |
GIT_CLONE="git clone --depth 10" && \ | |
rm -rf /etc/apt/sources.list.d/cuda.list \ |
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import torch | |
import torchvision.transforms as transforms | |
from PIL import Image | |
from io import BytesIO | |
from torchdata.datapipes.iter import FileLister, FileOpener, TFRecordLoader, Mapper, Shuffler, Batcher, Collator, ShardingFilter | |
from torchdata.dataloader2 import adapter, DataLoader2, PrototypeMultiProcessingReadingService | |
from codebase.torchutils.serialization import jsonunpack | |
from torch.utils.data import DataLoader | |
def get_train_transforms(): |
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import torch | |
import torch.nn as nn | |
from torchvision.models import resnet50 | |
import types | |
import copy | |
def tbr_bn_forward_impl(self: nn.BatchNorm2d, x: torch.Tensor): | |
batch_var, batch_mean = torch.var_mean(x, dim=(0, 2, 3), keepdim=True) | |
batch_std = torch.sqrt(batch_var+self.eps) |
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import torch | |
import torch.nn as nn | |
from torchvision.models import resnet50 | |
import types | |
import copy | |
def tbr_bn_forward_impl(self: nn.BatchNorm2d, x: torch.Tensor): | |
# print("x.shape", x.shape) | |
batch_mean = x.mean(dim=(0, 2, 3), keepdim=True) |
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FROM nvcr.io/nvidia/pytorch:22.11-py3 | |
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8 \ | |
TZ=Asia/Shanghai | |
RUN APT_INSTALL="apt-get install -y --no-install-recommends --no-install-suggests" && \ | |
GIT_CLONE="git clone --depth 10" && \ | |
mirror_url=mirrors.cloud.tencent.com && \ | |
sed -i "s/security.ubuntu.com/$mirror_url/" /etc/apt/sources.list && \ | |
sed -i "s/archive.ubuntu.com/$mirror_url/" /etc/apt/sources.list && \ |
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import torch | |
from typing import List, Tuple | |
import matplotlib.pyplot as plt | |
from matplotlib import ticker | |
from matplotlib import font_manager | |
# more details about matplotlib usage at | |
# https://wizardforcel.gitbooks.io/matplotlib-user-guide/content/ | |
def color(*items): |
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import time | |
import os | |
import warnings | |
import pathlib | |
try: | |
import nvidia.dali.types as types | |
import nvidia.dali.fn as fn | |
from nvidia.dali.plugin.pytorch import DALIGenericIterator, LastBatchPolicy | |
from nvidia.dali.pipeline import Pipeline |
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import argparse | |
import os | |
import random | |
import shutil | |
import time | |
import warnings | |
import torch | |
import torch.nn as nn | |
import torch.nn.parallel |