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/* 
author: jbenet
os x, compile with: gcc -o testo test.c 
linux, compile with: gcc -o testo test.c -lrt
*/

#include <time.h>
#include <sys/time.h>
#include <stdio.h>

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n02672831 accordion
n02691156 airplane
n02219486 ant
n02419796 antelope
n07739125 apple
n02454379 armadillo
n07718747 artichoke
n02764044 axe
n02766320 baby bed
n02769748 backpack

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# please cite:
# @article{SqueezeNet,
#     Author = {Forrest N. Iandola and Matthew W. Moskewicz and Khalid Ashraf and Song Han and William J. Dally and Kurt Keutzer},
#     Title = {SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $<$1MB model size},
#     Journal = {arXiv:1602.07360},
#     Year = {2016}
# }
#
# this file is by Hyunjun Kim (rmekdma); taken from:
# https://github.com/DeepScale/SqueezeNet/pull/20

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## @package get_python_cmake_flags
# Module scripts.get_python_cmake_flags
##############################################################################
# Use this script to find your preferred python installation.
##############################################################################
#
# You can use the following to build with your preferred version of python
# if your installation is not being properly detected by CMake.
#
#   mkdir -p build && cd build

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deepspeed --num_nodes 1 --num_gpus 16 pretrain_gpt2.py --model-parallel-size 1 --num-layers 4 --hidden-size 512 --num-attention-heads 8 --seq-length 512 --max-position-embeddings 4096 --batch-size 1 --train-iters 10 --lr-decay-iters 320000 --data-path data/webtext/webtext_text_document --vocab-file data/gpt2-vocab.json --merge-file data/gpt2-merges.txt --data-impl mmap --split 949,50,1 --distributed-backend nccl --lr 1.5e-4 --lr-decay-style cosine --min-lr 1.0e-5 --weight-decay 1e-2 --clip-grad 1.0 --warmup 0.01 --log-interval 100 --save-interval 10000 --eval-interval 1000 --eval-iters 10 --fp16 --hysteresis 2 --num-workers 0 --deepspeed --deepspeed_config /home/chengli1/projects/Megatron-LM/examples/ds_zero_stage_2_config.json --zero-stage 0 --zero-reduce-bucket-size 50000000 --zero-allgather-bucket-size 5000000000 --zero-contigious-gradients --zero-reduce-scatter --checkpoint-activations --checkpoint-num-layers 1 --partition-activations --synchronize-each-layer --contigious-checkpointing
[2020-10-30 23:43:3

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perl: warning: Setting locale failed.
perl: warning: Please check that your locale settings:
	LANGUAGE = (unset),
	LC_ALL = (unset),
	LC_CTYPE = "UTF-8",
	LANG = "en_US.UTF-8"
    are supported and installed on your system.
perl: warning: Falling back to the standard locale ("C").

~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ 

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import argparse
import torch
import torch.distributed as dist

parser = argparse.ArgumentParser()
parser.add_argument("--local_rank", type=int)
args = parser.parse_args()
device = args.local_rank

dist.init_process_group('nccl')

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Locate the section for your github remote in the .git/config file. It looks like this:

[remote "origin"]
	fetch = +refs/heads/*:refs/remotes/origin/*
	url = git@github.com:joyent/node.git

Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this:

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import torch
import torch.nn as nn
from torch.profiler import profile, record_function, ProfilerActivity
import torchprof

class NeuralNetwork(nn.Module):
    def __init__(self):
        super(NeuralNetwork, self).__init__()
        self.flatten = nn.Flatten()
        self.linear_relu_stack = nn.Sequential(

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from transformers import CONFIG_MAPPING
from huggingface_hub import HfApi

api = HfApi()

def _get_all_hf_model_types():
    return list(CONFIG_MAPPING.keys())

def _get_total_downloads_by_model_type(model_type):
    models = api.list_models(filter=model_type)