<commit_before>import argparse
import random

import numpy as np

import chainer
import chainer.links as L
import chainer.functions as F
from chainer import iterators
from chainer import training
from chainer.training import extensions

from chainercv.datasets import ImageFolderDataset
from chainercv.links import VGG16Layers

from chainercv.utils import apply_prediction_to_iterator


def main():
    parser = argparse.ArgumentParser(
        description='Learning convnet from ILSVRC2012 dataset')
    parser.add_argument('val', help='Path to root of the validation dataset')
    parser.add_argument('--gpu', type=int, default=-1)
    parser.add_argument('--batchsize', type=int, default=32)
    args = parser.parse_args()

    dataset = ImageFolderDataset(args.val)<commit_msg>add pretrained_model ooption to eval_imagenet<commit_after>import argparse
import random

import numpy as np

import chainer
import chainer.links as L
import chainer.functions as F
from chainer import iterators
from chainer import training
from chainer.training import extensions

from chainercv.datasets import ImageFolderDataset
from chainercv.links import VGG16Layers

from chainercv.utils import apply_prediction_to_iterator


def main():
    parser = argparse.ArgumentParser(
        description='Learning convnet from ILSVRC2012 dataset')
    parser.add_argument('val', help='Path to root of the validation dataset')
    parser.add_argument('--pretrained_model')
    parser.add_argument('--gpu', type=int, default=-1)
    parser.add_argument('--batchsize', type=int, default=32)
    args = parser.parse_args()

    dataset = ImageFolderDataset(args.val)
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{'dir': 'git-commits-cleaned', 'id': '3940422', 'n_tokens_mistral': 479, 'n_tokens_neox': 459, 'n_words': 142}