tmanabe

#!/usr/bin/env python

from argparse import ArgumentParser
from transformers import AutoModel, AutoTokenizer

import torch

"""
Usage: ./sort_vocab_by_norm.py \
    line-corporation/line-distilbert-base-japanese --trust-remote-code

tmanabe

#!/usr/bin/env python

# Efficiently Evaluating Complex Boolean Expressions [Yahoo, SIGMOD 2010]
# https://theory.stanford.edu/~sergei/papers/sigmod10-index.pdf


class Node(object):
    __slots__ = ["name", "_children", "_left_leaves", "begin", "end"]

    def __init__(n, name, *_children):

tmanabe

#!/usr/bin/env python

import numpy
import sys

numpy.set_printoptions(edgeitems=4, linewidth=120, suppress=True)
ls = sys.stdin.read().split("\n")


from tensorflow_hub import load

tmanabe

#!/usr/bin/env python


class ZScorer(object):
    __slots__ = ['means', 'stds']

    def __init__(self):
        self.means, self.stds = [], []

    def learn(self, rank_lib):

tmanabe

#!/usr/bin/env python3
# coding: utf-8

from json import dumps
from numpy import array
from numpy import logical_and
from numpy import piecewise
from scipy import optimize
from sys import argv

tmanabe

#!/usr/bin/env python3

from collections import defaultdict

LABEL_CAP = 4
LETOR_DATASET = 'C:/letor/MSLR-WEB10K/Fold1/test.txt'
OLQ_CLICK_LOG = 'C:/OpenLiveQ_yahoo_data/OpenLiveQ-clickthrough.tsv'


def avg(l):

tmanabe

#!/usr/bin/env python
# coding: utf-8

from math import log


class BASE(object):

    def __init__(self, id_to_relevance):
        # Document ID -> Relevance

tmanabe

#!/usr/bin/env python
# coding: utf-8


class TrieNode(object):
    '''A node in a trie.'''
    __slots__ = ['body', 'list_count', 'metakey']

    def __init__(self, metakey='!'):
        '''intializes a node in a trie.'''

tmanabe

#!/usr/bin/env python
# coding: utf-8

import matplotlib.pyplot as plt
import sys
from xgboost import Booster
from xgboost import plot_tree
from xgboost import XGBClassifier