Pythonメソッド（任意のクラスのメンバーではないメソッド）の自己引数と混同しました

Question

私は自分のニーズを満たすためにそれを変更できるようにいくつかのgithubコードを読み込もうとしています。私は理解に苦しんでいますthis file。 classキーワードは含まれていませんが、メソッド定義内にはselfキーワードが使用されています。 私の質問は、selfのメソッド宣言内のものは何ですか？ もう1つの関連する質問は、このファイルとは何ですか（つまり、機能していますか）。

コメント、提案、お役立ち情報が非常に役に立ちます。どうも！以下は

は、私は、リンクで参照コードです：

""" 
tfnet secondary (helper) methods 
""" 
from ..utils.loader import create_loader 
from time import time as timer 
import tensorflow as tf 
import numpy as np 
import sys 
import cv2 
import os 
import csv 

old_graph_msg = 'Resolving old graph def {} (no guarantee)' 

def build_train_op(self): 
    self.framework.loss(self.out) 
    self.say('Building {} train op'.format(self.meta['model'])) 
    optimizer = self._TRAINER[self.FLAGS.trainer](self.FLAGS.lr) 
    gradients = optimizer.compute_gradients(self.framework.loss) 
    self.train_op = optimizer.apply_gradients(gradients) 

def load_from_ckpt(self): 
    if self.FLAGS.load < 0: # load lastest ckpt 
     with open(self.FLAGS.backup + 'checkpoint', 'r') as f: 
      last = f.readlines()[-1].strip() 
      load_point = last.split(' ')[1] 
      load_point = load_point.split('"')[1] 
      load_point = load_point.split('-')[-1] 
      self.FLAGS.load = int(load_point) 

    load_point = os.path.join(self.FLAGS.backup, self.meta['name']) 
    load_point = '{}-{}'.format(load_point, self.FLAGS.load) 
    self.say('Loading from {}'.format(load_point)) 
    try: self.saver.restore(self.sess, load_point) 
    except: load_old_graph(self, load_point) 

def say(self, *msgs): 
    if not self.FLAGS.verbalise: 
     return 
    msgs = list(msgs) 
    for msg in msgs: 
     if msg is None: continue 
     print(msg) 

def load_old_graph(self, ckpt): 
    ckpt_loader = create_loader(ckpt) 
    self.say(old_graph_msg.format(ckpt)) 

    for var in tf.global_variables(): 
     name = var.name.split(':')[0] 
     args = [name, var.get_shape()] 
     val = ckpt_loader(args) 
     assert val is not None, \ 
     'Cannot find and load {}'.format(var.name) 
     shp = val.shape 
     plh = tf.placeholder(tf.float32, shp) 
     op = tf.assign(var, plh) 
     self.sess.run(op, {plh: val}) 

def _get_fps(self, frame): 
    elapsed = int() 
    start = timer() 
    preprocessed = self.framework.preprocess(frame) 
    feed_dict = {self.inp: [preprocessed]} 
    net_out = self.sess.run(self.out, feed_dict)[0] 
    processed = self.framework.postprocess(net_out, frame, False) 
    return timer() - start 

def camera(self): 
    file = self.FLAGS.demo 
    SaveVideo = self.FLAGS.saveVideo 

    if self.FLAGS.track : 
     if self.FLAGS.tracker == "deep_sort": 
      from deep_sort import generate_detections 
      from deep_sort.deep_sort import nn_matching 
      from deep_sort.deep_sort.tracker import Tracker 
      metric = nn_matching.NearestNeighborDistanceMetric(
      "cosine", 0.2, 100) 
      tracker = Tracker(metric) 
      encoder = generate_detections.create_box_encoder(
       os.path.abspath("deep_sort/resources/networks/mars-small128.ckpt-68577")) 
     elif self.FLAGS.tracker == "sort": 
      from sort.sort import Sort 
      encoder = None 
      tracker = Sort() 
    if self.FLAGS.BK_MOG and self.FLAGS.track : 
     fgbg = cv2.bgsegm.createBackgroundSubtractorMOG() 

    if file == 'camera': 
     file = 0 
    else: 
     assert os.path.isfile(file), \ 
     'file {} does not exist'.format(file) 

    camera = cv2.VideoCapture(file) 

    if file == 0: 
     self.say('Press [ESC] to quit video') 

    assert camera.isOpened(), \ 
    'Cannot capture source' 

    if self.FLAGS.csv : 
     f = open('{}.csv'.format(file),'w') 
     writer = csv.writer(f, delimiter=',') 
     writer.writerow(['frame_id', 'track_id' , 'x', 'y', 'w', 'h']) 
     f.flush() 
    else : 
     f =None 
     writer= None 
    if file == 0:#camera window 
     cv2.namedWindow('', 0) 
     _, frame = camera.read() 
     height, width, _ = frame.shape 
     cv2.resizeWindow('', width, height) 
    else: 
     _, frame = camera.read() 
     height, width, _ = frame.shape 

    if SaveVideo: 
     fourcc = cv2.VideoWriter_fourcc(*'XVID') 
     if file == 0:#camera window 
      fps = 1/self._get_fps(frame) 
      if fps < 1: 
      fps = 1 
     else: 
      fps = round(camera.get(cv2.CAP_PROP_FPS)) 
     videoWriter = cv2.VideoWriter(
      'output_{}'.format(file), fourcc, fps, (width, height)) 

    # buffers for demo in batch 
    buffer_inp = list() 
    buffer_pre = list() 

    elapsed = 0 
    start = timer() 
    self.say('Press [ESC] to quit demo') 
    #postprocessed = [] 
    # Loop through frames 
    n = 0 
    while camera.isOpened(): 
     elapsed += 1 
     _, frame = camera.read() 
     if frame is None: 
      print ('\nEnd of Video') 
      break 
     if self.FLAGS.skip != n : 
      n+=1 
      continue 
     n = 0 
     if self.FLAGS.BK_MOG and self.FLAGS.track : 
      fgmask = fgbg.apply(frame) 
     else : 
      fgmask = None 
     preprocessed = self.framework.preprocess(frame) 
     buffer_inp.append(frame) 
     buffer_pre.append(preprocessed) 
     # Only process and imshow when queue is full 
     if elapsed % self.FLAGS.queue == 0: 
      feed_dict = {self.inp: buffer_pre} 
      net_out = self.sess.run(self.out, feed_dict) 
      for img, single_out in zip(buffer_inp, net_out): 
       if not self.FLAGS.track : 
        postprocessed = self.framework.postprocess(
         single_out, img, save= False) 
       else : 
        postprocessed = self.framework.postprocess(
         single_out, img,frame_id = elapsed,csv_file=f,csv=writer,mask = fgmask,encoder=encoder,tracker=tracker,save=False) 
       if SaveVideo: 
        videoWriter.write(postprocessed) 
       if self.FLAGS.display : 
        cv2.imshow('', postprocessed) 
      # Clear Buffers 
      buffer_inp = list() 
      buffer_pre = list() 

     if elapsed % 5 == 0: 
      sys.stdout.write('\r') 
      sys.stdout.write('{0:3.3f} FPS'.format(
       elapsed/(timer() - start))) 
      sys.stdout.flush() 
     if self.FLAGS.display : 
      choice = cv2.waitKey(1) 
      if choice == 27: 
       break 

    sys.stdout.write('\n') 
    if SaveVideo: 
     videoWriter.release() 
    if self.FLAGS.csv : 
     f.close() 
    camera.release() 
    if self.FLAGS.display : 
     cv2.destroyAllWindows() 

def to_darknet(self): 
    darknet_ckpt = self.darknet 

    with self.graph.as_default() as g: 
     for var in tf.global_variables(): 
      name = var.name.split(':')[0] 
      var_name = name.split('-') 
      l_idx = int(var_name[0]) 
      w_sig = var_name[1].split('/')[-1] 
      l = darknet_ckpt.layers[l_idx] 
      l.w[w_sig] = var.eval(self.sess) 

    for layer in darknet_ckpt.layers: 
     for ph in layer.h: 
      layer.h[ph] = None 

    return darknet_ckpt 

Answer 1

これはかなり複雑なセットアップです。基本的にhelp.pyファイルに「単独」されている機能が、その後、他のクラス定義に「パッチを適用」されている（build.pyを参照してください...

from . import help 
...  
class TFNet(object): 
    ... 
    # imported methods 
    say = help.say 
    load_from_ckpt = help.load_from_ckpt 
    ... 
      self.say('\nLoading from .pb and .meta') 
    ...  
     if self.FLAGS.load != 0: self.load_from_ckpt() 

これは、任意のドキュメンテーション文字列を含まない）、IMO（本当に手抜きです関数定義内の引数が何であるかを説明すること。この種のものを行うための

はるかに通常の方法は、派生クラスによって継承することができ、親クラスを持つことです。

であなたの質問への答えでEDITコメント、はい。このように

import help 

class OddSystem(object): 
    say = help.say 

o = OddSystem() 
o.say('hello world!') 

# more normal system would use inheritance, help.py defines a parent class Help 
class NormalSystem(help.Help): 
    def __init__(self): 
    ''' normal definitions etc ''' 
    pass 

n = NormalSystem() 
n.say('that is better!') 

help.pyは、同じディレクトリ内のファイルです：

def say(self, msg): 
    print(msg) 

class Help(object): 
    def say(self, msg): 
    print(msg)