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python - 拆分后获取子字符串的值

问题描述

我有一个看起来像这样的 json 文件：

{
    "model": "Sequential",
    "layers": [
        {
            "L1": "Conv2D(filters = 64, kernel_size=(2,2), strides=(2,2), padding='same', data_format='channels_last', activation='relu', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.), input_shape=(224,224,3))",
            "L2": "MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same', data_format='channels_last')",
            "L3": "Conv2D(filters = 64, kernel_size=(2,2), strides=(2,2), padding='same', data_format='channels_last', activation='relu', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L4": "MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same', data_format='channels_last')",
            "L5": "Conv2D(filters = 64, kernel_size=(2,2), strides=(2,2), padding='same', data_format='channels_last', activation='relu', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L6": "Conv2D(filters = 64, kernel_size=(2,2), strides=(2,2), padding='same', data_format='channels_last', activation='relu', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L7": "Conv2D(filters = 64, kernel_size=(2,2), strides=(2,2), padding='same', data_format='channels_last', activation='relu', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L8": "MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same', data_format='channels_last')",
            "L9": "Flatten()",
            "L10": "Dense(4096, activation='softmax', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L11": "Dropout(0.4)",
            "L12": "Dense(2048, activation='softmax', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L13": "Dropout(0.4)",
            "L14": "Dense(1000, activation='softmax', use_bias=True, kernel_initializer='zeros', bias_initializer='zeros', kernel_regularizer=regularizers.l1(0.), bias_regularizer=regularizers.l1(0.), activity_regularizer=regularizers.l1(0.), kernel_constraint=max_norm(2.), bias_constraint=max_norm(2.))",
            "L15": "Dropout(0.4)"
        }
    ]
}

我想获取有关 json 文件中存在什么层的信息。例如，Conv2D、MaxPooling2D、Flatten() 等。

另外，我想知道过滤器、内核大小、步幅、激活等字符串的值。

我尝试通过这样做来获取图层名称：

with open('model.json','r') as fb:
    con = json.load(fb)
con['layers'][0]['L1'].split('(', 1)[0].rstrip()

输出是'Conv2d'。同样，我得到了其他图层名称。

我需要帮助的是获取过滤器的值（例如 L1 中的 64）。

我试过这样做：

c = con['layers'][0]['L1'].split('(', 1)[1].rstrip()
c.split(',')
['filters = 8', ' kernel_size=(3', '3)', ' strides=(1', ' 1)', " padding='valid'", " data_format='channels_last'", " activation='relu'", ' use_bias=True', " kernel_initializer='zeros'", " bias_initializer='zeros'", ' kernel_regularizer=regularizers.l1(0.)', ' bias_regularizer=regularizers.l1(0.)', ' activity_regularizer=regularizers.l2(0.)', ' kernel_constraint=max_norm(2.)', ' bias_constraint=max_norm(2.)', ' input_shape=(28', '28', '1))']

但我仍然没有得到价值。

有谁知道如何获取这些信息？

标签： pythonregexpython-3.xsplit

解决方案

更新：使用正则表达式，您可以提取关键字参数。然后拆分“=”以查找每个层的每个关键字参数的值。

import json
import re

with open('model.json','r') as fb:
  con = json.load(fb)

for layer_key in con['layers'][0]:
  print("Layer: {}".format(layer_key))
  layer = con['layers'][0][layer_key]
  layers_kwargs = re.sub('^(.*?)\(', '', layer)[:-1]
  if not layers_kwargs:
    print('No kwargs')
    continue
  for kwarg in layers_kwargs.split(', '):
    kwarg = [i.strip() for i in kwarg.split('=')]
    if len(kwarg) != 2:
      print('No key', kwarg)
      continue
    k = kwarg[0]
    v = kwarg[1]
    print(k,v)

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