try add in1k_v2

vi_backbones.py

@@ -2,7 +2,7 @@ import os
 import re
 import requests
 import datasets
-import pandas as pd
+# import pandas as pd
 from bs4 import BeautifulSoup
 
 
@@ -12,10 +12,10 @@ _HOMEPAGE = "https://huggingface.co/datasets/george-chou/" + _DBNAME
 
 _URL = 'https://pytorch.org/vision/main/_modules/'
 
-_TYPES = pd.read_csv(_HOMEPAGE + '/resolve/main/data/backbone.csv',
-                     index_col='ver').to_dict()['type']
+# _TYPES = pd.read_csv(_HOMEPAGE + '/resolve/main/data/backbone.csv',
+#                      index_col='ver').to_dict()['type']
 
-_NAMES = sorted(list(set(_TYPES.values())))
+# _NAMES = sorted(list(set(_TYPES.values())))
 
 
 class vi_backbones(datasets.GeneratorBasedBuilder):
@@ -27,8 +27,8 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
                     "ver": datasets.Value("string"),
                     "type": datasets.Value("string"),
                     # "type": datasets.features.ClassLabel(names=_NAMES),
-                    "input_size": datasets.Value("int32"),
-                    "output_size": datasets.Value("int32"),
+                    "input_size": datasets.Value("int16"),
+                    "num_params": datasets.Value("int32"),
                     "url": datasets.Value("string"),
                 }
             ),
@@ -43,50 +43,72 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
         return BeautifulSoup(html, 'html.parser')
 
     def _generate_dataset(self, url):
+
         torch_page = self._parse_url(url)
         article = torch_page.find('article', {'id': 'pytorch-article'})
         ul = article.find('ul').find('ul')
-        dataset = []
+        in1k_v1, in1k_v2 = [], []
+
         for li in ul.find_all('li'):
             name = str(li.text)
             if name.__contains__('torchvision.models.') and len(name.split('.')) == 3:
                 if name.__contains__('_api') or name.__contains__('feature_extraction'):
                     continue
+
                 href = li.find('a').get('href')
                 model_page = self._parse_url(url + href)
                 divs = model_page.select('div.viewcode-block')
+
                 for div in divs:
                     div_id = str(div['id'])
                     if div_id.__contains__('_Weights'):
                         m_ver = div_id.split('_Weight')[0].lower()
                         m_type = re.search('[a-zA-Z]+', m_ver).group(0)
-                        input_size = int(
-                            div.find('span', {'class': 'mi'}).text)
-                        m_url = str(div.find('span', {'class': 's2'}).text)
+                        ints = div.find_all('span', {'class': 'mi'})
+                        m_urls = div.find_all('span', {'class': 's2'})
+                        input_size = int(ints[0].text)
+                        num_params = int(ints[1].text)
+                        m_url = m_urls[0].text
                         m_dict = {
                             'ver': m_ver,
                             'type': m_type,
                             'input_size': input_size,
+                            'num_params': num_params,
                             'url': m_url
                         }
-                        print('Adding ' + m_ver)
-                        dataset.append(m_dict)
-        return dataset
+                        # print('Adding ' + m_ver + ' on IMAGENET1K_V1')
+                        in1k_v1.append(m_dict)
+
+                        if len(ints) > 2 and len(m_urls) > 1:
+                            input_size = int(ints[2].text)
+                            num_params = int(ints[3].text)
+                            m_url = m_urls[1].text
+                            m_dict = {
+                                'ver': m_ver,
+                                'type': m_type,
+                                'input_size': input_size,
+                                'num_params': num_params,
+                                'url': m_url
+                            }
+                            # print('Adding ' + m_ver + ' on IMAGENET1K_V2')
+                            in1k_v2.append(m_dict)
+
+        return in1k_v1, in1k_v2
 
     def _split_generators(self, dl_manager):
-        dataset = self._generate_dataset(_URL)
+        in1k_v1, in1k_v2 = self._generate_dataset(_URL)
 
         return [
             datasets.SplitGenerator(
                 name="IMAGENET1K_V1",
                 gen_kwargs={
-                    "files": dataset,
+                    "files": in1k_v1,
                 },
             ),
             datasets.SplitGenerator(
                 name="IMAGENET1K_V2",
                 gen_kwargs={
-                    "files": dataset,
+                    "files": in1k_v2,
                 },
             ),
         ]
@@ -97,6 +119,6 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
                 "ver": model['ver'],
                 "type": model['type'],
                 "input_size": model['input_size'],
-                "output_size": 9216,
+                "num_params": model['num_params'],
                 "url": model['url'],
             }