pranjalAI

# Convert the model.
converter = tf.lite.TFLiteConverter.from_keras_model(generator)
tflite_model = converter.convert()

pranjalAI

class ResidualSep(nn.Module):
    def __init__(self, channels, dilation=1):
        super().__init__()

        self.blocks = nn.Sequential(
            nn.ReLU(),
            nn.ReflectionPad2d(dilation),
            nn.Conv2d(channels, channels, kernel_size=3, stride=1, 
                      padding=0, dilation=dilation, 
                      groups=channels, bias=False),

pranjalAI

class ResidualHourglass(nn.Module):
    def __init__(self, channels, mult=0.5):
        super().__init__()

        hidden_channels = int(channels * mult)

        self.blocks = nn.Sequential(
            nn.ReLU(),
            # Downsample
            nn.ReflectionPad2d(1),

pranjalAI

class TransformerNet(torch.nn.Module):
    def __init__(self, width=8):
        super().__init__()

        self.blocks = nn.Sequential( 
            nn.ReflectionPad2d(1),
            nn.Conv2d(3, width, kernel_size=3, stride=1, padding=0, bias=False),
            nn.BatchNorm2d(width, affine=True),
            ResidualHourglass(channels=width),
            ResidualHourglass(channels=width),

pranjalAI

links=[]
pubs=["swlh",'illumination','analytics-vidhya','better-advice','the-post-grad-survival-guide','the-ascent']
stop_words = set(stopwords.words('english')) 
for pub in pubs:
    links.append("https://medium.com/"+str(pub)+"/latest")

pranjalAI

pub_links={}
for link in links:
    response = requests.get(link)
    soup = BeautifulSoup(response.text, "lxml" )
    data = soup.find('div', class_ = 'js-postListHandle')
    my_data=data.find('div',class_ = 'js-postListHandle')
    final_data=my_data.find_all('div',{'class':'postArticle-content'})
    Alinks=[]
    for Alink in final_data:
        href=Alink.find("a").get('href').split("?")[0]

pranjalAI

response = requests.get(data_link)
soup = BeautifulSoup(response.text, "lxml" )
para=soup.find_all("p")
head1=soup.find_all("h1")
head2=soup.find_all("h2")
head3=soup.find_all("h3")

pranjalAI

text=[]
for paragraph in para:
    text.append(paragraph.text)
for header1 in head1:
    text.append(header1.text)
for header2 in head2:
    text.append(header2.text)
for header3 in head3:
    text.append(header3.text)

pranjalAI

doc = processArti(content)
doc = tokenize(doc)
doc = [wd for wd in doc if wd not in stop_words]
doc = sorted(set(doc))
doc = " ".join(doc)
doc = tokens(doc)
doc = removeNum(doc)
doc = [i for i in doc if not i==""]
doc = " ".join(doc)

pranjalAI

for pub in pubs:
  for data_link in pub_links[pub]:
      doc=get_doc(data_link)
      to_add = pd.DataFrame({"publication":[pub],"article":[doc]})
      data=data.append(to_add, ignore_index = True)