src/build_embeddings.py
def load_glove_embeddings_from_txt_file(filename):
    """
    DESCRIPTION: 
            Loads a word embedding file and returns a python dictionary of the form
            (word, [vector of embeddings]) in memory
    INPUT: 
            filename: name of the word embedding file to be loaded
    OUTPUT: 
            words: python dictionary of the form (word, [vector of embeddings])
    """
    print('Loading', filename ,'embeddings file')

    if not os.path.exists(filename):
        print(filename,'embeddings not found')
        return None
    print('Constructing dictionary for', filename, 'file')
    words = {} #key= word, value=embeddings
    with open(filename, "r") as f:
        for line in f:
            tokens = line.strip().split()
            words[tokens[0]] = np.array([float(x) for x in tokens[1:]])
    print('DONE')
    return words

    DESCRIPTION: 
            Loads a word embedding file and returns a python dictionary of the form
            (word, [vector of embeddings]) in memory
    INPUT: 
            filename: name of the word embedding file to be loaded
    OUTPUT: 
            words: python dictionary of the form (word, [vector of embeddings])
    
Loads a word embedding file and returns a python dictionary of the form
(word, [vector of embeddings]) in memory
INPUT:
filename: name of the word embedding file to be loaded
OUTPUT:
words: python dictionary of the form (word, [vector of embeddings])
Loads a word embedding file and returns a python dictionary of the form ( word [ vector of embeddings ] ) in memory INPUT : filename : name of the word embedding file to be loaded OUTPUT : words : python dictionary of the form ( word [ vector of embeddings ] )
def load_glove_embeddings_from_txt_file(filename):
    print('Loading', filename ,'embeddings file')
    if not os.path.exists(filename):
        print(filename,'embeddings not found')
        return None
    print('Constructing dictionary for', filename, 'file')
    words = {} 
    with open(filename, "r") as f:
        for line in f:
            tokens = line.strip().split()
            words[tokens[0]] = np.array([float(x) for x in tokens[1:]])
    print('DONE')
    return words
def load_glove_embeddings_from_txt_file ( filename ) : print ( 'Loading' , filename , 'embeddings file' ) if not os . path . exists ( filename ) : print ( filename , 'embeddings not found' ) return None print ( 'Constructing dictionary for' , filename , 'file' ) words = { } with open ( filename , "r" ) as f : for line in f : tokens = line . strip ( ) . split ( ) words [ tokens [ 0 ] ] = np . array ( [ float ( x ) for x in tokens [ 1 : ] ] ) print ( 'DONE' ) return words
DESCRIPTION:
Loads a word embedding file and returns a python dictionary of the form
(word, [vector of embeddings]) in memory
INPUT:
filename: name of the word embedding file to be loaded
OUTPUT:
words: python dictionary of the form (word, [vector of embeddings])
DESCRIPTION : Loads a word embedding file and returns a python dictionary of the form ( word [ vector of embeddings ] ) in memory INPUT : filename : name of the word embedding file to be loaded OUTPUT : words : python dictionary of the form ( word [ vector of embeddings ] )
"""
    DESCRIPTION: 
            Loads a word embedding file and returns a python dictionary of the form
            (word, [vector of embeddings]) in memory
    INPUT: 
            filename: name of the word embedding file to be loaded
    OUTPUT: 
            words: python dictionary of the form (word, [vector of embeddings])
    """ #key= word, value=embeddings
filename