numpy.argsort - python examples

Here are the examples of the python api numpy.argsort taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

145 Examples 7

3 View Complete Implementation : a1_seq2seq_attention_predict.py
Copyright MIT License
Author : brightmart
def process_each_row_get_lable(row,vocabulary_index2word_label,vocabulary_word2index_label,result_list):
    """
    :param row: it is a list.length is number of labels. e.g. 2002
    :param vocabulary_index2word_label
    :param result_list
    :return: a lable
    """
    label_list=list(np.argsort(row))
    label_list.reverse()
    #print("label_list:",label_list) # a list,length is number of labels.
    for i,index in enumerate(label_list): # if index is not exists, and not _PAD,_END, then it is the label we want.
        #print(i,"index:",index)
        flag1=vocabulary_index2word_label[index] not in result_list
        flag2=index!=vocabulary_word2index_label[_PAD]
        flag3=index!=vocabulary_word2index_label[_END]
        if flag1 and flag2 and flag3:
            #print("going to return ")
            return vocabulary_index2word_label[index]

3 View Complete Implementation : p1_HierarchicalAttention_predict.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_with_value(logits,vocabulary_index2word_label,top_number=5):
    index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
    index_list=index_list[::-1]
    value_list=[]
    label_list=[]
    for index in index_list:
        label=vocabulary_index2word_label[index]
        label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        value_list.append(logits[index])
    return label_list,value_list

3 View Complete Implementation : a8_predict.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_batch(question_id_sublist,logits_batch,vocabulary_index2word_label,f,top_number=5):
    #print("get_label_using_logits.shape:", logits_batch.shape) # (10, 1999))=[batch_size,num_labels]===>需要(10,5)
    for i,logits in enumerate(logits_batch):
        index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
        index_list=index_list[::-1]
        label_list=[]
        for index in index_list:
            label=vocabulary_index2word_label[index]
            label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        #print("get_label_using_logits.label_list",label_list)
        write_question_id_with_labels(question_id_sublist[i], label_list, f)
    f.flush()

3 View Complete Implementation : a08_predict_ensemble.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_batch(question_id_sublist,logits_batch,vocabulary_index2word_label,f,top_number=5):
    #print("get_label_using_logits.shape:", logits_batch.shape) # (10, 1999))=[batch_size,num_labels]===>需要(10,5)
    for i,logits in enumerate(logits_batch):
        index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
        index_list=index_list[::-1]
        label_list=[]
        for index in index_list:
            label=vocabulary_index2word_label[index]
            label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        #print("get_label_using_logits.label_list",label_list)
        write_question_id_with_labels(question_id_sublist[i], label_list, f)
    f.flush()

3 View Complete Implementation : p71_TextRCNN_predict.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_batch(question_id_sublist,logits_batch,vocabulary_index2word_label,f,top_number=5):
    #print("get_label_using_logits.shape:", logits_batch.shape) # (10, 1999))=[batch_size,num_labels]===>需要(10,5)
    for i,logits in enumerate(logits_batch):
        index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
        index_list=index_list[::-1]
        label_list=[]
        for index in index_list:
            label=vocabulary_index2word_label[index]
            label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        #print("get_label_using_logits.label_list",label_list)
        write_question_id_with_labels(question_id_sublist[i], label_list, f)
    f.flush()

3 View Complete Implementation : p8_TextCNN_predict_exp.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_with_value(logits,vocabulary_index2word_label,top_number=5):
    index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
    index_list=index_list[::-1]
    value_list=[]
    label_list=[]
    for index in index_list:
        label=vocabulary_index2word_label[index]
        label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        value_list.append(logits[index])
    return label_list,value_list

3 View Complete Implementation : p8_TextRNN_predict.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_batch(question_id_sublist,logits_batch,vocabulary_index2word_label,f,top_number=5):
    #print("get_label_using_logits.shape:", logits_batch.shape) # (10, 1999))=[batch_size,num_labels]===>需要(10,5)
    for i,logits in enumerate(logits_batch):
        index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
        index_list=index_list[::-1]
        label_list=[]
        for index in index_list:
            label=vocabulary_index2word_label[index]
            label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        #print("get_label_using_logits.label_list",label_list)
        write_question_id_with_labels(question_id_sublist[i], label_list, f)
    f.flush()

3 View Complete Implementation : p7_TextCNN_predict.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_with_value(logits,vocabulary_index2word_label,top_number=5):
    index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
    index_list=index_list[::-1]
    value_list=[]
    label_list=[]
    for index in index_list:
        label=vocabulary_index2word_label[index]
        label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        value_list.append(logits[index])
    return label_list,value_list

3 View Complete Implementation : a3_predict.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_with_value(logits,vocabulary_index2word_label,top_number=5):
    index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
    index_list=index_list[::-1]
    value_list=[]
    label_list=[]
    for index in index_list:
        label=vocabulary_index2word_label[index]
        label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        value_list.append(logits[index])
    return label_list,value_list

3 View Complete Implementation : p7_TextCNN_predict_exp512_simple.py
Copyright MIT License
Author : brightmart
def get_label_using_logits_with_value(logits,vocabulary_index2word_label,top_number=5):
    index_list=np.argsort(logits)[-top_number:] #print("sum_p", np.sum(1.0 / (1 + np.exp(-logits))))
    index_list=index_list[::-1]
    value_list=[]
    label_list=[]
    for index in index_list:
        label=vocabulary_index2word_label[index]
        label_list.append(label) #('get_label_using_logits.label_list:', [u'-3423450385060590478', u'2838091149470021485', u'-3174907002942471215', u'-1812694399780494968', u'6815248286057533876'])
        value_list.append(logits[index])
    return label_list,value_list