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Python eval.QGEvalCap方法代码示例

本文整理汇总了Python中eval.QGEvalCap方法的典型用法代码示例。如果您正苦于以下问题:Python eval.QGEvalCap方法的具体用法?Python eval.QGEvalCap怎么用?Python eval.QGEvalCap使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在eval的用法示例。


在下文中一共展示了eval.QGEvalCap方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: eval

# 需要导入模块: import eval [as 别名]
# 或者: from eval import QGEvalCap [as 别名]
def eval(out_file, src_file, tgt_file, isDIn=False, num_pairs=500):
    """
        Given a filename, calculate the metric scores for that prediction file

        isDin: boolean value to check whether input file is DirectIn.txt
    """

    pairs = []
    with open(src_file, 'r') as infile:
        for line in infile:
            pair = {}
            pair['tokenized_sentence'] = line[:-1].strip().lower()
            pairs.append(pair)

    with open(tgt_file, "r") as infile:
        cnt = 0
        for line in infile:
            pairs[cnt]['tokenized_question'] = line[:-1].strip()
            cnt += 1

    output = []
    with open(out_file, 'r') as infile:
        for line in infile:
            line = fix_tokenization(line[:-1].strip()).lower()
            output.append(line)

    for idx, pair in enumerate(pairs):
        pair['prediction'] = output[idx]

    # eval
    from eval import QGEvalCap
    import json
    from json import encoder
    encoder.FLOAT_REPR = lambda o: format(o, '.4f')

    res = defaultdict(lambda: [])
    gts = defaultdict(lambda: [])

    for pair in pairs[:]:
        key = pair['tokenized_sentence']
        res[key] = [pair['prediction'].encode('utf-8')]

        # gts
        gts[key].append(pair['tokenized_question'].encode('utf-8'))

    QGEval = QGEvalCap(gts, res)
    return QGEval.evaluate() 
开发者ID:microsoft,项目名称:unilm,代码行数:49,代码来源:eval.py

示例2: eval

# 需要导入模块: import eval [as 别名]
# 或者: from eval import QGEvalCap [as 别名]
def eval(out_file, src_file, tgt_file, isDIn=False, num_pairs=500):
    """
        Given a filename, calculate the metric scores for that prediction file

        isDin: boolean value to check whether input file is DirectIn.txt
    """

    pairs = []
    with open(src_file, 'r') as infile:
        for line in infile:
            pair = {}
            pair['tokenized_sentence'] = line[:-1].strip().lower()
            pairs.append(pair)

    with open(tgt_file, "r") as infile:
        cnt = 0
        for line in infile:
            pairs[cnt]['tokenized_question'] = " ".join(
                detokenize(line[:-1].strip().split())).lower()
            cnt += 1

    output = []
    with open(out_file, 'r') as infile:
        for line in infile:
            line = line[:-1].strip().lower()
            output.append(line)

    for idx, pair in enumerate(pairs):
        pair['prediction'] = output[idx]

    # eval
    from eval import QGEvalCap
    import json
    from json import encoder
    encoder.FLOAT_REPR = lambda o: format(o, '.4f')

    res = defaultdict(lambda: [])
    gts = defaultdict(lambda: [])

    for pair in pairs[:]:
        key = pair['tokenized_sentence']
        res[key] = [pair['prediction'].encode('utf-8')]

        # gts
        gts[key].append(pair['tokenized_question'].encode('utf-8'))

    QGEval = QGEvalCap(gts, res)
    return QGEval.evaluate() 
开发者ID:microsoft,项目名称:unilm,代码行数:50,代码来源:eval_on_unilm_tokenized_ref.py

示例3: eval

# 需要导入模块: import eval [as 别名]
# 或者: from eval import QGEvalCap [as 别名]
def eval(out_file, src_file, tgt_file, isDIn = False, num_pairs = 500):
    """
        Given a filename, calculate the metric scores for that prediction file

        isDin: boolean value to check whether input file is DirectIn.txt
    """

    pairs = []
    with open(src_file, 'r') as infile:
        for line in infile:
            pair = {}
            pair['tokenized_sentence'] = line[:-1]
            pairs.append(pair)

    with open(tgt_file, "r") as infile:
        cnt = 0
        for line in infile:
            pairs[cnt]['tokenized_question'] = line[:-1]
            cnt += 1

    output = []
    with open(out_file, 'r') as infile:
        for line in infile:
            line = line[:-1]
            output.append(line)


    for idx, pair in enumerate(pairs):
        pair['prediction'] = output[idx]


    ## eval
    from eval import QGEvalCap
    import json
    from json import encoder
    encoder.FLOAT_REPR = lambda o: format(o, '.4f')

    res = defaultdict(lambda: [])
    gts = defaultdict(lambda: [])
    for pair in pairs[:]:
        key = pair['tokenized_sentence']
        res[key] = [pair['prediction'].encode('utf-8')]

        ## gts 
        gts[key].append(pair['tokenized_question'].encode('utf-8'))

    QGEval = QGEvalCap(gts, res)
    return QGEval.evaluate() 
开发者ID:yanghoonkim,项目名称:NQG_ASs2s,代码行数:50,代码来源:eval.py

示例4: eval

# 需要导入模块: import eval [as 别名]
# 或者: from eval import QGEvalCap [as 别名]
def eval(out_file, src_file, tgt_file, isDIn = False, num_pairs = 500):
    """
        Given a filename, calculate the metric scores for that prediction file

        isDin: boolean value to check whether input file is DirectIn.txt
    """

    pairs = []
    with open(src_file, 'r') as infile:
        for line in infile:
            pair = {}
            pair['tokenized_sentence'] = line[:-1]
            pairs.append(pair)

    with open(tgt_file, "r") as infile:
        cnt = 0
        for line in infile:
            pairs[cnt]['tokenized_question'] = line[:-1]
            cnt += 1

    output = []
    with open(out_file, 'r') as infile:
        for line in infile:
            line = line[:-1]
            output.append(line)


    for idx, pair in enumerate(pairs):
        pair['prediction'] = output[idx]


    ## eval
    from eval import QGEvalCap
    import json
    from json import encoder
    encoder.FLOAT_REPR = lambda o: format(o, '.4f')

    res = defaultdict(lambda: [])
    gts = defaultdict(lambda: [])
    for pair in pairs[:]:
        key = pair['tokenized_sentence']
        res[key] = [pair['prediction'].encode('utf-8')]

        ## gts
        gts[key].append(pair['tokenized_question'].encode('utf-8'))

    QGEval = QGEvalCap(gts, res)
    return QGEval.evaluate() 
开发者ID:hugochan,项目名称:RL-based-Graph2Seq-for-NQG,代码行数:50,代码来源:eval.py

示例5: eval

# 需要导入模块: import eval [as 别名]
# 或者: from eval import QGEvalCap [as 别名]
def eval(out_file, src_file, tgt_file, isDIn = False, num_pairs = 500):
    """
        Given a filename, calculate the metric scores for that prediction file

        isDin: boolean value to check whether input file is DirectIn.txt
    """

    pairs = []
    with open(src_file, 'r') as infile:
        for line in infile:
            pair = {}
            pair['tokenized_sentence'] = line[:-1]
            pairs.append(pair)

    with open(tgt_file, "r") as infile:
        cnt = 0
        for line in infile:
            pairs[cnt]['tokenized_question'] = line[:-1]
            cnt += 1

    output = []
    with open(out_file, 'r') as infile:
        for line in infile:
            line = line[:-1]
            output.append(line)


    for idx, pair in enumerate(pairs):
        pair['prediction'] = output[idx]


    ## eval
    from eval import QGEvalCap
    import json
    from json import encoder
    encoder.FLOAT_REPR = lambda o: format(o, '.4f')

    res = defaultdict(lambda: [])
    gts = defaultdict(lambda: [])

    set_trace()

    for pair in pairs[:]:
        key = pair['tokenized_sentence']
        res[key] = [pair['prediction'].encode('utf-8')]

        ## gts 
        gts[key].append(pair['tokenized_question'].encode('utf-8'))

    set_trace()

    QGEval = QGEvalCap(gts, res)
    return QGEval.evaluate() 
开发者ID:moonlightlane,项目名称:QG-Net,代码行数:55,代码来源:eval.py


注:本文中的eval.QGEvalCap方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。