Python WeightedRandomSampler.__iter__ Beispiele

Beispiel #1

Datei: samplers.py Projekt: cnlinxi/Multilingual_Text_to_Speech

class RandomImbalancedSampler(Sampler):
    """Samples randomly imbalanced dataset (with repetition).
    
    Argument:
        data_source -- instance of TextToSpeechDataset
    """
    def __init__(self, data_source):

        lebel_freq = {}
        for idx in range(len(data_source)):
            label = data_source.items[idx]['language']
            if label in lebel_freq: lebel_freq[label] += 1
            else: lebel_freq[label] = 1

        total = float(sum(lebel_freq.values()))
        weights = [
            total / lebel_freq[data_source.items[idx]['language']]
            for idx in range(len(data_source))
        ]

        self._sampler = WeightedRandomSampler(weights, len(weights))

    def __iter__(self):
        return self._sampler.__iter__()

    def __len__(self):
        return len(self._sampler)

Beispiel #2

Datei: dataset.py Projekt: Tomiinek/WaveRNN

class RandomImbalancedSampler(Sampler):
    def __init__(self, data_source):
        lebel_freq = {}
        for idx in range(len(data_source)):
            label = data_source.items[idx]['language']
            if label in lebel_freq: lebel_freq[label] += 1
            else: lebel_freq[label] = 1

        total = float(sum(lebel_freq.values()))
        weights = [
            total / lebel_freq[data_source.items[idx]['language']]
            for idx in range(len(data_source))
        ]
        self._sampler = WeightedRandomSampler(weights, len(weights))

    def __iter__(self):
        return self._sampler.__iter__()

    def __len__(self):
        return len(self._sampler)