修改了随机读取数据的方法,可以提高模型的泛化能力
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@ -193,9 +193,11 @@ class DataSpeech():
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label_length = []
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ran_num = random.randint(0,self.DataNum - 1) # 获取一个随机数
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for i in range(batch_size):
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data_input, data_labels = self.GetData((ran_num + i) % self.DataNum) # 从随机数开始连续向后取一定数量数据
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ran_num = random.randint(0,self.DataNum - 1) # 获取一个随机数
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data_input, data_labels = self.GetData(ran_num) # 通过随机数取一个数据
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#data_input, data_labels = self.GetData((ran_num + i) % self.DataNum) # 从随机数开始连续向后取一定数量数据
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input_length.append(data_input.shape[0] // 8 + data_input.shape[0] % 8)
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#print(data_input, data_labels)
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