我想使用from_generator()函数创建一些tf.data.Dataset.我想向生成器函数(raw_data_gen)发送一个参数.这个想法是生成器函数将根据发送的参数产生不同的数据.通过这种方式,我希望raw_data_gen能够提供培训,验证或测试数据.

training_dataset = tf.data.Dataset.from_generator(raw_data_gen,(tf.float32,tf.uint8),([None,1],[None]),args=([1]))

validation_dataset = tf.data.Dataset.from_generator(raw_data_gen,args=([2]))

test_dataset = tf.data.Dataset.from_generator(raw_data_gen,args=([3]))

我尝试以这种方式调用from_generator()时得到的错误消息是：

TypeError: from_generator() got an unexpected keyword argument 'args'

这是raw_data_gen函数,虽然我不确定你是否需要这个,因为我的预感是问题是调用from_generator()：

def raw_data_gen(train_val_or_test):

    if train_val_or_test == 1:        
        #For every filename collected in the list
        for filename,lab in training_filepath_label_dict.items():
            raw_data,samplerate = soundfile.read(filename)
            try: #assume the audio is stereo,ready to be sliced
                raw_data = raw_data[:,0] #raw_data is a np.array,just take first channel with slice
            except IndexError:
                pass #this must be mono audio
            yield raw_data,lab

    elif train_val_or_test == 2:
        #For every filename collected in the list
        for filename,lab in validation_filepath_label_dict.items():
            raw_data,lab

    elif train_val_or_test == 3:
        #For every filename collected in the list
        for filename,lab in test_filepath_label_dict.items():
            raw_data,lab

    else:
        print("generator function called with an argument not in [1,2,3]")
        raise ValueError()