dataset_val=keras.preprocessing.timeseries_dataset_from_array( x_val, y_val, sequence_length=sequence_length, sampling_rate=step, batch_size=batch_size, ) 补0之后,测试数据比原来数据多past-1个,2个。 #输出数据forbatchindataset_val.take(1): inputs, targets=batchprint("val Input shape:", i...
keras.preprocessing.timeseries_dataset_from_array( data, targets, sequence_length, # 窗口大小 sequence_stride=1, #连续输出序列之间的周期。对于步幅s,输出采样将开始索引data[i],data[i + s],data[i + 2 * s],等。 sampling_rate=1, # 序列中连续的各个时间步之间的时间间隔。对于rate r,时间步 ...
我有一个pandas数据基,为了生成一个tensorflow数据集,我将其转换为一个numpy数组: dataset = tf.keras.utils.timeseries_dataset_from_array当我试图训练这个模型时,我会遇到像ValueError: Cannot convert a partially known TensorShape (None, None) to a Tensor.这样的错误我怀疑这是由于我的数据集</e ...
I have gone through the example-2 in the TF documentation of keras.utils.timeseries_dataset_from_array. With existing code we can only generate one batch of dataset.In TF forum one of the user raised concern that users may confuse why we are using input_data = data[:-10] as it can ...
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return np.array(X), np.array(y) time_step = 10 # 设定用于输入的时间步长 X, y = create_dataset(df_scaled, time_step) # 拆分训练和测试数据集 train_size = int(len(X) * 0.7) test_size = len(X) - train_size X_train, X_test = X[:train_size], X[train_size:] y_train, y...
fromnumpyimportarrayfromnumpyimporthstackfromnumpyimportinsertfromkeras.preprocessing.sequenceimportTimeseriesGenerator# 给定数据in_seq1=array([10,20,30,40,50,60,70,80,90,100])in_seq2=array([15,25,35,45,55,65,75,85,95,105])out_seq=array([25,45,65,85,105,125,145,165,185,205])in_se...
(10) #1 dummy_dataset = keras.preprocessing.timeseries_dataset_from_array( data=int_sequence[:-3], #2 targets=int_sequence[3:], #3 sequence_length=3, #4 batch_size=2, #5 ) for inputs, targets in dummy_dataset: for i in range(inputs.shape[0]): print([int(x) for x in ...
For example, I only want some basic windowing, I found more help setting this up in the keras preprocessing docs here https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/timeseries_dataset_from_array than I did in this help page. While this page demonstrates many potential use...
1.1、尺寸单位