【发布时间】:2023-10-17 06:43:01
【问题描述】:
【问题讨论】:
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请提供您目前拥有的代码以及您期望的清晰图表。
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@thushv89 添加了图表。我还不知道如何为顶层编写代码。底层只是一个简单的RNN层。
标签: tensorflow neural-network recurrent-neural-network
【问题讨论】:
标签: tensorflow neural-network recurrent-neural-network
这是你需要的吗?
from tensorflow.keras import layers, models
import tensorflow.keras.backend as K
inp = layers.Input(shape=(10, 5))
out = layers.LSTM(50, return_sequences=True)(inp)
out = layers.Lambda(lambda x: tf.stack(tf.unstack(out, axis=1)[::2], axis=1))(out)
out = layers.LSTM(50)(out)
out = layers.Dense(20)(out)
m = models.Model(inputs=inp, outputs=out)
m.summary()
您得到以下模型。你可以看到第二个 LSTM 在总共 10 个步骤中只得到了 5 个时间步(即前一层的每隔一个输出)
Model: "model_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_2 (InputLayer) [(None, 10, 5)] 0
_________________________________________________________________
lstm_2 (LSTM) (None, 10, 50) 11200
_________________________________________________________________
lambda_1 (Lambda) (None, 5, 50) 0
_________________________________________________________________
lstm_3 (LSTM) (None, 50) 20200
_________________________________________________________________
dense_1 (Dense) (None, 20) 1020
=================================================================
Total params: 32,420
Trainable params: 32,420
Non-trainable params: 0
【讨论】: