Layer "model_3" expects 1 input(s), but it received 3 input tensors.

This error message indicates that the layer "model_3" expects only one input tensor, but it received three input tensors instead.

To resolve this error, you can check the input shape of each tensor and make sure they match the expected input shape of the layer. You can also check the model architecture and ensure that the tensors are being passed to the correct layer.

If you are using a functional API in Keras, you may need to use the "Concatenate" layer to merge multiple tensors into a single one before passing it to the "model_3" layer.

相关问题

Q = tf.keras.layers.Dense(units, activation=tf.nn.relu)(Q) ValueError: Layer dense expects 1 inputs, but it received 3 input tensors. Inputs received: [<tf.Tensor: shape=(), dtype=int32, numpy=100>,

这个错误通常是因为您在调用 `tf.keras.layers.Dense` 函数时传入的参数不正确。具体来说，您传入的输入张量的维度可能不匹配。

请检查您的代码，确保您传入 `tf.keras.layers.Dense` 函数的输入张量的维度与您期望的维度一致。您可以尝试使用 `tf.keras.Input` 函数来创建输入张量，例如：

inputs = tf.keras.Input(shape=(input_shape,))
Q = tf.keras.layers.Dense(units, activation=tf.nn.relu)(inputs)

这里，`input_shape` 是您期望的输入张量的形状。这样，您将确保输入张量的维度正确，并且可以避免传递不必要的参数。

Layer "dense" expects 1 input(s), but it received 3 input tensors. Inputs received: [<tf.Tensor 'Placeholder:0' shape=(None, 4, 4) dtype=float32>, <tf.Tensor 'Placeholder_1:0' shape=(None, 4) dtype=float32>, <tf.Tensor 'Placeholder_2:0' shape=(None, 4) dtype=float32>]

这个错误提示表明在你尝试调用一个名为“dense”的层时，你给它提供的输入张量数量与该层期望的输入张量数量不匹配。该层期望1个输入张量，但你提供了3个。这通常是由于你在构建模型时有误，例如你可能不小心将多个输入张量传递给了该层。你需要检查一下你的模型代码，确保每一层的输入输出张量数量与它们之间的连接方式正确无误。