ValueError: in user code: ValueError: No gradients provided for any variable for Autoencoder Tensorflow

Question

I have the above code and I have the below error during my fit

ValueError: No gradients provided for any variable: ([‘dense_12/kernel:0’, ‘dense_12/bias:0’, ‘dense_13/kernel:0’, ‘dense_13/bias:0’],). Provided grads_and_vars is ((None, <tf.Variable ‘dense_12/kernel:0’ shape=(784, 2) dtype=float32>), (None, <tf.Variable ‘dense_12/bias:0’ shape=(2,) dtype=float32>), (None, <tf.Variable ‘dense_13/kernel:0’ shape=(2, 784) dtype=float32>), (None, <tf.Variable ‘dense_13/bias:0’ shape=(784,) dtype=float32>)).

I tried to change encoder and decoder and It didn’t solve the problem. I have an autoencoder problem that is why i used X_train and X_test dataset instead of y_train and y_test dataset.
How can I solve this error?
Thank you for your feedbacks!


class autoencoder(Model):
  def __init__(self, output_dim = 2): 
    super(autoencoder, self).__init__()
    self.output_dim = output_dim   
    self.encoder = tf.keras.Sequential([
      layers.Flatten(),
      layers.Dense(2, activation='relu')
    ])
    self.decoder = tf.keras.Sequential([
      layers.Dense(784, activation='relu')
     
    ])
  def encoder_call(self, inputs):
    inputs = Flatten()(inputs)
    return self.encoder(inputs) 
  def call(self, x, train = None):
    x = Flatten()(x)
    encoded = self.encoder(x)
    decoded = self.decoder(encoded)
    return tf.reshape(x,(-1,28,28)) 


model = autoencoder()
model.compile(optimizer='adam', loss=losses.MeanSquaredError())

model.fit(X_train, X_train,
                epochs=1,
                shuffle=True,
                validation_data=(X_test, X_test)) ```

Asked By: gülsümmm

||

Source

Answer 1

return tf.reshape(x,(-1,28,28))

it should be return tf.reshape(decoded,(-1,28,28))

Cause of error: your input x is first passed through a Flatten layer, then through encoder and decoder successively. Finally, call method returns reshaped version of x, but not the decoded. So, there is no possibility to build a computational graph and backpropagate through it.

Answered By: rajkumar_data

ValueError: in user code: ValueError: No gradients provided for any variable for Autoencoder Tensorflow

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