You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In the following code portion (8th code block of the notebook):
`# Optimization process.
def run_optimization(x):
# Wrap computation inside a GradientTape for automatic differentiation.
with tf.GradientTape() as g:
reconstructed_image = decoder(encoder(x))
loss = mean_square(reconstructed_image, x)
# Variables to update, i.e. trainable variables.
trainable_variables = weights.values() + biases.values()
# Compute gradients.
gradients = g.gradient(loss, trainable_variables)
# Update W and b following gradients.
optimizer.apply_gradients(zip(gradients, trainable_variables))
return loss`
results to me in an error due to the impossibility of summing two python dict_values. I personally solved the issue by converting both dict_values to lists:
Referring to the notebook:
https://github.com/aymericdamien/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/autoencoder.ipynb
In the following code portion (8th code block of the notebook):
`# Optimization process.
def run_optimization(x):
# Wrap computation inside a GradientTape for automatic differentiation.
with tf.GradientTape() as g:
reconstructed_image = decoder(encoder(x))
loss = mean_square(reconstructed_image, x)
the line:
trainable_variables = weights.values() + biases.values()
results to me in an error due to the impossibility of summing two python dict_values. I personally solved the issue by converting both dict_values to lists:
trainable_variables = list(weights.values()) + list(biases.values())
I hope my issue is of utility for this great repo! Thank you for the work
The text was updated successfully, but these errors were encountered: