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Embedding loss backwards? about vqvae HOT 2 OPEN

mishalaskin avatar mishalaskin commented on August 20, 2024 3
Embedding loss backwards?

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Comments (2)

lianyixin avatar lianyixin commented on August 20, 2024 10

original tf code is the same as in the paper:
e_latent_loss = tf.reduce_mean((tf.stop_gradient(quantized) - inputs) ** 2)
q_latent_loss = tf.reduce_mean((quantized - tf.stop_gradient(inputs)) ** 2)
loss = q_latent_loss + self._commitment_cost * e_latent_loss

maybe is wrong here

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sakethbachu avatar sakethbachu commented on August 20, 2024

@eembees I also think the same

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