149ec80539b903677c6c69fe52968867dd50c95f,VAEs/vq-vae/models/vq_vae.py,VectorQuantizerEMA,__init__,#VectorQuantizerEMA#,78

Before Change

		self.epsilon = epsilon

		with nn.parameter_scope(scope_name):
			self.embedding_weight = nn.parameter.get_parameter_or_create("W", shape=(self.num_embedding, self.embedding_dim),
			initializer=I.NormalInitializer(rng=self.rng), need_grad=True)

			self.ema_cluster_size = nn.parameter.get_parameter_or_create("ema_cluster_size", shape = (self.num_embedding,), 

After Change

		// with nn.parameter_scope(scope_name):
			// self.embedding_weight = nn.parameter.get_parameter_or_create("emb/W", shape=(self.num_embedding, self.embedding_dim),
			// initializer=I.NormalInitializer(rng=self.rng), need_grad=True)
		self.embedding_weight = nn.Variable.from_numpy_array(np.random.randn(self.num_embedding, self.embedding_dim))
		self.embedding_weight.need_grad = True
		self.ema_cluster_size = nn.Variable.from_numpy_array(np.zeros(self.num_embedding,))
		self.ema_cluster_size.need_grad = False
		self.ema_w = nn.Variable.from_numpy_array(np.random.randn(self.num_embedding, self.embedding_dim))
		self.ema_w.need_grad = True

			// self.ema_cluster_size = nn.parameter.get_parameter_or_create("ema_cluster_size", shape = (self.num_embedding,), 

Instances