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use memory queue if r is smaller than queue size
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@@ -395,7 +395,7 @@ class Decoder(nn.Module):
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return output, stop_token, self.attention_layer.attention_weights
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def _update_memory_queue(self, new_memory):
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if self.memory_size > 0:
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if self.memory_size > 0 and new_memory.shape[-1] < self.memory_size:
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self.memory_input = torch.cat([
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self.memory_input[:, self.r * self.memory_dim:].clone(),
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new_memory
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