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use target dim to reshape lags
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@@ -549,7 +549,7 @@ class TransformerTempFlowPredictionNetwork(TransformerTempFlowTrainingNetwork):
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lags_scaled = lags / repeated_scale.unsqueeze(-1)
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input_lags = lags_scaled.reshape(
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shape=(-1, 1, prod(self.target_shape) * len(self.lags_seq))
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(-1, 1, len(self.lags_seq) * self.target_dim)
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)
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# (batch_size, target_dim, embed_dim)
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