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@@ -121,12 +121,9 @@ class NBEATSEstimator(PTSEstimator):
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else:
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return new_value
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# here we do only a simple operation to convert the input data to a form
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# Here we do only a simple operation to convert the input data to a form
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# that can be digested by our model by only splitting the target in two, a
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# conditioning part and a to-predict part, for each training example.
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# for a more complex transformation example, see the `gluonts.model.deepar`
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# transformation that includes time features, age feature, observed values
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# indicator, ...
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def create_transformation(self) -> Transformation:
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return Chain(
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[
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@@ -210,7 +210,7 @@ class NBEATSNetwork(nn.Module):
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self.prediction_length = prediction_length
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self.context_length = context_length
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self.net_blocks: nn.ModuleList[NBEATSBlock] = nn.ModuleList()
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self.net_blocks = nn.ModuleList()
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for stack_id in range(num_stacks):
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for block_id in range(num_blocks[stack_id]):
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if self.stack_types[stack_id] == "G":
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