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fix repeated states

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This commit is contained in:
Dr. Kashif Rasul
2020-01-04 15:53:15 +01:00
parent c1be3fa5a7
commit d1683a406e
1 changed files with 4 additions and 4 deletions
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pts/model/deepvar/deepvar_network.py
+4 -4
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@@ -457,8 +457,8 @@ class DeepVARPredictionNetwork(DeepVARTrainingNetwork):
prediction_length, target_dim).
"""
def repeat(tensor):
return tensor.repeat_interleave(repeats=self.num_parallel_samples, dim=0)
def repeat(tensor, dim=0):
return tensor.repeat_interleave(repeats=self.num_parallel_samples, dim=dim)
# blows-up the dimension of each tensor to
# batch_size * self.num_sample_paths for increasing parallelism
@@ -469,9 +469,9 @@ class DeepVARPredictionNetwork(DeepVARTrainingNetwork):
# slight difference for GPVAR and DeepVAR, in GPVAR, its a list
if self.cell_type == "LSTM":
repeated_states = [repeat(s) for s in begin_states]
repeated_states = [repeat(s, dim=1) for s in begin_states]
else:
repeated_states = repeat(begin_states)
repeated_states = repeat(begin_states, dim=1)
future_samples = []