From d1683a406e19d70765b4f70466f1f07d48ebe201 Mon Sep 17 00:00:00 2001 From: "Dr. Kashif Rasul" Date: Sat, 4 Jan 2020 15:53:15 +0100 Subject: [PATCH] fix repeated states --- pts/model/deepvar/deepvar_network.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pts/model/deepvar/deepvar_network.py b/pts/model/deepvar/deepvar_network.py index cb6051a..37cc7f3 100644 --- a/pts/model/deepvar/deepvar_network.py +++ b/pts/model/deepvar/deepvar_network.py @@ -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 = []