From ba99237f1ab258e8f5eac0d01719e92751c9b2a3 Mon Sep 17 00:00:00 2001
From: Jules Laplace <julescarbon@gmail.com>
Date: Mon, 14 May 2018 23:27:16 +0200
Subject: okayyyyyyy

---
 gen-prime.sh | 2 +-
 model.py     | 5 +++--
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/gen-prime.sh b/gen-prime.sh
index 28c9ddf..19ef340 100755
--- a/gen-prime.sh
+++ b/gen-prime.sh
@@ -12,7 +12,7 @@ function gen_prime () {
   echo "___________________________________________________"
   echo ">> generating $exp_name"
   echo ""
-  python generate.py \
+  CUDA_LAUNCH_BLOCKING=1 python generate.py \
     --exp $exp_name --dataset $exp_name \
     --frame_sizes 8 2                   \
     --n_rnn 2 --dim 1024 --q_levels 256 \
diff --git a/model.py b/model.py
index bbbd6ea..ff35baa 100644
--- a/model.py
+++ b/model.py
@@ -378,7 +378,7 @@ class PrimedGenerator(Runner):
                 ratio = i / (n-1)
                 a = sub_sequence_a[:, j].float() * (1-ratio)
                 b = sub_sequence_b[:, j].float() * ratio
-                tmp_sub_sequence[:, j] = (a + b).long()
+                tmp_sub_sequence[:, j] = clamp(a + b, 0, q_levels).long()
 
             return tmp_sub_sequence
 
@@ -420,7 +420,8 @@ class PrimedGenerator(Runner):
                 print("ran rnn")
 
             print("at bottom frame")
-            sub_sequence = get_sub_sequence(i, bottom_frame_size)
+            # sub_sequence = get_sub_sequence(i, bottom_frame_size)
+            sub_sequence = sequences[:, i-bottom_frame_size : i]
 
             prev_samples = torch.autograd.Variable(
                 sub_sequence,
-- 
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