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| author | Jules Laplace <julescarbon@gmail.com> | 2018-05-15 00:31:01 +0200 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2018-05-15 00:31:01 +0200 |
| commit | 4ac07532efa4baa97ac96c29664134c3e45c4817 (patch) | |
| tree | c8f09a0e8b3d3e0d458ed74aed3587a87f16803f | |
| parent | 367aaaa101293c0da641a82b2a2e3a03ce09251f (diff) | |
lol typo
| -rw-r--r-- | model.py | 6 |
1 files changed, 3 insertions, 3 deletions
@@ -370,7 +370,7 @@ class PrimedGenerator(Runner): tmp_sub_sequence = tmp_sequences[:, i-n : i] # tmp/output for j in range(n): - ratio = j / (n-1) + ratio = j / (bottom_frame_size-1) a = sub_sequence_a[:, j].float() * (1-ratio) b = sub_sequence_b[:, j].float() * ratio tmp_sub_sequence[:, j] = torch.clamp(a + b, 1, q_levels-1).long() @@ -413,8 +413,8 @@ class PrimedGenerator(Runner): rnn, prev_samples, upper_tier_conditioning ) - # sub_sequence = get_sub_sequence(i, bottom_frame_size) - sub_sequence = out_sequences[:, i-bottom_frame_size : i] + sub_sequence = get_sub_sequence(i, bottom_frame_size) + # sub_sequence = out_sequences[:, i-bottom_frame_size : i] prev_samples = torch.autograd.Variable( sub_sequence, |
