From 6fb0fed58c90f14e604650e0817077b510a42c63 Mon Sep 17 00:00:00 2001
From: Neta Zmora <neta.zmora@intel.com>
Date: Sun, 25 Nov 2018 12:50:17 +0200
Subject: [PATCH] Activation statistics: fix computation of Channel-wise APoZ
Instead of returning the average-percentage-of-zeros, we returned the
average-percentage-of-non-zeros.
So inverted the results, and also multiplied by 100, because the name
of the statistic has "percentage" not "fraction" (not very important,
but still...)
---
distiller/utils.py | 2 +-
tests/test_basic.py | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/distiller/utils.py b/distiller/utils.py
index cb000b3..29e8bde 100755
--- a/distiller/utils.py
+++ b/distiller/utils.py
@@ -395,7 +395,7 @@ def activation_channels_apoz(activation):
featuremap_apoz_mat = activation.abs().gt(0).sum(dim=1).float() / activation.size(1) # batch x 1
else:
raise ValueError("activation_channels_apoz: Unsupported shape: ".format(activation.shape))
- return featuremap_apoz_mat.mean(dim=0).cpu()
+ return 100 - featuremap_apoz_mat.mean(dim=0).mul(100).cpu()
def log_training_progress(stats_dict, params_dict, epoch, steps_completed, total_steps, log_freq, loggers):
diff --git a/tests/test_basic.py b/tests/test_basic.py
index 5d57a35..942f8eb 100755
--- a/tests/test_basic.py
+++ b/tests/test_basic.py
@@ -66,7 +66,7 @@ def test_activations():
[7., 0., 8.],
[0., 9., 0.]]]])
assert all(distiller.activation_channels_l1(x) == torch.tensor([21/2, 45/2]))
- assert all(distiller.activation_channels_apoz(x) == torch.tensor([6/18, 9/18]))
+ assert all(distiller.activation_channels_apoz(x) == torch.tensor([100*(6+6)/(9+9), 100*(4+5)/(9+9)]))
assert all(distiller.activation_channels_means(x) == torch.tensor([21/18, 45/18]))
--
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