From f762fef4285837f60a09e48848d01fc786d4eb27 Mon Sep 17 00:00:00 2001
From: Guy Jacob <guy.jacob@intel.com>
Date: Wed, 31 Jul 2019 12:48:57 +0300
Subject: [PATCH] Fix crash in dynamic post-train quant (caused by commit
69b1452)
---
distiller/quantization/range_linear.py | 5 ++++-
1 file changed, 4 insertions(+), 1 deletion(-)
diff --git a/distiller/quantization/range_linear.py b/distiller/quantization/range_linear.py
index 343f887..f31c945 100644
--- a/distiller/quantization/range_linear.py
+++ b/distiller/quantization/range_linear.py
@@ -982,7 +982,6 @@ class PostTrainLinearQuantizer(Quantizer):
self.adjacency_map = summary_graph.adjacency_map(dedicated_modules_only=False)
if not self.model_activation_stats:
- msglogger.info("No activation stats - skipping optimizations for modules followed by Relu/Tanh/Sigmoid")
return
# Update the activation stats to reflect BN folding
@@ -1005,6 +1004,10 @@ class PostTrainLinearQuantizer(Quantizer):
# Now we look for certain "fusions" of layers and activations
# We modify stats to make sure we quantize only the ranges relevant to the activation function
# By doing so we reduce quantization error while still keeping all
+ if not self.model_activation_stats:
+ msglogger.info("No activation stats - skipping optimizations for modules followed by Relu/Tanh/Sigmoid")
+ return
+
msglogger.info('Optimizing output statistics for modules followed by ReLU/Tanh/Sigmoid')
named_modules = OrderedDict(self.model.named_modules())
--
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