From 34e5d20f181df5e9d928bc6ba51d3d17e4ce4490 Mon Sep 17 00:00:00 2001
From: Guy Jacob <guy.jacob@intel.com>
Date: Tue, 14 May 2019 11:17:38 +0300
Subject: [PATCH] Post train quant - warn instead of exit when dynamic quant
not supported
---
distiller/quantization/range_linear.py | 27 +++++++++++++++++---------
1 file changed, 18 insertions(+), 9 deletions(-)
diff --git a/distiller/quantization/range_linear.py b/distiller/quantization/range_linear.py
index 6a24304..67cd85c 100644
--- a/distiller/quantization/range_linear.py
+++ b/distiller/quantization/range_linear.py
@@ -511,6 +511,10 @@ class RangeLinearQuantParamLayerWrapper(RangeLinearQuantWrapper):
return tmpstr
+class NoStatsError(NotImplementedError):
+ pass
+
+
class RangeLinearQuantConcatWrapper(RangeLinearQuantWrapper):
def __init__(self, wrapped_module, num_bits_acts, mode=LinearQuantMode.SYMMETRIC, clip_acts=ClipMode.NONE,
activation_stats=None, clip_n_stds=None):
@@ -518,8 +522,8 @@ class RangeLinearQuantConcatWrapper(RangeLinearQuantWrapper):
raise ValueError(self.__class__.__name__ + ' can only wrap distiller.modules.Concat modules')
if not activation_stats:
- raise ValueError(self.__class__.__name__ +
- ' must get activation stats, dynamic quantization not supported')
+ raise NoStatsError(self.__class__.__name__ +
+ ' must get activation stats, dynamic quantization not supported')
super(RangeLinearQuantConcatWrapper, self).__init__(wrapped_module, num_bits_acts, mode=mode,
clip_acts=clip_acts, activation_stats=activation_stats,
@@ -564,8 +568,8 @@ class RangeLinearQuantEltwiseAddWrapper(RangeLinearQuantWrapper):
raise ValueError(self.__class__.__name__ + ' can only wrap distiller.modules.EltwiseAdd modules')
if not activation_stats:
- raise ValueError(self.__class__.__name__ +
- ' must get activation stats, dynamic quantization not supported')
+ raise NoStatsError(self.__class__.__name__ +
+ ' must get activation stats, dynamic quantization not supported')
super(RangeLinearQuantEltwiseAddWrapper, self).__init__(wrapped_module, num_bits_acts, mode=mode,
clip_acts=clip_acts, activation_stats=activation_stats,
@@ -612,8 +616,8 @@ class RangeLinearQuantEltwiseMultWrapper(RangeLinearQuantWrapper):
raise ValueError(self.__class__.__name__ + ' can only wrap distiller.modules.EltwiseMult modules')
if not activation_stats:
- raise ValueError(self.__class__.__name__ +
- ' must get activation stats, dynamic quantization not supported')
+ raise NoStatsError(self.__class__.__name__ +
+ ' must get activation stats, dynamic quantization not supported')
super(RangeLinearQuantEltwiseMultWrapper, self).__init__(wrapped_module, num_bits_acts, mode=mode,
clip_acts=clip_acts, activation_stats=activation_stats,
@@ -773,9 +777,14 @@ class PostTrainLinearQuantizer(Quantizer):
return FP16Wrapper(module)
norm_name = distiller.utils.normalize_module_name(name)
clip = self.clip_acts if norm_name not in self.no_clip_layers else ClipMode.NONE
- return wrapper_type(module, qbits_map[name].acts, mode=mode, clip_acts=clip,
- activation_stats=self.model_activation_stats.get(norm_name, None),
- clip_n_stds=clip_n_stds)
+ try:
+ return wrapper_type(module, qbits_map[name].acts, mode=mode, clip_acts=clip,
+ activation_stats=self.model_activation_stats.get(norm_name, None),
+ clip_n_stds=clip_n_stds)
+ except NoStatsError:
+ msglogger.warning('WARNING: {0} - quantization of {1} without stats not supported. '
+ 'Keeping the original FP32 module'.format(name, module.__class__.__name__))
+ return module
def replace_embedding(module, name, qbits_map, fp16=fp16):
if fp16:
--
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