From cfd49acc268e687868cd8b0f724a7c97f3801a39 Mon Sep 17 00:00:00 2001
From: XGZhang <46363693+XGZhang11@users.noreply.github.com>
Date: Tue, 10 Aug 2021 16:35:16 +0800
Subject: [PATCH] fix a quantization bug (#34647)

---
 .../contrib/slim/quantization/post_training_quantization.py     | 1 +
 .../paddle/fluid/contrib/slim/quantization/quantization_pass.py | 2 ++
 2 files changed, 3 insertions(+)

diff --git a/python/paddle/fluid/contrib/slim/quantization/post_training_quantization.py b/python/paddle/fluid/contrib/slim/quantization/post_training_quantization.py
index 5996e752c8c..06f3f5f3afa 100644
--- a/python/paddle/fluid/contrib/slim/quantization/post_training_quantization.py
+++ b/python/paddle/fluid/contrib/slim/quantization/post_training_quantization.py
@@ -578,6 +578,7 @@ class PostTrainingQuantization(object):
             var_tensor = _load_variable_data(self._scope, var_name)
             var_tensor = var_tensor.flatten()
             abs_max_value = float(np.max(np.abs(var_tensor)))
+            abs_max_value = 1e-8 if abs_max_value == 0.0 else abs_max_value
             s = 0.3
             if var_name not in self._best_mse_loss:
                 self._best_mse_loss[var_name] = float('inf')
diff --git a/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py b/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py
index b3b12a477e2..9917730daa5 100644
--- a/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py
+++ b/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py
@@ -1312,6 +1312,7 @@ class QuantizationFreezePass(object):
                 assert self._is_float(
                     scale_v), 'The scale of parameter %s is not a float.' % (
                         original_var_name)
+                scale_v = 1e-8 if scale_v == 0.0 else scale_v
                 max_range *= param_range / scale_v
             else:
                 max_range *= act_range
@@ -1413,6 +1414,7 @@ class QuantizationFreezePass(object):
                     x[:, i] = _clip(x[:, i], s)
                     x[:, i] = np.round(x[:, i] / s * bnt)
         else:
+            scale = 1e-8 if scale == 0.0 else scale
             x = _clip(x, scale)
             x = np.round(x / scale * bnt)
         return x
-- 
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