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@ -562,8 +562,9 @@ class PostTrainingQuantization(object):
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for var_name in self._quantized_act_var_name:
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var_tensor = _load_variable_data(self._scope, var_name)
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var_tensor = var_tensor.ravel()
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save_path = os.path.join(self._cache_dir,
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var_name + "_" + str(iter) + ".npy")
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save_path = os.path.join(
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self._cache_dir,
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var_name.replace("/", ".") + "_" + str(iter) + ".npy")
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np.save(save_path, var_tensor)
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else:
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for var_name in self._quantized_act_var_name:
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@ -598,7 +599,7 @@ class PostTrainingQuantization(object):
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for var_name in self._quantized_act_var_name:
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sampling_data = []
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filenames = [f for f in os.listdir(self._cache_dir) \
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if re.match(var_name + '_[0-9]+.npy', f)]
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if re.match(var_name.replace("/", ".") + '_[0-9]+.npy', f)]
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for filename in filenames:
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file_path = os.path.join(self._cache_dir, filename)
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sampling_data.append(np.load(file_path))
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