# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import paddle from ..base_observer import BaseObserver from ..factory import ObserverFactory class AbsmaxObserver(ObserverFactory): r""" It collects maximum absolute values of target tensor. Args: bit_length(int, optional): Number of bits to represent an quantized integer in binary. dtype(str, optional): The data type of input tensor. name (str, optional): This parameter is used by developers to print debugging information. \ For details, please refer to :ref:`api_guide_Name`. Default is None. Examples: .. code-block:: python from paddle.quantization import QuantConfig from paddle.quantization.quanters import FakeQuanterWithAbsMaxObserver quanter = FakeQuanterWithAbsMaxObserver(moving_rate=0.99) q_config = QuantConfig(activation=quanter, weight=quanter) """ def __init__(self, quant_bits=8): super(AbsmaxObserver, self).__init__(quant_bits=quant_bits) def _get_class(self): return AbsmaxObserverLayer class AbsmaxObserverLayer(BaseObserver): """ Per-tensor abs max quantizer. """ INIT_ABS_MAX = 1e-7 def __init__(self, layer, quant_bits=8): super(AbsmaxObserverLayer, self).__init__() self._quant_bits = quant_bits self.abs_max_val = paddle.to_tensor(AbsmaxObserverLayer.INIT_ABS_MAX) def forward(self, input): abs_max_val = paddle.max(paddle.abs(input)) self.abs_max_val = paddle.maximum(abs_max_val, self.abs_max_val) return input def cal_thresholds(self): self.thresholds = self.abs_max_val def bit_length(self): return self._quant_bits def quant_axis(self): return -1 def scales(self): return self.abs_max_val def zero_points(self): return None