Source code for pytorch_quantization.calib.max

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"""Calibrator that returns the absolute max of all collected tensors"""
from absl import logging
import torch

from pytorch_quantization.calib.calibrator import _Calibrator
from pytorch_quantization import utils as quant_utils

[docs]class MaxCalibrator(_Calibrator): """Max calibrator, tracks the maximum value globally Args: calib_desc: A MaxCalibDescriptor. num_bits: An integer. Number of bits of quantization. axis: A tuple. see QuantDescriptor. unsigned: A boolean. using unsigned quantization. Readonly Properties: amaxs: A list of amax. Numpy array is saved as it is likely to be used for some plot. """ def __init__(self, num_bits, axis, unsigned, track_amax=False): super(MaxCalibrator, self).__init__(num_bits, axis, unsigned) self._track_amax = track_amax if self._track_amax: self._amaxs = [] # shall we have a better name? self._calib_amax = None # pylint:disable=missing-docstring @property def amaxs(self): return self._amaxs # pylint:enable=missing-docstring
[docs] def collect(self, x): """Tracks the absolute max of all tensors Args: x: A tensor Raises: RuntimeError: If amax shape changes """ if torch.min(x) < 0.: logging.log_first_n( logging.INFO, ("Calibrator encountered negative values. It shouldn't happen after ReLU. " "Make sure this is the right tensor to calibrate."), 1) x = x.abs() # Swap axis to reduce. axis = self._axis if isinstance(self._axis, (list, tuple)) else [self._axis] reduce_axis = [] for i in range(x.dim()): if not i in axis: reduce_axis.append(i) local_amax = quant_utils.reduce_amax(x, axis=reduce_axis).detach() if self._calib_amax is None: self._calib_amax = local_amax else: if local_amax.shape != self._calib_amax.shape: raise RuntimeError("amax shape changed!") self._calib_amax.copy_(torch.max(self._calib_amax, local_amax).data) if self._track_amax: self._amaxs.append(local_amax.cpu().numpy())
[docs] def reset(self): """Reset the collected absolute max""" self._calib_amax = None
[docs] def compute_amax(self): """Return the absolute max of all tensors collected""" return self._calib_amax
# pylint:disable=missing-docstring def __str__(self): s = "MaxCalibrator(" s += "track_amax={_track_amax}" s += ")" return s.format(**self.__dict__) def __repr__(self): s = "MaxCalibrator(" s += super(MaxCalibrator, self).__repr__() s += " calib_amax={_calib_amax}" s += " track_amax={_track_amax}" if self._track_amax: s += " amaxs={_amaxs}" s += ")" return s.format(**self.__dict__)
# pylint:enable=missing-docstring