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perf: add OpSampler to support multiple ops

pull/1064/head
gaotingquan 2021-07-26 07:36:54 +00:00
parent ae768d6aee
commit b578662b32
2 changed files with 77 additions and 33 deletions
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4
ppcls/data/preprocess/__init__.py
View File

@ -29,7 +29,7 @@ from ppcls.data.preprocess.ops.operators import NormalizeImage
from ppcls.data.preprocess.ops.operators import ToCHWImage
from ppcls.data.preprocess.ops.operators import AugMix
from ppcls.data.preprocess.batch_ops.batch_operators import MixupOperator, CutmixOperator, FmixOperator
from ppcls.data.preprocess.batch_ops.batch_operators import MixupOperator, CutmixOperator, OpSampler, FmixOperator
import six
import numpy as np
@ -45,6 +45,7 @@ def transform(data, ops=[]):
class AutoAugment(RawImageNetPolicy):
""" ImageNetPolicy wrapper to auto fit different img types """
def __init__(self, *args, **kwargs):
if six.PY2:
super(AutoAugment, self).__init__(*args, **kwargs)
@ -69,6 +70,7 @@ class AutoAugment(RawImageNetPolicy):
class RandAugment(RawRandAugment):
""" RandAugment wrapper to auto fit different img types """
def __init__(self, *args, **kwargs):
if six.PY2:
super(RandAugment, self).__init__(*args, **kwargs)

106
ppcls/data/preprocess/batch_ops/batch_operators.py
View File

@ -16,8 +16,11 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import random
import numpy as np
from ppcls.utils import logger
from ppcls.data.preprocess.ops.fmix import sample_mask
@ -46,37 +49,50 @@ class BatchOperator(object):
class MixupOperator(BatchOperator):
"""Mixup and Cutmix operator"""
""" Mixup operator """
def __init__(self,
mixup_alpha: float=1.,
cutmix_alpha: float=0.,
switch_prob: float=0.5):
def __init__(self, alpha: float=1.):
"""Build Mixup operator
Args:
mixup_alpha (float, optional): The parameter alpha of mixup, mixup is active if > 0. Defaults to 1..
cutmix_alpha (float, optional): The parameter alpha of cutmix, cutmix is active if > 0. Defaults to 0..
switch_prob (float, optional): The probability of switching to cutmix instead of mixup when both are active. Defaults to 0.5.
alpha (float, optional): The parameter alpha of mixup. Defaults to 1..
Raises:
Exception: The value of parameters are illegal.
Exception: The value of parameter is illegal.
"""
if mixup_alpha <= 0 and cutmix_alpha <= 0:
if alpha <= 0:
raise Exception(
f"At least one of parameter alpha of Mixup and Cutmix is greater than 0. mixup_alpha: {mixup_alpha}, cutmix_alpha: {cutmix_alpha}"
f"Parameter \"alpha\" of Mixup should be greater than 0. \"alpha\": {alpha}."
)
self._mixup_alpha = mixup_alpha
self._cutmix_alpha = cutmix_alpha
self._switch_prob = switch_prob
self._alpha = alpha
def _mixup(self, imgs, labels, bs):
def __call__(self, batch):
imgs, labels, bs = self._unpack(batch)
idx = np.random.permutation(bs)
lam = np.random.beta(self._mixup_alpha, self._mixup_alpha)
lam = np.random.beta(self._alpha, self._alpha)
lams = np.array([lam] * bs, dtype=np.float32)
imgs = lam * imgs + (1 - lam) * imgs[idx]
return list(zip(imgs, labels, labels[idx], lams))
class CutmixOperator(BatchOperator):
""" Cutmix operator """
def __init__(self, alpha=0.2):
"""Build Cutmix operator
Args:
alpha (float, optional): The parameter alpha of cutmix. Defaults to 0.2.
Raises:
Exception: The value of parameter is illegal.
"""
if alpha <= 0:
raise Exception(
f"Parameter \"alpha\" of Cutmix should be greater than 0. \"alpha\": {alpha}."
)
self._alpha = alpha
def _rand_bbox(self, size, lam):
""" _rand_bbox """
w = size[2]
@ -96,9 +112,10 @@ class MixupOperator(BatchOperator):
return bbx1, bby1, bbx2, bby2
def _cutmix(self, imgs, labels, bs):
def __call__(self, batch):
imgs, labels, bs = self._unpack(batch)
idx = np.random.permutation(bs)
lam = np.random.beta(self._cutmix_alpha, self._cutmix_alpha)
lam = np.random.beta(self._alpha, self._alpha)
bbx1, bby1, bbx2, bby2 = self._rand_bbox(imgs.shape, lam)
imgs[:, :, bbx1:bbx2, bby1:bby2] = imgs[idx, :, bbx1:bbx2, bby1:bby2]
@ -107,20 +124,6 @@ class MixupOperator(BatchOperator):
lams = np.array([lam] * bs, dtype=np.float32)
return list(zip(imgs, labels, labels[idx], lams))
def __call__(self, batch):
imgs, labels, bs = self._unpack(batch)
if np.random.rand() < self._switch_prob:
return self._cutmix(imgs, labels, bs)
else:
return self._mixup(imgs, labels, bs)
class CutmixOperator(BatchOperator):
def __init__(self, **kwargs):
raise Exception(
f"\"CutmixOperator\" has been deprecated. Please use MixupOperator with \"cutmix_alpha\" and \"switch_prob\" to enable Cutmix. Refor to doc for details."
)
class FmixOperator(BatchOperator):
""" Fmix operator """
@ -139,3 +142,42 @@ class FmixOperator(BatchOperator):
size, self._max_soft, self._reformulate)
imgs = mask * imgs + (1 - mask) * imgs[idx]
return list(zip(imgs, labels, labels[idx], [lam] * bs))
class OpSampler(object):
""" Sample a operator from """
def __init__(self, **op_dict):
"""Build OpSampler
Raises:
Exception: The parameter \"prob\" of operator(s) are be set error.
"""
if len(op_dict) < 1:
msg = f"ConfigWarning: No operator in \"OpSampler\". \"OpSampler\" has been skipped."
self.ops = {}
total_prob = 0
for op_name in op_dict:
param = op_dict[op_name]
if "prob" not in param:
msg = f"ConfigWarning: Parameter \"prob\" should be set when use operator in \"OpSampler\". The operator \"{op_name}\"'s prob has been set \"0\"."
logger.warning(msg)
prob = param.pop("prob", 0)
total_prob += prob
op = eval(op_name)(**param)
self.ops.update({op: prob})
if total_prob > 1:
msg = f"ConfigError: The total prob of operators in \"OpSampler\" should be less 1."
logger.error(msg)
raise Exception(msg)
# add "None Op" when total_prob < 1, "None Op" do nothing
self.ops[None] = 1 - total_prob
def __call__(self, batch):
op = random.choices(
list(self.ops.keys()), weights=list(self.ops.values()), k=1)[0]
# return batch directly when None Op
return op(batch) if op else batch