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[Typing][C-121,C-122,C-123,C-124] Add type annotations for python/paddle/quantization/{base_observer,factory,ptq,qat}.py #66693

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Jul 31, 2024
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[Typing][C-121,C-122,C-123,C-124] Add type annotations for python/paddle/quantization/{base_observer,factory,ptq,qat}.py #66693

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enkilee Jul 29, 2024
e93dafa
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enkilee Jul 29, 2024
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enkilee Jul 31, 2024
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5 changes: 3 additions & 2 deletions python/paddle/quantization/base_observer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
# 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.
from __future__ import annotations

import abc

Expand All @@ -24,9 +25,9 @@ class BaseObserver(BaseQuanter, metaclass=abc.ABCMeta):
and implement abstract methods.
"""

def __init__(self):
def __init__(self) -> None:
super().__init__()

@abc.abstractmethod
def cal_thresholds(self):
def cal_thresholds(self) -> None:
pass
19 changes: 12 additions & 7 deletions python/paddle/quantization/factory.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,19 +11,21 @@
# 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.

from __future__ import annotations

import abc
import inspect
from functools import partial
from typing import TYPE_CHECKING, Any, Callable

from paddle.nn import Layer
if TYPE_CHECKING:
from paddle.nn import Layer

from .base_quanter import BaseQuanter
from .base_quanter import BaseQuanter


class ClassWithArguments(metaclass=abc.ABCMeta):
def __init__(self, *args, **kwargs):
def __init__(self, *args: Any, **kwargs: Any) -> None:
self._args = args
self._kwargs = kwargs

Expand Down Expand Up @@ -55,7 +57,7 @@ class QuanterFactory(ClassWithArguments):
the arguments used to create quanter instance.
"""

def __init__(self, *args, **kwargs):
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
self.partial_class = None

Expand All @@ -73,7 +75,9 @@ def _instance(self, layer: Layer) -> BaseQuanter:
ObserverFactory = QuanterFactory


def quanter(class_name):
def quanter(
class_name: str,
) -> Callable[[type[BaseQuanter]], type[BaseQuanter]]:
r"""
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2024-07-29 18:07:11 ----------------Check results--------------------
2024-07-29 18:07:11 paddle.quantization.quanter:1
2024-07-29 18:07:11 <string>:10:11: error: Name "CustomizedQuanter" is not defined  [name-defined]
2024-07-29 18:07:11 <string>:11:35: error: Argument "activation" to "QuantConfig" has incompatible type "Callable[[str], BaseQuanter]"; expected "QuanterFactory"  [arg-type]
2024-07-29 18:07:11 <string>:11:51: error: Argument "weight" to "QuantConfig" has incompatible type "Callable[[str], BaseQuanter]"; expected "QuanterFactory"  [arg-type]
2024-07-29 18:07:11 Found 3 errors in 1 file (checked 1 source file)
2024-07-29 18:07:11 
2024-07-29 18:07:11 
2024-07-29 18:07:11 >>> Mistakes found in type checking!
2024-07-29 18:07:11 >>> Please recheck the type annotations. Run `tools/type_checking.py` to check the typing issues:
2024-07-29 18:07:11 > python tools/type_checking.py paddle.quantization.quanter
2024-07-29 18:07:11 ----------------End of the Check--------------------

这示例代码看样子本来就不能跑，直接在最前面加个 # type: ignore 吧，在 # doctest: +SKIP('need 2 file to run example') 下一行单独写一行

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@enkilee enkilee Jul 31, 2024 •
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收到，我看其他都是加在 # doctest: +SKIP('xxxxxxx') 上面来着？

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# type: ignore 和 # doctest: +SKIP('xxxxxxx') 互不影响，前者是应对 type checking ，后者是应对 example code running check ～ 注意一下，针对整段代码，都需要独占一行 ～

Annotation to declare a factory class for quanter.

Expand All @@ -83,6 +87,7 @@ def quanter(class_name):
Examples:
.. code-block:: python

>>> # type: ignore
>>> # doctest: +SKIP('need 2 file to run example')
>>> # Given codes in ./customized_quanter.py
>>> from paddle.quantization import quanter
Expand All @@ -102,7 +107,7 @@ def quanter(class_name):

"""

def wrapper(target_class):
def wrapper(target_class: type[BaseQuanter]) -> type[BaseQuanter]:
init_function_str = f"""
def init_function(self, *args, **kwargs):
super(type(self), self).__init__(*args, **kwargs)
Expand Down
13 changes: 9 additions & 4 deletions python/paddle/quantization/ptq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,22 +11,27 @@
# 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.
from __future__ import annotations

import copy
from typing import TYPE_CHECKING

from paddle.distributed import fleet
from paddle.nn import Layer

from .config import QuantConfig
from .quantize import Quantization

if TYPE_CHECKING:
from paddle.nn import Layer

from .config import QuantConfig


class PTQ(Quantization):
"""
Applying post training quantization to the model.
"""

def __init__(self, config: QuantConfig):
def __init__(self, config: QuantConfig) -> None:
super().__init__(config)

def _is_parallel_training(self):
Expand All @@ -38,7 +43,7 @@ def _is_parallel_training(self):
except Exception: # fleet is not initialized
return False

def quantize(self, model: Layer, inplace=False):
def quantize(self, model: Layer, inplace: bool = False) -> Layer:
r"""
Create a model for post-training quantization.

Expand Down
14 changes: 9 additions & 5 deletions python/paddle/quantization/qat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,14 +11,18 @@
# 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.
from __future__ import annotations

import copy
from typing import TYPE_CHECKING

from paddle.nn import Layer

from .config import QuantConfig
from .quantize import Quantization

if TYPE_CHECKING:
from paddle.nn import Layer

from .config import QuantConfig


class QAT(Quantization):
r"""
Expand All @@ -36,10 +40,10 @@ class QAT(Quantization):
>>> qat = QAT(q_config)
"""

def __init__(self, config: QuantConfig):
def __init__(self, config: QuantConfig) -> None:
super().__init__(config)

def quantize(self, model: Layer, inplace=False):
def quantize(self, model: Layer, inplace: bool = False) -> Layer:
r"""
Create a model for quantization-aware training.

Expand Down