Source code for mindspore.ops.silent_check

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"""Silent Check."""
import os

from mindspore.common.tensor import Tensor
from mindspore.common.parameter import Parameter
import mindspore.common.dtype as mstype

from . import operations
from .operations._inner_ops import _MirrorSilentCheck
from .operations import RmsNorm as OriginRmsNorm
from .operations import LayerNorm as OriginLayerNorm
from .primitive import Primitive


NPU_ASD_ENABLE = 'NPU_ASD_ENABLE'


[docs]class ASDBase: """ ASD Base Class. """ _index = 0 __ms_class__ = True def __init__(self, cls, *args, **kwargs): self.op = cls(*args, **kwargs) self.check_op = _MirrorSilentCheck() self._suffix = "ASD_" + cls.__name__ primitive_attr = dir(Primitive) self._op_attr_dict = { name for name in primitive_attr if not name.startswith("_")} self.enable_check = os.environ.get(NPU_ASD_ENABLE) == "1" def __getattr__(self, name): def method_wrapper(*args, **kwargs): out = getattr(self.op, name)(*args, **kwargs) if out is self.op: return self return out if name in self._op_attr_dict: if callable(getattr(self.op, name)): return method_wrapper if hasattr(self.op, name): return getattr(self.op, name) return super().__getattr__(self, name) def __repr__(self): return self.op.__repr__()
[docs] def generate_params(self): """ Generate check params. """ pre_val = Parameter(Tensor(0, mstype.float32), name=f"{self._suffix}_pre_val_{self._index}", requires_grad=False) min_val = Parameter(Tensor(0, mstype.float32), name=f"{self._suffix}_min_val_{self._index}", requires_grad=False) max_val = Parameter(Tensor(0, mstype.float32), name=f"{self._suffix}_max_val_{self._index}", requires_grad=False) cnt = Parameter(Tensor(0, mstype.int32), name=f"{self._suffix}_cnt_{self._index}", requires_grad=False) ASDBase._index += 1 return pre_val, min_val, max_val, cnt
class RmsNormASD(ASDBase): """ RmsNorm with ASD. """ def __init__(self, *args, **kwargs): super().__init__(OriginRmsNorm, *args, **kwargs) self.pre_val, self.min_val, self.max_val, self.cnt = self.generate_params() def __call__(self, input_x, gamma): if self.enable_check: input_x = self.check_op( input_x, self.pre_val, self.min_val, self.max_val, self.cnt, None) self.cnt += 1 return self.op(input_x, gamma) class LayerNormASD(ASDBase): """ LayerNorm with ASD. """ def __init__(self, *args, **kwargs): super().__init__(OriginLayerNorm, *args, **kwargs) self.pre_val, self.min_val, self.max_val, self.cnt = self.generate_params() def __call__(self, input_x, gamma, beta): if self.enable_check: input_x = self.check_op( input_x, self.pre_val, self.min_val, self.max_val, self.cnt, None) self.cnt += 1 return self.op(input_x, gamma, beta) def _silent_check(): if os.environ.get(NPU_ASD_ENABLE) == "1": operations.LayerNorm = LayerNormASD operations.RmsNorm = RmsNormASD