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!27176 remove api "GraphKernel" and prim "InplaceAssign" 

Merge pull request !27176 from DeshiChen/1203_gk_api
This commit is contained in:
i-robot 2021-12-06 07:00:38 +00:00 committed by Gitee
parent 9a727e5344 cc26b5394c
commit 1f768998bc
9 changed files with 3 additions and 297 deletions
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4
mindspore/nn/__init__.py
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@ -21,7 +21,7 @@ from . import layer, loss, optim, metrics, wrap, grad, probability, sparse, dyna
reinforcement
from .learning_rate_schedule import *
from .dynamic_lr import *
from .cell import Cell, GraphKernel, GraphCell
from .cell import Cell, GraphCell
from .layer import *
from .loss import *
from .optim import *
@ -31,7 +31,7 @@ from .grad import Jvp, Vjp
from .sparse import *
from .reinforcement import *
__all__ = ["Cell", "GraphKernel", "GraphCell"]
__all__ = ["Cell", "GraphCell"]
__all__.extend(layer.__all__)
__all__.extend(loss.__all__)
__all__.extend(optim.__all__)

38
mindspore/nn/cell.py
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@ -24,7 +24,6 @@ import numpy
from mindspore._checkparam import args_type_check
from mindspore import log as logger
from mindspore.common.parameter import PARAMETER_NAME_DEFAULT
from mindspore.common._decorator import deprecated
from mindspore.context import ParallelMode
from .. import context
from .._c_expression import init_pipeline, Cell_, FuncGraph, MixedPrecisionType
@ -1650,43 +1649,6 @@ class Cell(Cell_):
return params
class GraphKernel(Cell):
"""
Base class for GraphKernel.
A `GraphKernel` a composite of basic primitives and can be compiled into a fused kernel automatically when
enable_graph_kernel in context is set to True.
This class is deprecated from version 1.3 and will be removed in a future version, use Cell instead.
GraphKernel is not supported user-defined cells anymore, the `GraphKernel` objects will be treated as
normal `Cell` objects.
Args:
auto_prefix (bool): Recursively generate namespaces. Default: True.
flags (dict) : Set graph flags. Default: None.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> class Relu(nn.GraphKernel):
... def __init__(self):
... super(Relu, self).__init__()
... self.max = P.Maximum()
...
... def construct(self, x):
... return self.max(P.Fill()(P.DType()(x), P.Shape()(x), 0.0), x)
"""
@deprecated("1.3", "Cell", True)
def __init__(self, auto_prefix=True, flags=None):
super(GraphKernel, self).__init__(auto_prefix, flags)
def construct(self):
raise NotImplementedError
class GraphCell(Cell):
"""
Base class for running the graph loaded from a MindIR.

1
mindspore/ops/_op_impl/akg/ascend/__init__.py
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@ -24,7 +24,6 @@ from .exp import _exp_akg
from .expand_dims import _expand_dims_akg
from .greater import _greater_akg
from .greater_equal import _greater_equal_akg
from .inplace_assign import _inplace_assign_akg
from .less import _less_akg
from .less_equal import _less_equal_akg
from .log import _log_akg

41
mindspore/ops/_op_impl/akg/ascend/inplace_assign.py
View File

@ -1,41 +0,0 @@
# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""InplaceAssign op"""
from mindspore.ops.op_info_register import op_info_register, AkgAscendRegOp, DataType as DT
op_info = AkgAscendRegOp("InplaceAssign") \
.fusion_type("ELEMWISE") \
.input(0, "x") \
.input(1, "y") \
.input(2, "z") \
.output(0, "output") \
.attr("fake_output", "optional", "bool") \
.dtype_format(DT.F16_Default, DT.F16_Default, DT.F16_Default, DT.F16_Default) \
.dtype_format(DT.F32_Default, DT.F32_Default, DT.F32_Default, DT.F32_Default) \
.dtype_format(DT.I32_Default, DT.I32_Default, DT.I32_Default, DT.I32_Default) \
.dtype_format(DT.F16_5HD, DT.F16_5HD, DT.F16_5HD, DT.F16_5HD) \
.dtype_format(DT.F32_5HD, DT.F32_5HD, DT.F32_5HD, DT.F32_5HD) \
.dtype_format(DT.I32_5HD, DT.I32_5HD, DT.I32_5HD, DT.I32_5HD) \
.dtype_format(DT.F16_FracZ, DT.F16_FracZ, DT.F16_FracZ, DT.F16_FracZ) \
.dtype_format(DT.F32_FracZ, DT.F32_FracZ, DT.F32_FracZ, DT.F32_FracZ) \
.dtype_format(DT.I32_FracZ, DT.I32_FracZ, DT.I32_FracZ, DT.I32_FracZ) \
.get_op_info()
@op_info_register(op_info)
def _inplace_assign_akg():
"""InplaceAssign Akg register"""
return

1
mindspore/ops/_op_impl/akg/gpu/__init__.py
View File

@ -15,7 +15,6 @@
"""__init__"""
from .equal import _equal_akg
from .greater_equal import _greater_equal_akg
from .inplace_assign import _inplace_assign_akg
from .lessequal import _lessequal_akg
from .logical_and import _logical_and_akg
from .logical_not import _logical_not_akg

41
mindspore/ops/_op_impl/akg/gpu/inplace_assign.py
View File

@ -1,41 +0,0 @@
# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""InplaceAssign op"""
from mindspore.ops.op_info_register import op_info_register, AkgGpuRegOp, DataType as DT
op_info = AkgGpuRegOp("InplaceAssign") \
.fusion_type("ELEMWISE") \
.input(0, "x") \
.input(1, "y") \
.input(2, "z") \
.output(0, "output") \
.attr("fake_output", "optional", "bool") \
.dtype_format(DT.F16_Default, DT.F16_Default, DT.F16_Default, DT.F16_Default) \
.dtype_format(DT.F32_Default, DT.F32_Default, DT.F32_Default, DT.F32_Default) \
.dtype_format(DT.I32_Default, DT.I32_Default, DT.I32_Default, DT.I32_Default) \
.dtype_format(DT.F16_5HD, DT.F16_5HD, DT.F16_5HD, DT.F16_5HD) \
.dtype_format(DT.F32_5HD, DT.F32_5HD, DT.F32_5HD, DT.F32_5HD) \
.dtype_format(DT.I32_5HD, DT.I32_5HD, DT.I32_5HD, DT.I32_5HD) \
.dtype_format(DT.F16_FracZ, DT.F16_FracZ, DT.F16_FracZ, DT.F16_FracZ) \
.dtype_format(DT.F32_FracZ, DT.F32_FracZ, DT.F32_FracZ, DT.F32_FracZ) \
.dtype_format(DT.I32_FracZ, DT.I32_FracZ, DT.I32_FracZ, DT.I32_FracZ) \
.get_op_info()
@op_info_register(op_info)
def _inplace_assign_akg():
"""InplaceAssign Akg register"""
return

124
mindspore/ops/op_selector.py
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@ -1,124 +0,0 @@
# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""
A factory class that create op selector instance to config switch on a class,
which can be used to control the switch of op type: GraphKernel or Primitive.
"""
import importlib
import inspect
from mindspore import context
from mindspore.common._decorator import deprecated
class _OpSelector:
"""
A helper class, which can be used to choose different type of operator.
When an instance of this class is called, we return the right operator
according to the context['enable_graph_kernel'] and the name of the
parameter. returned operator will be a GraphKernel op ora Primitive op.
Args:
op (class): an empty class has an operator name as its class name
config_optype (str): operator type, which must be either 'GraphKernel'
or 'Primitive'
graph_kernel_pkg (str): real operator's package name
primitive_pkg (str): graph kernel operator's package name
Examples:
>>> class A: pass
>>> selected_op = _OpSelector(A, "GraphKernel",
... "graph_kernel.ops.pkg", "primitive.ops.pkg")
>>> # selected_op() will call graph_kernel.ops.pkg.A()
"""
GRAPH_KERNEL = "GraphKernel"
PRIMITIVE = "Primitive"
DEFAULT_OP_TYPE = PRIMITIVE
KW_STR = "op_type"
def __init__(self, op, config_optype, primitive_pkg, graph_kernel_pkg):
self.op_name = op.__name__
self.config_optype = config_optype
self.graph_kernel_pkg = graph_kernel_pkg
self.primitive_pkg = primitive_pkg
def __call__(self, *args, **kwargs):
_op_type = _OpSelector.DEFAULT_OP_TYPE
if context.get_context("device_target") in ['Ascend', 'GPU'] and context.get_context("enable_graph_kernel"):
if _OpSelector.KW_STR in kwargs:
_op_type = kwargs.get(_OpSelector.KW_STR)
kwargs.pop(_OpSelector.KW_STR, None)
elif self.config_optype is not None:
_op_type = self.config_optype
if _op_type == _OpSelector.GRAPH_KERNEL:
pkg = self.graph_kernel_pkg
else:
pkg = self.primitive_pkg
op = getattr(importlib.import_module(pkg, __package__), self.op_name)
return op(*args, **kwargs)
@deprecated("1.3", "basic Primitive", False)
def new_ops_selector(primitive_pkg, graph_kernel_pkg):
"""
A factory method to return an op selector
When the GraphKernel switch is on:
`context.get_context('enable_graph_kernel') == True`, we have 2 ways to control the op type:
(1). call the real op with an extra parameter `op_type='Primitive'` or `op_type='GraphKernel'`
(2). pass a parameter to the op selector, like `@op_selector('Primitive')` or
`@op_selector('GraphKernel')`
(3). default op type is PRIMITIVE
The order of the highest priority to lowest priority is (1), (2), (3)
If the GraphKernel switch is off, then op_type will always be PRIMITIVE.
The user-defined GraphKernel Cell is deprecated, this interface will be removed in a future version.
Args:
primitive_pkg (str): primitive op's package name
graph_kernel_pkg (str): graph kernel op's package name
Returns:
returns an op selector, which can control what operator should be actually called.
Examples:
>>> op_selector = new_ops_selector("primitive_pkg.some.path",
... "graph_kernel_pkg.some.path")
>>> @op_selector
>>> class ReduceSum: pass
"""
def op_selector(cls_or_optype):
_primitive_pkg = primitive_pkg
_graph_kernel_pkg = graph_kernel_pkg
def direct_op_type():
darg = None
if cls_or_optype is None:
pass
elif not inspect.isclass(cls_or_optype):
darg = cls_or_optype
return darg
if direct_op_type() is not None:
def deco_cls(_real_cls):
return _OpSelector(_real_cls, direct_op_type(), _primitive_pkg, _graph_kernel_pkg)
return deco_cls
return _OpSelector(cls_or_optype, direct_op_type(), _primitive_pkg, _graph_kernel_pkg)
return op_selector

2
mindspore/ops/operations/__init__.py
View File

@ -89,7 +89,7 @@ from .nn_ops import (LSTM, SGD, Adam, AdamWeightDecay, FusedSparseAdam, FusedSpa
ApplyRMSProp, ApplyCenteredRMSProp, BasicLSTMCell, InTopK, AdaptiveAvgPool2D, SoftShrink)
from . import _quant_ops
from ._quant_ops import *
from .other_ops import (Assign, InplaceAssign, IOU, BoundingBoxDecode, BoundingBoxEncode,
from .other_ops import (Assign, IOU, BoundingBoxDecode, BoundingBoxEncode,
ConfusionMatrix, PopulationCount, UpdateState, Load,
CheckValid, Partial, Depend, identity, CheckBprop, Push, Pull, PullWeight, PushWeight,
PushMetrics, StartFLJob, UpdateModel, GetModel, PyFunc, ExchangeKeys, GetKeys)

48
mindspore/ops/operations/other_ops.py
View File

@ -17,7 +17,6 @@
import functools
import mindspore.common._monad as monad
from mindspore import log as logger
from mindspore.common._decorator import deprecated
from .. import signature as sig
from ..._checkparam import Validator as validator, Rel
from ...common import dtype as mstype
@ -71,53 +70,6 @@ class Assign(Primitive):
self.add_prim_attr('side_effect_mem', True)
class InplaceAssign(PrimitiveWithInfer):
"""
Inplace assign `Parameter` with a value.
This primitive can only use in graph kernel.
InplaceAssign is deprecated from version 1.3 and will be removed in a future version, use Assign instead.
Inputs:
- **variable** (Parameter) - The `Parameter`.
- **value** (Tensor) - The value to be assigned.
- **depend** (Tensor) - The dependent tensor to keep this op connected in graph.
Outputs:
Tensor, has the same type as original `variable`.
Raises:
TypeError: If `value` or `depend` is not a Tensor.
Examples:
>>> class Net(nn.Cell):
... def __init__(self):
... super(Net, self).__init__()
... self.inplace_assign = ops.InplaceAssign()
...
... def construct(self, x):
... val = x - 1.0
... ret = x + 2.0
... return self.inplace_assign(x, val, ret)
...
>>> x = Tensor([2.0], mindspore.float32)
>>> net = Net()
>>> output = net(x)
>>> print(output)
"""
@deprecated("1.3", "Assign", False)
@ prim_attr_register
def __init__(self):
"""Initialize InplaceAssign."""
self.init_prim_io_names(inputs=['x', 'y', 'z'], outputs=['output'])
def infer_shape(self, x, y, z):
return z
def infer_dtype(self, x, y, z):
return z
class Load(PrimitiveWithCheck):
"""
Load `Parameter` to a value.