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!44253 remove operator ScalarToArray 

Merge pull request !44253 from zhujingxuan/remove
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i-robot 2022-10-20 06:34:48 +00:00 committed by Gitee
parent f25f16743e 5dfe8f2669
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16 changed files with 20 additions and 131 deletions
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1
docs/api/api_python/mindspore.ops.function.rst
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@ -386,7 +386,6 @@ Array操作
:template: classtemplate.rst
mindspore.ops.scalar_cast
mindspore.ops.scalar_to_array
mindspore.ops.scalar_to_tensor
mindspore.ops.tuple_to_array

1
docs/api/api_python/mindspore.ops.rst
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@ -466,7 +466,6 @@ Array操作
:template: classtemplate.rst
mindspore.ops.ScalarCast
mindspore.ops.ScalarToArray
mindspore.ops.ScalarToTensor
mindspore.ops.TupleToArray

8
docs/api/api_python/ops/mindspore.ops.ScalarToArray.rst
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@ -1,8 +0,0 @@
mindspore.ops.ScalarToArray
=============================
.. py:class:: mindspore.ops.ScalarToArray
将Scalar转换为 `Tensor` 。
更多参考详见 :func:`mindspore.ops.scalar_to_array`。

15
docs/api/api_python/ops/mindspore.ops.func_scalar_to_array.rst
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@ -1,15 +0,0 @@
mindspore.ops.scalar_to_array
=============================
.. py:function:: mindspore.ops.scalar_to_array(input_x)
将Scalar转换为 `Tensor` 。
参数：
- **input_x** (Union[int, float]) - ScalarToArray的输入，是Scalar且只能是常量值。
返回：
Tensor，0维Tensor，其值和输入一致。
异常：
- **TypeError** - `input_x` 既不是int也不是float。

1
docs/api/api_python_en/mindspore.ops.function.rst
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@ -386,7 +386,6 @@ Type Conversion
:template: classtemplate.rst
mindspore.ops.scalar_cast
mindspore.ops.scalar_to_array
mindspore.ops.scalar_to_tensor
mindspore.ops.tuple_to_array

1
docs/api/api_python_en/mindspore.ops.rst
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@ -466,7 +466,6 @@ Type Conversion
:template: classtemplate.rst
mindspore.ops.ScalarCast
mindspore.ops.ScalarToArray
mindspore.ops.ScalarToTensor
mindspore.ops.TupleToArray

40
mindspore/ccsrc/pipeline/jit/resource.cc
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@ -72,29 +72,27 @@ BuiltInTypeMap &GetMethodMap() {
{"__le__", prim::kPrimScalarLe}, // P.scalar_le
{"__ge__", prim::kPrimScalarGe}, // P.scalar_ge
{"__bool__", std::string("int_bool")}, // C.int_bool
{"__ms_to_array__", prim::kPrimScalarToArray}, // P.scalar_to_array
}},
{kNumberTypeUInt,
{
{"__add__", prim::kPrimScalarAdd}, // P.scalar_add,
{"__sub__", prim::kPrimScalarSub}, // P.scalar_sub,
{"__mul__", prim::kPrimScalarMul}, // P.scalar_mul,
{"__floordiv__", prim::kPrimScalarDiv}, // P.scalar_div,
{"__truediv__", std::string("int_truediv")}, // C.int_truediv
{"__mod__", prim::kPrimScalarMod}, // P.scalar_mod,
{"__pow__", prim::kPrimScalarPow}, // P.scalar_pow,
{"__floor__", prim::kPrimIdentity}, // P.identity,
{"__trunc__", prim::kPrimIdentity}, // P.identity,
{"__pos__", prim::kPrimScalarUadd}, // P.scalar_uadd,
{"__neg__", prim::kPrimScalarUsub}, // P.scalar_usub,
{"__eq__", prim::kPrimScalarEq}, // P.scalar_eq,
{"__ne__", prim::kPrimScalarNe}, // P.scalar_ne,
{"__lt__", prim::kPrimScalarLt}, // P.scalar_lt,
{"__gt__", prim::kPrimScalarGt}, // P.scalar_gt,
{"__le__", prim::kPrimScalarLe}, // P.scalar_le,
{"__ge__", prim::kPrimScalarGe}, // P.scalar_ge,
{"__bool__", std::string("int_bool")}, // C.int_bool
{"__ms_to_array__", prim::kPrimScalarToArray}, // P.scalar_to_array,
{"__add__", prim::kPrimScalarAdd}, // P.scalar_add,
{"__sub__", prim::kPrimScalarSub}, // P.scalar_sub,
{"__mul__", prim::kPrimScalarMul}, // P.scalar_mul,
{"__floordiv__", prim::kPrimScalarDiv}, // P.scalar_div,
{"__truediv__", std::string("int_truediv")}, // C.int_truediv
{"__mod__", prim::kPrimScalarMod}, // P.scalar_mod,
{"__pow__", prim::kPrimScalarPow}, // P.scalar_pow,
{"__floor__", prim::kPrimIdentity}, // P.identity,
{"__trunc__", prim::kPrimIdentity}, // P.identity,
{"__pos__", prim::kPrimScalarUadd}, // P.scalar_uadd,
{"__neg__", prim::kPrimScalarUsub}, // P.scalar_usub,
{"__eq__", prim::kPrimScalarEq}, // P.scalar_eq,
{"__ne__", prim::kPrimScalarNe}, // P.scalar_ne,
{"__lt__", prim::kPrimScalarLt}, // P.scalar_lt,
{"__gt__", prim::kPrimScalarGt}, // P.scalar_gt,
{"__le__", prim::kPrimScalarLe}, // P.scalar_le,
{"__ge__", prim::kPrimScalarGe}, // P.scalar_ge,
{"__bool__", std::string("int_bool")}, // C.int_bool
}},
{kNumberTypeFloat,
{
@ -116,7 +114,6 @@ BuiltInTypeMap &GetMethodMap() {
{"__le__", prim::kPrimScalarLe}, // P.scalar_le,
{"__ge__", prim::kPrimScalarGe}, // P.scalar_ge,
{"__bool__", std::string("float_bool")}, // C.float_bool
{"__ms_to_array__", prim::kPrimScalarToArray}, // P.scalar_to_array,
}},
{kObjectTypeTuple,
{
@ -202,7 +199,6 @@ BuiltInTypeMap &GetMethodMap() {
{"__ms_iter__", prim::kPrimIdentity}, // C.array_iter
{"__ms_hasnext__", std::string("array_hasnext")}, // C.array_hasnext
{"__ms_next__", std::string("array_next")}, // C.array_next
{"__ms_to_array__", prim::kPrimIdentity}, // P.identity,
{"gather_elements", std::string("gather_elements")}, // P.GatherD
{"item", std::string("item")}, // P.item,
{"itemset", std::string("itemset")}, // P.itemset,

1
mindspore/ccsrc/pipeline/pynative/pynative_cache.h
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@ -94,7 +94,6 @@ static std::unordered_map<std::string, std::vector<size_t>> kDynamicInputOpMap =
{"Xdivy", {0, 1}},
{"Xlogy", {0, 1}},
{"ScalarToTensor", {0}},
{"ScalarToArray", {0}},
{"StandardLaplace", {0}},
{"UniqueWithPad", {1}},
{"ApplyAdadelta", {3, 4, 5}},

2
mindspore/core/abstract/ops/infer_functions.h
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@ -56,8 +56,6 @@ AbstractBasePtr InferImplSqrt(const AnalysisEnginePtr &, const PrimitivePtr &pri
AbstractBasePtr InferImplSqrtGrad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplScalarToArray(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplArrayToScalar(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list);
AbstractBasePtr InferImplBroadCastShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive,

9
mindspore/core/abstract/ops/prim_arrays.cc
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@ -162,15 +162,6 @@ TypePtr RangeCheckAndInferType(const PrimitivePtr &prim, const std::vector<Abstr
return start_type;
}
} // namespace
AbstractBasePtr InferImplScalarToArray(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list) {
// Inputs: a scalar.
const std::string op_name = primitive->name();
CheckArgsSize(op_name, args_spec_list, 1);
AbstractScalarPtr arg = CheckArg<AbstractScalar>(op_name, args_spec_list, 0);
return std::make_shared<AbstractTensor>(arg, std::make_shared<Shape>());
}
AbstractBasePtr InferImplArrayToScalar(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
const AbstractBasePtrList &args_spec_list) {
// Inputs: a tensor with 0 shape.

1
mindspore/core/abstract/ops/primitive_infer_map.cc
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@ -272,7 +272,6 @@ PrimitiveEvalImplMap &GetPrimitiveToEvalImplMap() {
{prim::kPrimRealInner, R{InferImplReal, nullptr, true}},
// Array
{prim::kPrimRange, R{InferImplRange, nullptr, true}},
{prim::kPrimScalarToArray, R{InferImplScalarToArray, nullptr, true}},
{prim::kPrimArrayToScalar, R{InferImplArrayToScalar, nullptr, true}},
{prim::kPrimBroadcastShape, R{InferImplBroadCastShape, nullptr, true}},
{prim::kPrimUnique, R{InferImplUnique, nullptr, true}},

1
mindspore/core/ops/core_ops.h
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@ -503,7 +503,6 @@ GVAR_DEF(PrimitivePtr, kPrimUnravelIndex, std::make_shared<Primitive>(kUnravelIn
GVAR_DEF(PrimitivePtr, kPrimDynamicBroadcastTo, std::make_shared<Primitive>(kDynamicBroadcastTo));
GVAR_DEF(PrimitivePtr, kPrimCummin, std::make_shared<Primitive>("Cummin"));
GVAR_DEF(PrimitivePtr, kPrimBroadcastTo, std::make_shared<Primitive>("BroadcastTo"));
GVAR_DEF(PrimitivePtr, kPrimScalarToArray, std::make_shared<Primitive>("scalar_to_array"));
GVAR_DEF(PrimitivePtr, kPrimLogNormalReverse, std::make_shared<Primitive>("LogNormalReverse"));
GVAR_DEF(PrimitivePtr, kPrimTopK, std::make_shared<Primitive>(kTopK));
GVAR_DEF(PrimitivePtr, kPrimInTopK, std::make_shared<Primitive>("InTopK"));

1
mindspore/python/mindspore/ops/function/__init__.py
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@ -54,7 +54,6 @@ from .array_func import (
tensor_slice,
strided_slice,
slice,
scalar_to_array,
scalar_to_tensor,
tuple_to_array,
expand_dims,

31
mindspore/python/mindspore/ops/function/array_func.py
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@ -77,7 +77,6 @@ tensor_scatter_mul_ = P.TensorScatterMul()
tensor_scatter_div_ = P.TensorScatterDiv()
tensor_scatter_min_ = P.TensorScatterMin()
tensor_scatter_max_ = P.TensorScatterMax()
scalar_to_array_ = P.ScalarToArray()
scalar_to_tensor_ = P.ScalarToTensor()
tuple_to_array_ = P.TupleToArray()
masked_select_ = P.MaskedSelect()
@ -3996,35 +3995,6 @@ def tensor_scatter_div(input_x, indices, updates):
return tensor_scatter_div_(input_x, indices, updates)
def scalar_to_array(input_x):
"""
Converts a scalar to a `Tensor`.
Args:
input_x (Union[int, float]): The input is a scalar. Only constant value is allowed.
Returns:
Tensor. 0-D Tensor and the content is the input.
Raises:
TypeError: If `input_x` is neither int nor float.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> input_x = 1.0
>>> print(type(input_x))
<class 'float'>
>>> output = ops.scalar_to_array(input_x)
>>> print(type(output))
<class 'mindspore.common.tensor.Tensor'>
>>> print(output)
1.0
"""
return scalar_to_array_(input_x)
def scalar_to_tensor(input_x, dtype=mstype.float32):
"""
Converts a scalar to a `Tensor`, and converts the data type to the specified type.
@ -4825,7 +4795,6 @@ __all__ = [
'stack',
'unstack',
'scalar_cast',
'scalar_to_array',
'scalar_to_tensor',
'space_to_batch_nd',
'batch_to_space_nd',

3
mindspore/python/mindspore/ops/operations/__init__.py
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@ -35,7 +35,7 @@ from .array_ops import (ArgMaxWithValue, ArgMinWithValue, Argmax, Argmin, BatchT
Eye, Fill, Gather, GatherD, GatherNd, GatherV2, Identity, Im2Col, InvertPermutation, IsInstance,
IsSubClass, LowerBound, Lstsq, MaskedFill, MaskedSelect, Meshgrid, Mvlgamma, Ones, OnesLike,
Pack, Padding, ParallelConcat, PopulationCount, Range, Rank, Reshape, ResizeNearestNeighbor,
ReverseSequence, ReverseV2, Rint, SameTypeShape, ScalarToArray, ScalarToTensor, ScatterAdd,
ReverseSequence, ReverseV2, Rint, SameTypeShape, ScalarToTensor, ScatterAdd,
ScatterDiv, ScatterMax, ScatterMin, ScatterMul, ScatterNd, ScatterNdAdd, ScatterNdDiv,
ScatterNdMax, ScatterNdMin, ScatterNdSub, ScatterNdUpdate, ScatterNonAliasingAdd, ScatterSub,
ScatterUpdate, SearchSorted, Select, Shape, Size, Slice, Sort, SpaceToBatch, SpaceToBatchND,
@ -319,7 +319,6 @@ __all__ = [
'DynamicRNN',
'ReduceAll',
'ReduceAny',
'ScalarToArray',
'ScalarToTensor',
'TupleToArray',
'GeSwitch',

35
mindspore/python/mindspore/ops/operations/array_ops.py
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@ -868,6 +868,7 @@ class TensorShape(Primitive):
class Unsqueeze(PrimitiveWithCheck):
"""Unsqueeze"""
@prim_attr_register
def __init__(self, axis):
self.init_prim_io_names(inputs=['x'], outputs=['y'])
@ -1828,40 +1829,6 @@ class TupleToArray(PrimitiveWithInfer):
return _run_op(self, self.name, args)
class ScalarToArray(PrimitiveWithInfer):
"""
Converts a scalar to a `Tensor`.
Refer to :func:`mindspore.ops.scalar_to_array` for more detail.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> op = ops.ScalarToArray()
>>> input_x = 1.0
>>> print(type(input_x))
<class 'float'>
>>> output = op(input_x)
>>> print(type(output))
<class 'mindspore.common.tensor.Tensor'>
>>> print(output)
1.0
"""
@prim_attr_register
def __init__(self):
pass
def infer_value(self, x):
validator.check_value_type("x", x, [int, float], self.name)
if isinstance(x, int):
ret = np.array(x, np.int32)
else:
ret = np.array(x, np.float32)
return Tensor(ret)
class ScalarToTensor(PrimitiveWithInfer):
"""
Converts a scalar to a `Tensor`, and converts the data type to the specified type.