forked from mindspore-Ecosystem/mindspore
[feat] [assistant] [I48OA6] add dynamic shape for Sort operator
This commit is contained in:
parent
0799a81411
commit
d141de4b64
|
@ -0,0 +1,63 @@
|
|||
/**
|
||||
* Copyright 2021 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.
|
||||
*/
|
||||
#include "ops/sort.h"
|
||||
#include <string>
|
||||
#include <algorithm>
|
||||
#include <memory>
|
||||
#include <set>
|
||||
#include <vector>
|
||||
#include "ops/op_utils.h"
|
||||
#include "utils/check_convert_utils.h"
|
||||
#include "abstract/primitive_infer_map.h"
|
||||
|
||||
namespace mindspore {
|
||||
namespace ops {
|
||||
namespace {
|
||||
abstract::TupleShapePtr SortInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
|
||||
MS_EXCEPTION_IF_NULL(primitive);
|
||||
auto prim_name = primitive->name();
|
||||
const int64_t input_num = 1;
|
||||
(void)CheckAndConvertUtils::CheckInteger("input numbers", SizeToLong(input_args.size()), kGreaterEqual, input_num,
|
||||
prim_name);
|
||||
CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
|
||||
auto x = input_args[0]->BuildShape();
|
||||
MS_EXCEPTION_IF_NULL(x);
|
||||
auto shape_element = x->cast<abstract::ShapePtr>();
|
||||
MS_EXCEPTION_IF_NULL(shape_element);
|
||||
return std::make_shared<abstract::TupleShape>(std::vector<abstract::BaseShapePtr>{shape_element, shape_element});
|
||||
}
|
||||
|
||||
TuplePtr SortInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
|
||||
auto infer_type = input_args[0]->BuildType();
|
||||
MS_EXCEPTION_IF_NULL(infer_type);
|
||||
const std::set<TypePtr> valid_types = {kFloat16, kFloat32};
|
||||
auto type = CheckAndConvertUtils::CheckTensorTypeValid("inputx", infer_type, valid_types, prim->name());
|
||||
std::vector<TypePtr> type_tuple;
|
||||
type_tuple.push_back(type);
|
||||
type_tuple.push_back(kInt32);
|
||||
return std::make_shared<Tuple>(type_tuple);
|
||||
}
|
||||
} // namespace
|
||||
|
||||
AbstractBasePtr SortInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
|
||||
const std::vector<AbstractBasePtr> &input_args) {
|
||||
auto infertype = SortInferType(primitive, input_args);
|
||||
auto infershape = SortInferShape(primitive, input_args);
|
||||
return abstract::MakeAbstract(infershape, infertype);
|
||||
}
|
||||
REGISTER_PRIMITIVE_EVAL_IMPL(Sort, prim::kPrimSort, SortInfer, nullptr, true);
|
||||
} // namespace ops
|
||||
} // namespace mindspore
|
|
@ -0,0 +1,42 @@
|
|||
/**
|
||||
* Copyright 2021 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.
|
||||
*/
|
||||
|
||||
#ifndef MINDSPORE_CORE_OPS_SORT_H_
|
||||
#define MINDSPORE_CORE_OPS_SORT_H_
|
||||
#include <map>
|
||||
#include <vector>
|
||||
#include <string>
|
||||
#include <memory>
|
||||
#include "ops/primitive_c.h"
|
||||
#include "abstract/abstract_value.h"
|
||||
#include "utils/check_convert_utils.h"
|
||||
#include "ops/op_utils.h"
|
||||
|
||||
namespace mindspore {
|
||||
namespace ops {
|
||||
constexpr auto kNameSort = "Sort";
|
||||
class Sort : public PrimitiveC {
|
||||
public:
|
||||
Sort() : PrimitiveC(kNameSort) { InitIOName({"x"}, {"y1", "y2"}); }
|
||||
~Sort() = default;
|
||||
MS_DECLARE_PARENT(Sort, PrimitiveC);
|
||||
};
|
||||
AbstractBasePtr SortInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
|
||||
const std::vector<AbstractBasePtr> &input_args);
|
||||
} // namespace ops
|
||||
} // namespace mindspore
|
||||
|
||||
#endif // MINDSPORE_CORE_OPS_SORT_H_
|
|
@ -266,6 +266,7 @@ from .depth_to_space import _depth_to_space_tbe
|
|||
from .space_to_depth import _space_to_depth_tbe
|
||||
from .extract_image_patches import _extract_image_patches_tbe
|
||||
from .sort import _sort_tbe
|
||||
from .sort_ds import _sort_ds_tbe
|
||||
from .floor import _floor_tbe
|
||||
from .ceil import _ceil_tbe
|
||||
from .log1p import _log1p_tbe
|
||||
|
|
|
@ -0,0 +1,39 @@
|
|||
# Copyright 2021 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.
|
||||
# ============================================================================
|
||||
|
||||
"""Sort op"""
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
sort_op_info = TBERegOp("Sort") \
|
||||
.fusion_type("OPAQUE") \
|
||||
.async_flag(False) \
|
||||
.binfile_name("sort.so") \
|
||||
.compute_cost(10) \
|
||||
.kernel_name("sort") \
|
||||
.partial_flag(True) \
|
||||
.dynamic_shape(True) \
|
||||
.attr("axis", "optional", "int", "all", "-1") \
|
||||
.attr("descending", "optional", "bool", "all", "false") \
|
||||
.input(0, "x", False, "required", "all") \
|
||||
.output(0, "y1", False, "required", "all") \
|
||||
.output(1, "y2", False, "required", "all") \
|
||||
.dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.I32_Default) \
|
||||
.get_op_info()
|
||||
|
||||
|
||||
@op_info_register(sort_op_info)
|
||||
def _sort_ds_tbe():
|
||||
"""Sort TBE register"""
|
||||
return
|
|
@ -5868,7 +5868,7 @@ class TransShape(PrimitiveWithInfer):
|
|||
'value': None}
|
||||
|
||||
|
||||
class Sort(PrimitiveWithInfer):
|
||||
class Sort(Primitive):
|
||||
"""
|
||||
Sorts the elements of the input tensor along a given dimension in ascending order by value.
|
||||
|
||||
|
@ -5877,6 +5877,10 @@ class Sort(PrimitiveWithInfer):
|
|||
descending (bool): Controls the sorting order. If descending is True then the elements
|
||||
are sorted in descending order by value. Default: False.
|
||||
|
||||
.. warning::
|
||||
Currently, only the data type of Float16 is supported. If use Float32, it may cause loss
|
||||
of accuracy.
|
||||
|
||||
Inputs:
|
||||
- **x** (Tensor) - The input to sort, with float16 or float32 data type.
|
||||
The shape is :math:`(N,*)` where :math:`*` means,any number of additional dimensions.
|
||||
|
@ -5906,19 +5910,12 @@ class Sort(PrimitiveWithInfer):
|
|||
[2, 0, 1],
|
||||
[0, 1, 2]]))
|
||||
"""
|
||||
|
||||
@prim_attr_register
|
||||
def __init__(self, axis=-1, descending=False):
|
||||
"""Initialize Sort"""
|
||||
self.axis = validator.check_value_type("axis", axis, [int], self.name)
|
||||
self.descending = validator.check_value_type("descending", descending, [bool], self.name)
|
||||
|
||||
def infer_shape(self, x_shape):
|
||||
return x_shape, x_shape
|
||||
|
||||
def infer_dtype(self, x_dtype):
|
||||
validator.check_tensor_dtype_valid("x_dtype", x_dtype, [mstype.float32, mstype.float16], self.name)
|
||||
return x_dtype, mstype.tensor_type(mstype.int32)
|
||||
self.init_prim_io_names(inputs=['x'], outputs=['y1', 'y2'])
|
||||
|
||||
|
||||
class EmbeddingLookup(PrimitiveWithCheck):
|
||||
|
|
Loading…
Reference in New Issue