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!6933 add gatherD, identity op 

Merge pull request !6933 from wuxuejian/new_op
This commit is contained in:
mindspore-ci-bot 2020-09-30 09:09:02 +08:00 committed by Gitee
parent afb1a91568 8de76849ed
commit c12d48c727
6 changed files with 199 additions and 2 deletions
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4
mindspore/ccsrc/backend/kernel_compiler/aicpu/aicpu_util.h
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@ -43,8 +43,10 @@ constexpr auto kSeed2 = "seed2";
constexpr auto kTopK = "TopK";
constexpr auto kTopKV2 = "TopKV2";
constexpr auto kEditDistance = "EditDistance";
constexpr auto kGatherD = "GatherD";
constexpr auto kIdentity = "Identity";
constexpr auto kCustRunApi = "RunCpuKernel";
const std::set<std::string> kCustAiCpuKernelOps{kTopK, kEditDistance};
const std::set<std::string> kCustAiCpuKernelOps{kEditDistance, kGatherD, kIdentity};
struct AicpuParamHead {
uint32_t length; // Total length: include cunstom message

2
mindspore/ops/_op_impl/aicpu/__init__.py
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@ -16,6 +16,8 @@
from .init_data_set_queue import _init_data_set_queue_aicpu
from .embedding_lookup import _embedding_lookup_aicpu
from .padding import _padding_aicpu
from .gather import _gather_aicpu
from .identity import _identity_aicpu
from .dropout_genmask import _dropout_genmask_aicpu
from .get_next import _get_next_aicpu
from .print_tensor import _print_aicpu

78
mindspore/ops/_op_impl/aicpu/gather.py Normal file
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@ -0,0 +1,78 @@
# 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.
# ============================================================================
"""GatherD op"""
from mindspore.ops.op_info_register import op_info_register, AiCPURegOp, DataType
gather_op_info = AiCPURegOp("GatherD") \
.fusion_type("OPAQUE") \
.input(0, "input", "required") \
.input(1, "dim", "required") \
.input(2, "index", "required") \
.output(0, "output", "required") \
.dtype_format(DataType.I8_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.I8_Default) \
.dtype_format(DataType.I16_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.I16_Default) \
.dtype_format(DataType.I32_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.I32_Default) \
.dtype_format(DataType.I64_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.I64_Default) \
.dtype_format(DataType.U8_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.U8_Default) \
.dtype_format(DataType.U16_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.U16_Default) \
.dtype_format(DataType.U32_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.U32_Default) \
.dtype_format(DataType.U64_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.U64_Default) \
.dtype_format(DataType.F16_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.F16_Default) \
.dtype_format(DataType.F32_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.F32_Default) \
.dtype_format(DataType.F64_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.F64_Default) \
.dtype_format(DataType.BOOL_Default, DataType.I32_Default, \
DataType.I32_Default, DataType.BOOL_Default) \
.dtype_format(DataType.I8_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.I8_Default) \
.dtype_format(DataType.I16_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.I16_Default) \
.dtype_format(DataType.I32_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.I32_Default) \
.dtype_format(DataType.I64_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.I64_Default) \
.dtype_format(DataType.U8_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.U8_Default) \
.dtype_format(DataType.U16_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.U16_Default) \
.dtype_format(DataType.U32_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.U32_Default) \
.dtype_format(DataType.U64_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.U64_Default) \
.dtype_format(DataType.F16_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.F16_Default) \
.dtype_format(DataType.F32_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.F32_Default) \
.dtype_format(DataType.F64_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.F64_Default) \
.dtype_format(DataType.BOOL_Default, DataType.I32_Default, \
DataType.I64_Default, DataType.BOOL_Default) \
.get_op_info()
@op_info_register(gather_op_info)
def _gather_aicpu():
"""GatherD AiCPU register"""
return

40
mindspore/ops/_op_impl/aicpu/identity.py Normal file
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@ -0,0 +1,40 @@
# 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.
# ============================================================================
"""Identity op"""
from mindspore.ops.op_info_register import op_info_register, AiCPURegOp, DataType
identity_op_info = AiCPURegOp("Identity") \
.fusion_type("OPAQUE") \
.input(0, "x", "required") \
.output(0, "y", "required") \
.dtype_format(DataType.BOOL_Default, DataType.BOOL_Default) \
.dtype_format(DataType.I8_Default, DataType.I8_Default) \
.dtype_format(DataType.I16_Default, DataType.I16_Default) \
.dtype_format(DataType.I32_Default, DataType.I32_Default) \
.dtype_format(DataType.I64_Default, DataType.I64_Default) \
.dtype_format(DataType.U8_Default, DataType.U8_Default) \
.dtype_format(DataType.U16_Default, DataType.U16_Default) \
.dtype_format(DataType.U32_Default, DataType.U32_Default) \
.dtype_format(DataType.U64_Default, DataType.U64_Default) \
.dtype_format(DataType.F16_Default, DataType.F16_Default) \
.dtype_format(DataType.F32_Default, DataType.F32_Default) \
.dtype_format(DataType.F64_Default, DataType.F64_Default) \
.get_op_info()
@op_info_register(identity_op_info)
def _identity_aicpu():
"""Identity AiCPU register"""
return

4
mindspore/ops/operations/__init__.py
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@ -33,7 +33,7 @@ from .array_ops import (Argmax, Argmin, Cast, Concat, Pack, Unpack,
Transpose, TruncatedNormal, TupleToArray, UnsortedSegmentMin, UnsortedSegmentProd,
UnsortedSegmentSum, SpaceToDepth, DepthToSpace, SpaceToBatch, BatchToSpace,
SpaceToBatchND, BatchToSpaceND, BroadcastTo, InplaceUpdate, ReverseSequence, EmbeddingLookup,
Unique)
Unique, GatherD, Identity)
from .comm_ops import (AllGather, AllReduce, _AlltoAll, ReduceScatter, Broadcast,
_MirrorOperator, ReduceOp, _VirtualDataset,
_VirtualDiv, _GetTensorSlice,
@ -153,6 +153,8 @@ __all__ = [
'SparseGatherV2',
'EmbeddingLookup',
'Padding',
'GatherD',
'Identity',
'Concat',
'Pack',
'Unpack',

73
mindspore/ops/operations/array_ops.py
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@ -3797,3 +3797,76 @@ class EmbeddingLookup(PrimitiveWithInfer):
'dtype': params['dtype'],
'value': None}
return out
class GatherD(PrimitiveWithInfer):
"""
Gathers values along an axis specified by dim.
Inputs:
- **x** (Tensor) - The source tensor.
- **dim** (int) - The axis along which to index. It must be int32. Only constant value is allowed.
- **index** (Tensor) - The indices of elements to gather. It can be one of the following data types:
int32, int64.
Outputs:
Tensor, the shape of tensor is :math:`(z_1, z_2, ..., z_N)`.
Examples:
>>> x = Tensor(np.array([[1, 2], [3, 4]]), mindspore.int32)
>>> index = Tensor(np.array([[0, 0], [1, 0]]), mindspore.int32)
>>> dim = 1
>>> out = P.GatherD()(x, dim, index)
[[1, 1], [4, 3]]
"""
@prim_attr_register
def __init__(self):
"""Initialize GatherD"""
def __infer__(self, x, dim, index):
validator.check_subclass("x", x['dtype'], mstype.tensor, self.name)
validator.check_tensor_type_same({"index": index['dtype']}, [mstype.int32, mstype.int64], self.name)
validator.check_subclass("dim", dim['dtype'], mstype.int32, self.name)
x_shp = x['shape']
idx_shp = index['shape']
x_rank = len(x_shp)
idx_rank = len(idx_shp)
validator.check("x_rank, idx_rank", x_rank, "expected", idx_rank, Rel.EQ, self.name)
dim_v = dim['value']
validator.check("dim value", dim_v, "expected", 0, Rel.GE, self.name)
validator.check("dim value", dim_v, "expected", x_rank, Rel.LT, self.name)
for i in range(x_rank):
if i == dim_v:
continue
validator.check("x_shp[{0}], idx_shp[{0}]".format(i), x_shp[i], "expected", idx_shp[i], Rel.EQ, self.name)
out = {'shape': index['shape'],
'dtype': x['dtype'],
'value': None}
return out
class Identity(PrimitiveWithInfer):
"""
Returns a Tensor with the same shape and contents as input.
Inputs:
- **x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
Outputs:
Tensor, the shape of tensor is the same as `input_x`, :math:`(x_1, x_2, ..., x_R)`.
Examples:
>>> x = Tensor(np.array([1, 2, 3, 4]), mindspore.int64)
>>> y = P.Identity()(x)
[1, 2, 3, 4]
"""
@prim_attr_register
def __init__(self):
"""Initialize identity"""
def __infer__(self, x):
out = {'shape': x['shape'],
'dtype': x['dtype'],
'value': None}
return out