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!537 GPU add akg kernel logical_and logical_or

Merge pull request !537 from VectorSL/logical_and_or_new
tags/v0.2.0-alpha
mindspore-ci-bot Gitee 6 years ago
parent
commit
7355113bc7
6 changed files with 220 additions and 0 deletions
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      mindspore/_akg/gpu/logical_and.py
  2. +40
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      mindspore/_akg/gpu/logical_or.py
  3. +41
    -0
      mindspore/_akg/ops/math/logical_and.py
  4. +41
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      mindspore/_akg/ops/math/logical_or.py
  5. +29
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      mindspore/ops/_op_impl/akg/gpu/logical_and.py
  6. +29
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      mindspore/ops/_op_impl/akg/gpu/logical_or.py

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mindspore/_akg/gpu/logical_and.py View File

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# 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.
"""logical_and"""
import _akg.tvm
from _akg.ops.math import logical_and
from _akg.topi.generic import schedule_elemwise

def LogicalAnd(x, y):
"""LogicalAnd."""
return logical_and.logical_and(x, y)


def gpu_schedule_LogicalAnd(outs):
"""
GPU schedule for LogicalAnd.

Args:
outs (tvm.tensor.Tensor): outputs of compute.

Returns:
sch (schedule.Schedule): The created schedule.
"""
device = 'cuda'
ctx = _akg.tvm.context(device, 0)
if not ctx.exist:
raise SystemError("Skip because %s is not enabled" % device)
with _akg.tvm.target.create(device):
sch = schedule_elemwise(outs)
return sch

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mindspore/_akg/gpu/logical_or.py View File

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# 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.
"""logical_or"""
import _akg.tvm
from _akg.ops.math import logical_or
from _akg.topi.generic import schedule_elemwise

def LogicalOr(x, y):
"""LogicalOr."""
return logical_or.logical_or(x, y)


def gpu_schedule_LogicalOr(outs):
"""
GPU schedule for LogicalOr.

Args:
outs (tvm.tensor.Tensor): outputs of compute.

Returns:
sch (schedule.Schedule): The created schedule.
"""
device = 'cuda'
ctx = _akg.tvm.context(device, 0)
if not ctx.exist:
raise SystemError("Skip because %s is not enabled" % device)
with _akg.tvm.target.create(device):
sch = schedule_elemwise(outs)
return sch

+ 41
- 0
mindspore/_akg/ops/math/logical_and.py View File

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# 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.

"""operator dsl function: logical_and"""
import _akg.tvm
import _akg.topi
from _akg.utils import validation_check as vc_util

@vc_util.check_input_type(_akg.tvm.tensor.Tensor, _akg.tvm.tensor.Tensor)
def logical_and(input1, input2):
"""
Compute logical_and of input1 and input2.

Args:
input1 (tvm.tensor.Tensor): Tensor.
input2 (tvm.tensor.Tensor): Tensor.

Returns:
tvm.tensor.Tensor. LogicalAnd of input1 and input2.
"""

vc_util.elemwise_dtype_check(input1.dtype, input2.dtype)

shape1 = [x.value for x in input1.shape]
shape2 = [x.value for x in input2.shape]
vc_util.check_shape(shape1)
vc_util.check_shape(shape2)

res = _akg.topi.logical_and(input1, input2)
return res

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mindspore/_akg/ops/math/logical_or.py View File

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# 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.

"""operator dsl function: logical_or"""
import _akg.tvm
import _akg.topi
from _akg.utils import validation_check as vc_util

@vc_util.check_input_type(_akg.tvm.tensor.Tensor, _akg.tvm.tensor.Tensor)
def logical_or(input1, input2):
"""
Compute logical_or of input1 and input2.

Args:
input1 (tvm.tensor.Tensor): Tensor.
input2 (tvm.tensor.Tensor): Tensor.

Returns:
tvm.tensor.Tensor. LogicalOr of input1 and input2.
"""

vc_util.elemwise_dtype_check(input1.dtype, input2.dtype)

shape1 = [x.value for x in input1.shape]
shape2 = [x.value for x in input2.shape]
vc_util.check_shape(shape1)
vc_util.check_shape(shape2)

res = _akg.topi.logical_or(input1, input2)
return res

+ 29
- 0
mindspore/ops/_op_impl/akg/gpu/logical_and.py View File

@@ -0,0 +1,29 @@
# 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.

"""LogicalAnd op"""
from mindspore.ops.op_info_register import op_info_register, AkgRegOp, DataType

logicaland_op_info = AkgRegOp("LogicalAnd") \
.fusion_type("OPAQUE") \
.input(0, "x") \
.input(1, "y") \
.output(0, "output") \
.dtype_format(DataType.BOOL_Default, DataType.BOOL_Default, DataType.BOOL_Default) \
.get_op_info()

@op_info_register(logicaland_op_info)
def _logical_and_akg():
"""LogicalAnd register"""
return

+ 29
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mindspore/ops/_op_impl/akg/gpu/logical_or.py View File

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# 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.

"""LogicalOr op"""
from mindspore.ops.op_info_register import op_info_register, AkgRegOp, DataType

logicalor_op_info = AkgRegOp("LogicalOr") \
.fusion_type("OPAQUE") \
.input(0, "x") \
.input(1, "y") \
.output(0, "output") \
.dtype_format(DataType.BOOL_Default, DataType.BOOL_Default, DataType.BOOL_Default) \
.get_op_info()

@op_info_register(logicalor_op_info)
def _logical_or_akg():
"""LogicalOr register"""
return

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