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!1968 support vm for range

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Merge pull request !1968 from jiangjinsheng/vm_FusedMulApplyMomentumExtern
pull/1968/MERGE
mindspore-ci-bot 5 years ago committed by Gitee
parent 867cea77fd a1efe4d14d
commit eecf0a9ab8
8 changed files with 222 additions and 1 deletions
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1
mindspore/ccsrc/kernel/tbe/tbe_adapter.cc
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@ -100,6 +100,7 @@ static std::map<string, string> tbe_func_adapter_map = {
{"n_ms_with_mask", "nms_with_mask"},
{"square_sum_all", "square_sum_all"},
{"cum_sum", "cumsum_d"},
{"range", "range_d"},
{"inv_grad", "inv_grad"},
{"apply_rms_prop", "apply_rms_prop_d"},
{"cum_prod", "cumprod_d"},

4
mindspore/ops/_op_impl/tbe/__init__.py
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@ -244,3 +244,7 @@ from .confusion_matrix import _confusion_matrix_tbe
from .broadcast_to import _broadcast_to_tbe
from .strided_read import _strided_read_tbe
from .strided_write import _strided_write_tbe
from .range import _range_tbe
from .fused_mul_add_n_l2loss import _fused_mul_add_n_l2loss_tbe
from .fused_mul_apply_momentum_extern import _fused_mul_apply_momentum_extern_tbe
from .lamb_next_right import _lamb_next_right_tbe

53
mindspore/ops/_op_impl/tbe/fused_mul_add_n_l2loss.py
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@ -0,0 +1,53 @@
# 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.
# ============================================================================
"""FusedMulAddNL2loss op"""
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
fused_mul_add_n_l2loss_op_info = TBERegOp("FusedMulAddNL2loss") \
.fusion_type("OPAQUE") \
.async_flag(False) \
.binfile_name("fused_mul_addn_l2loss.so") \
.compute_cost(10) \
.kernel_name("fused_mul_addn_l2loss") \
.partial_flag(True) \
.input(0, "x1", False, "required", "all") \
.input(1, "x2", False, "required", "all") \
.input(2, "x3", False, "required", "all") \
.output(0, "y1", False, "required", "all") \
.output(1, "y2", False, "required", "all") \
.dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_Default,
DataType.F16_5HD, DataType.F16_Default) \
.dtype_format(DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0, DataType.F16_Default,
DataType.F16_C1HWNCoC0, DataType.F16_Default) \
.dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
DataType.F16_Default, DataType.F16_Default) \
.dtype_format(DataType.F16_FracZ, DataType.F16_FracZ, DataType.F16_Default,
DataType.F16_FracZ, DataType.F16_Default) \
.dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_Default,
DataType.F32_5HD, DataType.F32_Default) \
.dtype_format(DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0, DataType.F32_Default,
DataType.F32_C1HWNCoC0, DataType.F32_Default) \
.dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
DataType.F32_Default, DataType.F32_Default) \
.dtype_format(DataType.F32_FracZ, DataType.F32_FracZ, DataType.F32_Default,
DataType.F32_FracZ, DataType.F32_Default) \
.get_op_info()
@op_info_register(fused_mul_add_n_l2loss_op_info)
def _fused_mul_add_n_l2loss_tbe():
"""FusedMulAddNL2loss TBE register"""
return

67
mindspore/ops/_op_impl/tbe/fused_mul_apply_momentum_extern.py
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@ -0,0 +1,67 @@
# 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.
# ============================================================================
"""FusedMulApplyMomentumExtern op"""
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
fused_mul_apply_momentum_extern_op_info = TBERegOp("FusedMulApplyMomentumExtern") \
.fusion_type("OPAQUE") \
.async_flag(False) \
.binfile_name("fused_mul_apply_momentum_extern.so") \
.compute_cost(10) \
.kernel_name("fused_mul_apply_momentum_extern") \
.partial_flag(True) \
.attr("use_nesterov", "optional", "bool", "true,false", "false") \
.input(0, "var", False, "required", "all") \
.input(1, "accum", False, "required", "all") \
.input(2, "lr", False, "required", "all") \
.input(3, "x1", False, "required", "all") \
.input(4, "momentum", False, "required", "all") \
.input(5, "x2", False, "required", "all") \
.input(6, "var_copy", False, "required", "all") \
.output(0, "var", False, "required", "all") \
.output(1, "var_copy", False, "required", "all") \
.output(2, "accum", False, "required", "all") \
.dtype_format(DataType.F32_5HD, DataType.F16_5HD, DataType.F16_Default, DataType.F16_5HD,
DataType.F16_Default, DataType.F16_Default, DataType.F16_5HD, DataType.F32_5HD,
DataType.F16_5HD, DataType.F16_5HD) \
.dtype_format(DataType.F32_C1HWNCoC0, DataType.F16_C1HWNCoC0, DataType.F16_Default, DataType.F16_C1HWNCoC0,
DataType.F16_Default, DataType.F16_Default, DataType.F16_C1HWNCoC0, DataType.F32_C1HWNCoC0,
DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0) \
.dtype_format(DataType.F32_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F32_Default,
DataType.F16_Default, DataType.F16_Default) \
.dtype_format(DataType.F32_FracZ, DataType.F16_FracZ, DataType.F16_Default, DataType.F16_FracZ,
DataType.F16_Default, DataType.F16_Default, DataType.F16_FracZ, DataType.F32_FracZ,
DataType.F16_FracZ, DataType.F16_FracZ) \
.dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_Default, DataType.F32_5HD,
DataType.F32_Default, DataType.F32_Default, DataType.F16_5HD, DataType.F32_5HD,
DataType.F16_5HD, DataType.F32_5HD) \
.dtype_format(DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0, DataType.F32_Default, DataType.F32_C1HWNCoC0,
DataType.F32_Default, DataType.F32_Default, DataType.F16_C1HWNCoC0, DataType.F32_C1HWNCoC0,
DataType.F16_C1HWNCoC0, DataType.F32_C1HWNCoC0) \
.dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
DataType.F32_Default, DataType.F32_Default, DataType.F16_Default, DataType.F32_Default,
DataType.F16_Default, DataType.F32_Default) \
.dtype_format(DataType.F32_FracZ, DataType.F32_FracZ, DataType.F32_Default, DataType.F32_FracZ,
DataType.F32_Default, DataType.F32_Default, DataType.F16_FracZ, DataType.F32_FracZ,
DataType.F16_FracZ, DataType.F32_FracZ) \
.get_op_info()
@op_info_register(fused_mul_apply_momentum_extern_op_info)
def _fused_mul_apply_momentum_extern_tbe():
"""FusedMulApplyMomentumExtern TBE register"""
return

44
mindspore/ops/_op_impl/tbe/lamb_next_right.py
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@ -0,0 +1,44 @@
# 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.
# ============================================================================
"""LambNextRight op"""
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
lamb_next_right_op_info = TBERegOp("LambNextRight") \
.fusion_type("ELEMWISE") \
.async_flag(False) \
.binfile_name("lamb_next_right.so") \
.compute_cost(10) \
.kernel_name("lamb_next_right") \
.partial_flag(True) \
.input(0, "input_square", False, "required", "all") \
.input(1, "input_mul2", False, "required", "all") \
.input(2, "mul2_x", False, "required", "all") \
.input(3, "mul3_x", False, "required", "all") \
.input(4, "truediv1_recip", False, "required", "all") \
.input(5, "add2_y", False, "required", "all") \
.output(0, "y1", False, "required", "all") \
.output(1, "y2", False, "required", "all") \
.dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
.dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
.get_op_info()
@op_info_register(lamb_next_right_op_info)
def _lamb_next_right_tbe():
"""LambNextRight TBE register"""
return

39
mindspore/ops/_op_impl/tbe/range.py
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@ -0,0 +1,39 @@
# 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.
# ============================================================================
"""Range op"""
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
range_op_info = TBERegOp("Range") \
.fusion_type("OPAQUE") \
.async_flag(False) \
.binfile_name("range_d.so") \
.compute_cost(10) \
.kernel_name("range_d") \
.partial_flag(True) \
.attr("start", "required", "float", "all") \
.attr("limit", "required", "float", "all") \
.attr("delta", "required", "float", "all") \
.input(0, "x", False, "required", "all") \
.output(0, "y", False, "required", "all") \
.dtype_format(DataType.F32_Default, DataType.F32_Default) \
.dtype_format(DataType.I32_Default, DataType.I32_Default) \
.get_op_info()
@op_info_register(range_op_info)
def _range_tbe():
"""Range TBE register"""
return

3
mindspore/ops/operations/__init__.py
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@ -292,7 +292,8 @@ __all__ = [
"Atanh",
"BasicLSTMCell",
"ConfusionMatrix",
"BroadcastTo"
"BroadcastTo",
"Range"
]
__all__.extend(_quant_ops.__all__)

12
tests/ut/python/ops/test_array_ops.py
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@ -295,6 +295,15 @@ class ConfusionMatrixNet(Cell):
return self.confusion_matrix(x, y)
class RangeNet(Cell):
def __init__(self):
super(RangeNet, self).__init__()
self.range_ops = P.Range(1.0, 8.0, 2.0)
def construct(self, x):
return self.range_ops(x)
test_case_array_ops = [
('CustNet1', {
'block': CustNet1(),
@ -338,6 +347,9 @@ test_case_array_ops = [
('ConfusionMatrixNet', {
'block': ConfusionMatrixNet(),
'desc_inputs': [Tensor([0, 1, 1, 3], ms.int32), Tensor([0, 1, 1, 3], ms.int32)]}),
('RangeNet', {
'block': RangeNet(),
'desc_inputs': [Tensor(np.array([1, 2, 3, 2]), ms.int32)]}),
]
test_case_lists = [test_case_array_ops]

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