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tags/v0.3.0-alpha
z00478463 5 years ago
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  1. +0
    -75
      example/resnet50_imagenet2012_THOR/cus_ops/batch_matmul_impl.py
  2. +0
    -63
      example/resnet50_imagenet2012_THOR/cus_ops/cholesky_trsm.py
  3. +0
    -37
      example/resnet50_imagenet2012_THOR/cus_ops/cus_batch_matmul.py
  4. +0
    -37
      example/resnet50_imagenet2012_THOR/cus_ops/cus_cholesky_trsm.py
  5. +0
    -44
      example/resnet50_imagenet2012_THOR/cus_ops/cus_fused_abs_max1.py
  6. +0
    -51
      example/resnet50_imagenet2012_THOR/cus_ops/cus_img2col.py
  7. +0
    -54
      example/resnet50_imagenet2012_THOR/cus_ops/cus_matmul_cube.py
  8. +0
    -40
      example/resnet50_imagenet2012_THOR/cus_ops/cus_matmul_cube_dense_left.py
  9. +0
    -39
      example/resnet50_imagenet2012_THOR/cus_ops/cus_matmul_cube_fracz_right_mul.py
  10. +0
    -41
      example/resnet50_imagenet2012_THOR/cus_ops/cus_matrix_combine.py
  11. +0
    -44
      example/resnet50_imagenet2012_THOR/cus_ops/cus_transpose02314.py
  12. +0
    -69
      example/resnet50_imagenet2012_THOR/cus_ops/fused_abs_max1.py
  13. +0
    -87
      example/resnet50_imagenet2012_THOR/cus_ops/img2col_impl.py
  14. +0
    -102
      example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_dense_left.py
  15. +0
    -103
      example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_fracz_left_cast_impl.py
  16. +0
    -113
      example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_fracz_right_mul_impl.py
  17. +0
    -114
      example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_impl.py
  18. +0
    -63
      example/resnet50_imagenet2012_THOR/cus_ops/matrix_combine_impl.py
  19. +0
    -63
      example/resnet50_imagenet2012_THOR/cus_ops/transpose02314_impl.py

+ 0
- 75
example/resnet50_imagenet2012_THOR/cus_ops/batch_matmul_impl.py View File

@@ -1,75 +0,0 @@
# 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.
# ============================================================================
"""batch_matmul_impl"""
from mindspore.ops.op_info_register import op_info_register

@op_info_register("""{
"op_name": "CusBatchMatMul",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "batchmatmul.so",
"compute_cost": 10,
"kernel_name": "CusBatchMatMul",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 1,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "x2",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusBatchMatMul(input_x1, input_x2, output, transpose_a=False, transpose_b=True, kernel_name="batchmatmul"):
"""CusBatchMatMul"""
return

+ 0
- 63
example/resnet50_imagenet2012_THOR/cus_ops/cholesky_trsm.py View File

@@ -1,63 +0,0 @@
# 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.
# ============================================================================
"""CusCholeskyTrsm"""
from mindspore.ops.op_info_register import op_info_register

@op_info_register("""{
"op_name": "CusCholeskyTrsm",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "choleskytrsm.so",
"compute_cost": 10,
"kernel_name": "CusCholeskyTrsm",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusCholeskyTrsm(input_x, output, kernel_name):
"""CusCholeskyTrsm"""
return

+ 0
- 37
example/resnet50_imagenet2012_THOR/cus_ops/cus_batch_matmul.py View File

@@ -1,37 +0,0 @@
# 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.
# ============================================================================
"""CusBatchMatMul"""
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C

class CusBatchMatMul(PrimitiveWithInfer):
"""CusMatMulCube definition"""

@prim_attr_register
def __init__(self):
"""init CusMatMulCube"""
self.init_prim_io_names(inputs=['x1', 'x2'], outputs=['y'])

def get_bprop(self):
def bprop(x1, x2, out, dout):
return (C.zeros_like(x1), C.zeros_like(x2))

return bprop

def infer_shape(self, data1_shape, data2_shape):
return data1_shape

def infer_dtype(self, data1_dtype, data2_dtype):
return data1_dtype

+ 0
- 37
example/resnet50_imagenet2012_THOR/cus_ops/cus_cholesky_trsm.py View File

@@ -1,37 +0,0 @@
# 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.
# ============================================================================
"""CusCholeskyTrsm"""
from mindspore.ops import prim_attr_register, PrimitiveWithInfer


class CusCholeskyTrsm(PrimitiveWithInfer):
"""CusCholeskyTrsm definition"""

@prim_attr_register
def __init__(self):
"""init CusCholeskyTrsm"""
self.init_prim_io_names(inputs=['x1'], outputs=['y'])

def infer_shape(self, data1_shape):
ll = []
m, _ = data1_shape
if m >= 128:
ll = [m // 128, 128, 128]
else:
ll = [1, 64, 64]
return ll

def infer_dtype(self, data1_dtype):
return data1_dtype

+ 0
- 44
example/resnet50_imagenet2012_THOR/cus_ops/cus_fused_abs_max1.py View File

@@ -1,44 +0,0 @@
# 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.
# ============================================================================
"""CusFusedAbsMax1"""
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


class CusFusedAbsMax1(PrimitiveWithInfer):
"""CusCholeskyTrsm definition"""

@prim_attr_register
def __init__(self, origin_shape=[-1, -1]):
"""init CusCholeskyTrsm"""
self.init_prim_io_names(inputs=['x1'], outputs=['y'])
self.origin_shape = origin_shape

def get_bprop(self):
def bprop(x, out, dout):
return (C.zeros_like(x),)

return bprop

def infer_shape(self, data1_shape):
ll = []
if len(data1_shape) == 2:
ll = [1,]
else:
ll = [32, 64]
return ll

def infer_dtype(self, data1_dtype):
return data1_dtype

+ 0
- 51
example/resnet50_imagenet2012_THOR/cus_ops/cus_img2col.py View File

@@ -1,51 +0,0 @@
# 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.
# ============================================================================
"""CusImg2Col"""
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


class CusImg2Col(PrimitiveWithInfer):
"""CusImg2Col definition"""

@prim_attr_register
def __init__(self, ksizes, strides, dilates=(1, 1, 1, 1), mode="NC1HWC0"):
"""init CusImg2Col"""
self.init_prim_io_names(inputs=['x1'], outputs=['y'])
self.ksizes = ksizes
self.strides = strides
self.dilates = dilates
self.mode = mode

def get_bprop(self):
def bprop(x, out, dout):
return (C.zeros_like(x),)

return bprop

def infer_shape(self, data1_shape):
bs, c, h, w = data1_shape
_, stride_h, stride_w, _ = self.strides
_, k_w, k_h, _ = self.ksizes
# assert m == n
c0 = 16
c1 = c // 16
if c1 == 0:
c1 = 1
shape = [bs * int(h // stride_h) * int(w // stride_w), k_w * k_h * c1 * c0]
return shape

def infer_dtype(self, data1_dtype):
return data1_dtype

+ 0
- 54
example/resnet50_imagenet2012_THOR/cus_ops/cus_matmul_cube.py View File

@@ -1,54 +0,0 @@
# 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.
# ============================================================================
"""CusMatMulCube"""
import mindspore as ms
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


# y = x^2
class CusMatMulCube(PrimitiveWithInfer):
"""CusMatMulCube definition"""

@prim_attr_register
def __init__(self, transpose_a=False, transpose_b=False):
"""init CusMatMulCube"""
self.init_prim_io_names(inputs=['x1', 'x2'], outputs=['y'])
self.transpose_a = transpose_a
self.transpose_b = transpose_b

def get_bprop(self):
def bprop(x1, x2, out, dout):
return (C.zeros_like(x1), C.zeros_like(x2))

return bprop

def infer_shape(self, data1_shape, data2_shape):
# shape = [1, data1_shape[1], data2_shape[2], 16, 16]
# return shape
if self.transpose_a:
k1, m = data1_shape
else:
m, k1 = data1_shape
if self.transpose_b:
n, k2 = data2_shape
else:
k2, n = data2_shape
assert k1 == k2
shape = [m, n]
return shape

def infer_dtype(self, data1_dtype, data2_dtype):
return ms.common.dtype.tensor_type(getattr(ms, "float32"))

+ 0
- 40
example/resnet50_imagenet2012_THOR/cus_ops/cus_matmul_cube_dense_left.py View File

@@ -1,40 +0,0 @@
# 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.
# ============================================================================
"""CusMatMulCubeDenseLeft"""
import mindspore as ms
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


# y = x^2
class CusMatMulCubeDenseLeft(PrimitiveWithInfer):
"""CusMatMulCube definition"""

@prim_attr_register
def __init__(self):
"""init CusMatMulCube"""
self.init_prim_io_names(inputs=['x1', 'x2'], outputs=['y'])

def get_bprop(self):
def bprop(x1, x2, out, dout):
return (C.zeros_like(x1), C.zeros_like(x2))

return bprop

def infer_shape(self, data1_shape, data2_shape):
return data2_shape

def infer_dtype(self, data1_dtype, data2_dtype):
return ms.common.dtype.tensor_type(getattr(ms, "float16"))

+ 0
- 39
example/resnet50_imagenet2012_THOR/cus_ops/cus_matmul_cube_fracz_right_mul.py View File

@@ -1,39 +0,0 @@
# 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.
# ============================================================================
"""CusMatMulCubeFraczRightMul"""
import mindspore as ms
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


class CusMatMulCubeFraczRightMul(PrimitiveWithInfer):
"""CusMatMulCubeFraczRightMul definition"""

@prim_attr_register
def __init__(self):
"""init CusMatMulCubeFraczRightMul"""
self.init_prim_io_names(inputs=['x1', 'x2', 'x3'], outputs=['y'])

def get_bprop(self):
def bprop(x1, x2, x3, out, dout):
return (C.zeros_like(x1), C.zeros_like(x2), C.zeros_like(x3))

return bprop

def infer_shape(self, data1_shape, data2_shape, data3_shape):
return data1_shape

def infer_dtype(self, data1_dtype, data2_dtype, data3_dtype):
return ms.common.dtype.tensor_type(getattr(ms, "float32"))

+ 0
- 41
example/resnet50_imagenet2012_THOR/cus_ops/cus_matrix_combine.py View File

@@ -1,41 +0,0 @@
# 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.
# ============================================================================
"""CusMatrixCombine"""
from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


class CusMatrixCombine(PrimitiveWithInfer):
"""CusMatMulCube definition"""

@prim_attr_register
def __init__(self):
"""init CusMatMulCube"""
self.init_prim_io_names(inputs=['x'], outputs=['y'])

def get_bprop(self):
def bprop(x, out, dout):
return (C.zeros_like(x),)

return bprop

def infer_shape(self, data_shape):
a, b, c = data_shape
shape = [a * b, a * c]

return shape

def infer_dtype(self, data_dtype):
return data_dtype

+ 0
- 44
example/resnet50_imagenet2012_THOR/cus_ops/cus_transpose02314.py View File

@@ -1,44 +0,0 @@
# 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.
# ============================================================================
"""CusTranspose02314"""

from mindspore.ops import prim_attr_register, PrimitiveWithInfer
from mindspore.ops.composite import multitype_ops as C


class CusTranspose02314(PrimitiveWithInfer):
"""CusTranspose02314 definition"""

@prim_attr_register
def __init__(self):
"""init CusTranspose02314"""
self.init_prim_io_names(inputs=['x1'], outputs=['y'])

def get_bprop(self):
def bprop(x, out, dout):
return (C.zeros_like(x),)

return bprop

def infer_shape(self, data1_shape):
assert len(data1_shape) == 4
n, c, h, w = data1_shape
c0 = 16
c1 = c // 16
shape = (n * h * w, c1 * c0)
return shape

def infer_dtype(self, data1_dtype):
return data1_dtype

+ 0
- 69
example/resnet50_imagenet2012_THOR/cus_ops/fused_abs_max1.py View File

@@ -1,69 +0,0 @@
# 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.
# ============================================================================
"""CusFusedAbsMax1"""
from mindspore.ops.op_info_register import op_info_register


@op_info_register("""{
"op_name": "CusFusedAbsMax1",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "fusedabsmax1.so",
"compute_cost": 10,
"kernel_name": "CusFusedAbsMax1",
"partial_flag": true,
"attr": [
{
"name": "origin_shape",
"param_type": "required",
"type": "listInt",
"value": "all"
}
],
"inputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusFusedAbsMax1(input_x, output, origin_shape=None, kernel_name="fused_abs_max1"):
"""CusFusedAbsMax1"""
return

+ 0
- 87
example/resnet50_imagenet2012_THOR/cus_ops/img2col_impl.py View File

@@ -1,87 +0,0 @@
# 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.
# ============================================================================
"""CusImg2ColNC1HWC0"""
from mindspore.ops.op_info_register import op_info_register


@op_info_register("""{
"op_name": "CusImg2ColNC1HWC0",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "img2colnc1hwc0.so",
"compute_cost": 10,
"kernel_name": "CusImg2ColNC1HWC0",
"partial_flag": true,
"attr": [
{
"name": "ksizes",
"param_type": "required",
"type": "listInt",
"value": "all"
},
{
"name": "strides",
"param_type": "required",
"type": "listInt",
"value": "all"
},
{
"name": "dilates",
"param_type": "required",
"type": "listInt",
"value": "all"
},
{
"name": "padding",
"param_type": "required",
"type": "str",
"value": "all"
}
],
"inputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"NC1HWC0"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"FRACTAL_NZ"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusImg2ColNC1HWC0(input_x, output, ksizes, strides, dilates, padding, kernel_name="img2col"):
"""CusImg2ColNC1HWC0"""
return

+ 0
- 102
example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_dense_left.py View File

@@ -1,102 +0,0 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
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 == 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.

matmul
"""
from __future__ import absolute_import

from mindspore.ops.op_info_register import op_info_register
from topi.cce import util

# General limitation of the size for input shape: 2**31
SHAPE_SIZE_LIMIT = 2147483648
NoneType = type(None)


@op_info_register("""{
"op_name": "CusMatMulCubeDenseLeft",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "matmulcubedenseleft.so",
"compute_cost": 10,
"kernel_name": "CusMatMulCubeDenseLeft",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 1,
"dtype": [
"float16"
],
"format": [
"FRACTAL_NZ"
],
"name": "x2",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 2,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x3",
"need_compile": false,
"param_type": "optional",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"FRACTAL_NZ"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
@util.check_input_type(dict, dict, (dict, NoneType), dict, bool, bool, str)
def CusMatMulCubeDenseLeft(input_x1, input_x2, bias=None, output_y={}, trans_a=False, trans_b=False,
kernel_name="matmulcube"):
"""CusMatMulCubeDenseLeft"""
return

+ 0
- 103
example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_fracz_left_cast_impl.py View File

@@ -1,103 +0,0 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
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 == 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.

matmul
"""
from __future__ import absolute_import

from mindspore.ops.op_info_register import op_info_register
from topi.cce import util

# General limitation of the size for input shape: 2**31
SHAPE_SIZE_LIMIT = 2147483648
NoneType = type(None)


@op_info_register("""{
"op_name": "CusMatMulCubeFraczLeftCast",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "matmulcubefraczleftcast.so",
"compute_cost": 10,
"kernel_name": "CusMatMulCubeFraczLeftCast",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 1,
"dtype": [
"float32"
],
"format": [
"FracZ"
],
"name": "x2",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 2,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x3",
"need_compile": false,
"param_type": "optional",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"FracZ"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
# pylint: disable=locally-disabled,too-many-arguments, too-many-locals, too-many-statements
@util.check_input_type(dict, dict, (dict, NoneType), dict, bool, bool, str)
def CusMatMulCubeFraczLeftCast(input_x1, input_x2, bias=None, output_y={}, trans_a=False, trans_b=False,
kernel_name="CusMatMulCubeFraczLeftCast"):
"""CusMatMulCubeFraczLeftCast"""
return

+ 0
- 113
example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_fracz_right_mul_impl.py View File

@@ -1,113 +0,0 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
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 == 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.

matmul
"""
from __future__ import absolute_import

from mindspore.ops.op_info_register import op_info_register

# General limitation of the size for input shape: 2**31
SHAPE_SIZE_LIMIT = 2147483648
NoneType = type(None)


@op_info_register("""{
"op_name": "CusMatMulCubeFraczRightMul",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "matmulcubefraczrightmul.so",
"compute_cost": 10,
"kernel_name": "CusMatMulCubeFraczRightMul",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"FracZ"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 1,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x2",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 2,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "x3",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 3,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x4",
"need_compile": false,
"param_type": "optional",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"FracZ"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusMatMulCubeFraczRightMul(input_x1, input_x2, input_x3, bias=None, output_y={}, trans_a=False, trans_b=False,
kernel_name="matmulcube"):
"""CusMatMulCubeFraczRightMul"""
return

+ 0
- 114
example/resnet50_imagenet2012_THOR/cus_ops/matmul_cube_impl.py View File

@@ -1,114 +0,0 @@
#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
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 == 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.

matmul
"""
from __future__ import absolute_import

from mindspore.ops.op_info_register import op_info_register
from topi.cce import util

# General limitation of the size for input shape: 2**31
SHAPE_SIZE_LIMIT = 2147483648
NoneType = type(None)


@op_info_register("""{
"op_name": "CusMatMulCube",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "matmulcube.so",
"compute_cost": 10,
"kernel_name": "CusMatMulCube",
"partial_flag": true,
"attr": [
{
"name": "transpose_a",
"param_type": "required",
"type": "bool",
"value": "all"
},
{
"name": "transpose_b",
"param_type": "required",
"type": "bool",
"value": "all"
}
],
"inputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"FRACTAL_NZ"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 1,
"dtype": [
"float16"
],
"format": [
"FRACTAL_NZ"
],
"name": "x2",
"need_compile": false,
"param_type": "required",
"shape": "all"
},
{
"index": 2,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "x3",
"need_compile": false,
"param_type": "optional",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"FRACTAL_NZ"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
# pylint: disable=locally-disabled,too-many-arguments, too-many-locals, too-many-statements
@util.check_input_type(dict, dict, (dict, NoneType), dict, bool, bool, str)
def CusMatMulCube(input_x1, input_x2, bias=None, output_y={}, trans_a=False, trans_b=False, kernel_name="matmulcube"):
"""CusMatMulCube"""
return

+ 0
- 63
example/resnet50_imagenet2012_THOR/cus_ops/matrix_combine_impl.py View File

@@ -1,63 +0,0 @@
# 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.
# ============================================================================
"""CusMatrixCombine"""
from mindspore.ops.op_info_register import op_info_register


@op_info_register("""{
"op_name": "CusMatrixCombine",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "matrixcombine.so",
"compute_cost": 10,
"kernel_name": "CusMatrixCombine",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float32"
],
"format": [
"DefaultFormat"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusMatrixCombine(input_x, output, kernel_name="matrix_combine"):
"""CusMatrixCombine"""
return

+ 0
- 63
example/resnet50_imagenet2012_THOR/cus_ops/transpose02314_impl.py View File

@@ -1,63 +0,0 @@
# 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.
# ============================================================================
"""CusTranspose02314"""
from mindspore.ops.op_info_register import op_info_register


@op_info_register("""{
"op_name": "CusTranspose02314",
"imply_type": "TBE",
"fusion_type": "OPAQUE",
"async_flag": false,
"binfile_name": "transpose02314.so",
"compute_cost": 10,
"kernel_name": "CusTranspose02314",
"partial_flag": true,
"attr": [
],
"inputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"NC1HWC0"
],
"name": "x1",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
],
"outputs": [
{
"index": 0,
"dtype": [
"float16"
],
"format": [
"DefaultFormat"
],
"name": "y",
"need_compile": false,
"param_type": "required",
"shape": "all"
}
]
}""")
def CusTranspose02314(input_x, output, kernel_name="transpose021354"):
"""CusTranspose02314"""
return

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