Skip to content

A
akg

Guile_ / akg
与 Fork 源项目一致

Fork自 MindSpore / akg

通知 1
Star 0
Fork 0
A
akg

体验新版 GitCode，发现更多精彩内容 >>

提交 4200d597 编写于 作者: M mindspore-ci-bot 提交者： Gitee
浏览文件
操作

!14 add composite benchmark in akg 

Merge pull request !14 from dylangeng/benchmark
上级 34d89438 0d495b6a
隐藏空白更改
内联 并排
Showing with 1558 addition and 0 deletion
tests/perf_benchmark/benchmark/json_benchmark/case1.json 0 → 100644
浏览文件 @ 4200d597
{
"composite": true,
"input_desc": [
[
{
"data_type": "float32",
"shape": [
32,
16,
56,
56,
16
],
"tensor_name": "input_14"
}
],
[
{
"data_type": "float32",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_0"
}
],
[
{
"data_type": "float32",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_3"
}
],
[
{
"data_type": "float32",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_9"
}
],
[
{
"data_type": "float32",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_12"
}
]
],
"op": "Fused_Poly_Schedule_Opt_001",
"op_desc": [
{
"attr": [
{
"name": "x_shape",
"value": [
256
]
},
{
"name": "y_shape",
"value": [
1
]
},
{
"name": "data_format",
"value": [
"NC1HWC0",
"NC1HWC0"
]
}
],
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_0"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1
],
"tensor_name": "input_1",
"value": 9.964923265215475e-06
}
]
],
"name": "Mul",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_0"
}
]
},
{
"attr": [
{
"name": "x_shape",
"value": [
256
]
},
{
"name": "y_shape",
"value": [
256
]
},
{
"name": "data_format",
"value": [
"NC1HWC0",
"NC1HWC0"
]
}
],
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_0"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_0"
}
]
],
"name": "Mul",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_1"
}
]
},
{
"attr": [
{
"name": "x_shape",
"value": [
256
]
},
{
"name": "y_shape",
"value": [
1
]
},
{
"name": "data_format",
"value": [
"NC1HWC0",
"NC1HWC0"
]
}
],
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_3"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1
],
"tensor_name": "input_1",
"value": 9.964923265215475e-06
}
]
],
"name": "Mul",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_2"
}
]
},
{
"attr": null,
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_2"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_1"
}
]
],
"name": "Sub",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_3"
}
]
},
{
"attr": null,
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_3"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1
],
"tensor_name": "input_7",
"value": 9.999999747378752e-06
}
]
],
"name": "TensorAdd",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_4"
}
]
},
{
"attr": null,
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_4"
}
]
],
"name": "Sqrt",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_5"
}
]
},
{
"attr": null,
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_9"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_5"
}
]
],
"name": "RealDiv",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_6"
}
]
},
{
"attr": [
{
"name": "x_shape",
"value": [
256
]
},
{
"name": "y_shape",
"value": [
256
]
},
{
"name": "data_format",
"value": [
"NC1HWC0",
"NC1HWC0"
]
}
],
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_6"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_0"
}
]
],
"name": "Mul",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_7"
}
]
},
{
"attr": null,
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "input_12"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_7"
}
]
],
"name": "Sub",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_8"
}
]
},
{
"attr": [
{
"name": "x_shape",
"value": [
256
]
},
{
"name": "y_shape",
"value": [
32,
256,
56,
56
]
},
{
"name": "data_format",
"value": [
"NC1HWC0",
"NC1HWC0"
]
}
],
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_6"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
32,
16,
56,
56,
16
],
"tensor_name": "input_14"
}
]
],
"name": "Mul",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
32,
16,
56,
56,
16
],
"tensor_name": "output_0_9"
}
]
},
{
"attr": null,
"impl_path": "",
"input_desc": [
[
{
"data_type": "float32",
"name": "x",
"shape": [
32,
16,
56,
56,
16
],
"tensor_name": "output_0_9"
}
],
[
{
"data_type": "float32",
"name": "y",
"shape": [
1,
16,
1,
1,
16
],
"tensor_name": "output_0_8"
}
]
],
"name": "TensorAdd",
"output_desc": [
{
"data_type": "float32",
"name": "output",
"shape": [
32,
16,
56,
56,
16
],
"tensor_name": "output_0_10"
}
]
}
],
"output_desc": [
{
"data_type": "float32",
"shape": [
32,
16,
56,
56,
16
],
"tensor_name": "output_0_10"
}
],
"platform": "AKG",
"process": "aicore"
}
\ No newline at end of file
tests/perf_benchmark/benchmark/json_benchmark/case10.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"10313","input_desc":[[{"data_type":"float16","shape":[16,1,1,512],"tensor_name":"input_2"}],[{"data_type":"float16","shape":[16,16,512,512],"tensor_name":"input_1"}]],"op":"Fused_Mul_Mul_TensorAdd__4400644352246048056","op_desc":[{"attr":[{"name":"x_shape","value":[1]},{"name":"y_shape","value":[16,16,512,512]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[1],"tensor_name":"input_0","value":0.125}],[{"data_type":"float16","name":"y","shape":[16,16,512,512],"tensor_name":"input_1"}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[16,16,512,512],"tensor_name":"output_0_0"}]},{"attr":[{"name":"x_shape","value":[16,1,1,512]},{"name":"y_shape","value":[1]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[16,1,1,512],"tensor_name":"input_2"}],[{"data_type":"float16","name":"y","shape":[1],"tensor_name":"input_3","value":-10000.0}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[16,1,1,512],"tensor_name":"output_0_1"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[16,1,1,512],"tensor_name":"output_0_1"}],[{"data_type":"float16","name":"y","shape":[16,16,512,512],"tensor_name":"output_0_0"}]],"name":"TensorAdd","output_desc":[{"data_type":"float16","name":"output","shape":[16,16,512,512],"tensor_name":"output_0_2"}]}],"output_desc":[{"data_type":"float16","shape":[16,1,1,512],"tensor_name":"output_0_1"},{"data_type":"float16","shape":[16,16,512,512],"tensor_name":"output_0_2"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/json_benchmark/case2.json 0 → 100644
浏览文件 @ 4200d597
{
"composite": true,
"input_desc": [
[{
"data_type": "float16",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "input_0"
}],
[{
"data_type": "float16",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "input_9"
}],
[{
"data_type": "float32",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "input_7"
}],
[{
"data_type": "float32",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "input_2"
}]
],
"op": "Fused_Poly_Schedule_Opt_002",
"op_desc": [{
"attr": [{
"name": "dst_type",
"value": "float32"
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float16",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "input_0"
}]
],
"name": "Cast",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_0"
}]
}, {
"attr": [{
"name": "axis",
"value": [0, 2, 3]
}, {
"name": "keep_dims",
"value": true
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_0"
}]
],
"name": "ReduceSum",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_1"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "input_2"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1],
"tensor_name": "input_3",
"value": 9.999999747378752e-05
}]
],
"name": "TensorAdd",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_2"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_2"
}]
],
"name": "Sqrt",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_3"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1],
"tensor_name": "input_5",
"value": 1.0
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_3"
}]
],
"name": "RealDiv",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_4"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [256]
}, {
"name": "y_shape",
"value": []
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "input_7"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1],
"tensor_name": "input_8",
"value": -1.0
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_5"
}]
}, {
"attr": [{
"name": "dst_type",
"value": "float32"
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float16",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "input_9"
}]
],
"name": "Cast",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_6"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_6"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_5"
}]
],
"name": "TensorAdd",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_7"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [32, 256, 56, 56]
}, {
"name": "y_shape",
"value": [256]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_7"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_4"
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_8"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [32, 256, 56, 56]
}, {
"name": "y_shape",
"value": [32, 256, 56, 56]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_0"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_8"
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_9"
}]
}, {
"attr": [{
"name": "axis",
"value": [0, 2, 3]
}, {
"name": "keep_dims",
"value": true
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 16, 56, 56, 16],
"tensor_name": "output_0_9"
}]
],
"name": "ReduceSum",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_10"
}]
}],
"output_desc": [{
"data_type": "float32",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_10"
}, {
"data_type": "float32",
"shape": [1, 16, 1, 1, 16],
"tensor_name": "output_0_1"
}],
"platform": "AKG",
"process": "aicore"
}
tests/perf_benchmark/benchmark/json_benchmark/case3.json 0 → 100644
浏览文件 @ 4200d597
{
"composite": true,
"input_desc": [
[{
"data_type": "float16",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "input_19"
}],
[{
"data_type": "float16",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "input_14"
}],
[{
"data_type": "float32",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_7"
}],
[{
"data_type": "float32",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_5"
}],
[{
"data_type": "float32",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_3"
}],
[{
"data_type": "float32",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_9"
}],
[{
"data_type": "float32",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_0"
}]
],
"op": "Fused_Poly_Schedule_Opt_003",
"op_desc": [{
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_0"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1],
"tensor_name": "input_1",
"value": 9.999999747378752e-05
}]
],
"name": "TensorAdd",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_0"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_0"
}]
],
"name": "Sqrt",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_1"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_3"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_1"
}]
],
"name": "RealDiv",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_2"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [64]
}, {
"name": "y_shape",
"value": [1]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_5"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1],
"tensor_name": "input_6",
"value": -9.964923265215475e-06
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_3"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [64]
}, {
"name": "y_shape",
"value": [1]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_7"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1],
"tensor_name": "input_8",
"value": 9.964923265215475e-06
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_4"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_9"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_1"
}]
],
"name": "RealDiv",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_5"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [64]
}, {
"name": "y_shape",
"value": [64]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_5"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_4"
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_6"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_6"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_3"
}]
],
"name": "TensorAdd",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_7"
}]
}, {
"attr": [{
"name": "dst_type",
"value": "float32"
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float16",
"name": "x",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "input_14"
}]
],
"name": "Cast",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_8"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [64]
}, {
"name": "y_shape",
"value": [1]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "input_7"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1],
"tensor_name": "input_15",
"value": -9.964923265215475e-06
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_9"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_9"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_1"
}]
],
"name": "RealDiv",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_10"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [64]
}, {
"name": "y_shape",
"value": [32, 64, 56, 56]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_10"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_8"
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_11"
}]
}, {
"attr": [{
"name": "dst_type",
"value": "float32"
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float16",
"name": "x",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "input_19"
}]
],
"name": "Cast",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_12"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_12"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_11"
}]
],
"name": "TensorAdd",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_13"
}]
}, {
"attr": null,
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_13"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_7"
}]
],
"name": "TensorAdd",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_14"
}]
}, {
"attr": [{
"name": "x_shape",
"value": [32, 64, 56, 56]
}, {
"name": "y_shape",
"value": [64]
}, {
"name": "data_format",
"value": ["NC1HWC0", "NC1HWC0"]
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_14"
}],
[{
"data_type": "float32",
"name": "y",
"shape": [1, 4, 1, 1, 16],
"tensor_name": "output_0_2"
}]
],
"name": "Mul",
"output_desc": [{
"data_type": "float32",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_15"
}]
}, {
"attr": [{
"name": "dst_type",
"value": "float16"
}],
"impl_path": "",
"input_desc": [
[{
"data_type": "float32",
"name": "x",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_15"
}]
],
"name": "Cast",
"output_desc": [{
"data_type": "float16",
"name": "output",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_16"
}]
}],
"output_desc": [{
"data_type": "float16",
"shape": [32, 4, 56, 56, 16],
"tensor_name": "output_0_16"
}],
"platform": "AKG",
"process": "aicore"
}
\ No newline at end of file
tests/perf_benchmark/benchmark/json_benchmark/case4_logsoftmax.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"14745","input_desc":[[{"data_type":"float32","shape":[1216,30052],"tensor_name":"input_1"}],[{"data_type":"float32","shape":[1216,30052],"tensor_name":"input_0"}]],"op":"Fused_LogSoftmax_16500795147666726961","op_desc":[{"attr":[{"name":"axis","value":[-1]},{"name":"keep_dims","value":true}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1216,30052],"tensor_name":"input_0"}]],"name":"ReduceSum","output_desc":[{"data_type":"float32","name":"output","shape":[1216,1],"tensor_name":"output_0_0"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1216,30052],"tensor_name":"input_1"}]],"name":"Exp","output_desc":[{"data_type":"float32","name":"output","shape":[1216,30052],"tensor_name":"output_0_1"}]},{"attr":[{"name":"x_shape","value":[1216,30052]},{"name":"y_shape","value":[1216,1]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1216,30052],"tensor_name":"output_0_1"}],[{"data_type":"float32","name":"y","shape":[1216,1],"tensor_name":"output_0_0"}]],"name":"Mul","output_desc":[{"data_type":"float32","name":"output","shape":[1216,30052],"tensor_name":"output_0_2"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1216,30052],"tensor_name":"input_0"}],[{"data_type":"float32","name":"y","shape":[1216,30052],"tensor_name":"output_0_2"}]],"name":"Sub","output_desc":[{"data_type":"float32","name":"output","shape":[1216,30052],"tensor_name":"output_0_3"}]},{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1216,30052],"tensor_name":"output_0_3"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1216,30052],"tensor_name":"output_0_4"}]}],"output_desc":[{"data_type":"float32","shape":[1216,30052],"tensor_name":"output_0_3"},{"data_type":"float16","shape":[1216,30052],"tensor_name":"output_0_4"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/json_benchmark/case5_reciprocal.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"12299","input_desc":[[{"data_type":"float32","shape":[],"tensor_name":"input_0"}],[{"data_type":"float32","shape":[1216,30522],"tensor_name":"input_1"}]],"op":"Fused_Reciprocal_ReduceSum_Mul___1222261331617186059","op_desc":[{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1],"tensor_name":"input_0"}]],"name":"Reciprocal","output_desc":[{"data_type":"float32","name":"output","shape":[],"tensor_name":"output_0_0"}]},{"attr":[{"name":"axis","value":[0]},{"name":"keep_dims","value":false}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1216,30522],"tensor_name":"input_1"}]],"name":"ReduceSum","output_desc":[{"data_type":"float32","name":"output","shape":[30522],"tensor_name":"output_0_1"}]},{"attr":[{"name":"x_shape","value":[30522]},{"name":"y_shape","value":[]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[30522],"tensor_name":"output_0_1"}],[{"data_type":"float32","name":"y","shape":[1],"tensor_name":"output_0_0"}]],"name":"Mul","output_desc":[{"data_type":"float32","name":"output","shape":[30522],"tensor_name":"output_0_2"}]}],"output_desc":[{"data_type":"float32","shape":[1],"tensor_name":"output_0_0"},{"data_type":"float32","shape":[30522],"tensor_name":"output_0_2"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/json_benchmark/case6_mul_mul.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"10313","input_desc":[[{"data_type":"float16","shape":[16,1,1,512],"tensor_name":"input_2"}],[{"data_type":"float16","shape":[16,16,512,512],"tensor_name":"input_1"}]],"op":"Fused_Mul_Mul_TensorAdd__4400644352246048056","op_desc":[{"attr":[{"name":"x_shape","value":[1]},{"name":"y_shape","value":[16,16,512,512]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[1],"tensor_name":"input_0","value":0.125}],[{"data_type":"float16","name":"y","shape":[16,16,512,512],"tensor_name":"input_1"}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[16,16,512,512],"tensor_name":"output_0_0"}]},{"attr":[{"name":"x_shape","value":[16,1,1,512]},{"name":"y_shape","value":[1]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[16,1,1,512],"tensor_name":"input_2"}],[{"data_type":"float16","name":"y","shape":[1],"tensor_name":"input_3","value":-10000.0}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[16,1,1,512],"tensor_name":"output_0_1"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[16,1,1,512],"tensor_name":"output_0_1"}],[{"data_type":"float16","name":"y","shape":[16,16,512,512],"tensor_name":"output_0_0"}]],"name":"TensorAdd","output_desc":[{"data_type":"float16","name":"output","shape":[16,16,512,512],"tensor_name":"output_0_2"}]}],"output_desc":[{"data_type":"float16","shape":[16,1,1,512],"tensor_name":"output_0_1"},{"data_type":"float16","shape":[16,16,512,512],"tensor_name":"output_0_2"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/json_benchmark/case7_mul_mul.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"11288","input_desc":[[{"data_type":"float32","shape":[1024],"tensor_name":"input_1"}],[{"data_type":"float32","shape":[1024],"tensor_name":"input_0"}],[{"data_type":"float16","shape":[8192,1024],"tensor_name":"input_2"}]],"op":"Fused_Cast_Cast_Mul_TensorAdd___12292245117929986167","op_desc":[{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1024],"tensor_name":"input_0"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1024],"tensor_name":"output_0_0"}]},{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1024],"tensor_name":"input_1"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1024],"tensor_name":"output_0_1"}]},{"attr":[{"name":"x_shape","value":[8192,1024]},{"name":"y_shape","value":[1024]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[8192,1024],"tensor_name":"input_2"}],[{"data_type":"float16","name":"y","shape":[1024],"tensor_name":"output_0_1"}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[8192,1024],"tensor_name":"output_0_2"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[8192,1024],"tensor_name":"output_0_2"}],[{"data_type":"float16","name":"y","shape":[1024],"tensor_name":"output_0_0"}]],"name":"TensorAdd","output_desc":[{"data_type":"float16","name":"output","shape":[8192,1024],"tensor_name":"output_0_3"}]}],"output_desc":[{"data_type":"float16","shape":[1024],"tensor_name":"output_0_1"},{"data_type":"float16","shape":[8192,1024],"tensor_name":"output_0_3"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/json_benchmark/case8_cast_cast.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"11288","input_desc":[[{"data_type":"float32","shape":[1024],"tensor_name":"input_1"}],[{"data_type":"float32","shape":[1024],"tensor_name":"input_0"}],[{"data_type":"float16","shape":[8192,1024],"tensor_name":"input_2"}]],"op":"Fused_Cast_Cast_Mul_TensorAdd___12292245117929986167","op_desc":[{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1024],"tensor_name":"input_0"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1024],"tensor_name":"output_0_0"}]},{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1024],"tensor_name":"input_1"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1024],"tensor_name":"output_0_1"}]},{"attr":[{"name":"x_shape","value":[8192,1024]},{"name":"y_shape","value":[1024]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[8192,1024],"tensor_name":"input_2"}],[{"data_type":"float16","name":"y","shape":[1024],"tensor_name":"output_0_1"}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[8192,1024],"tensor_name":"output_0_2"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[8192,1024],"tensor_name":"output_0_2"}],[{"data_type":"float16","name":"y","shape":[1024],"tensor_name":"output_0_0"}]],"name":"TensorAdd","output_desc":[{"data_type":"float16","name":"output","shape":[8192,1024],"tensor_name":"output_0_3"}]}],"output_desc":[{"data_type":"float16","shape":[1024],"tensor_name":"output_0_1"},{"data_type":"float16","shape":[8192,1024],"tensor_name":"output_0_3"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/json_benchmark/case9.json 0 → 100644
浏览文件 @ 4200d597
{"composite":true,"composite_graph":"11288","input_desc":[[{"data_type":"float32","shape":[1024],"tensor_name":"input_1"}],[{"data_type":"float32","shape":[1024],"tensor_name":"input_0"}],[{"data_type":"float16","shape":[8192,1024],"tensor_name":"input_2"}]],"op":"Fused_Cast_Cast_Mul_TensorAdd___12292245117929986167","op_desc":[{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1024],"tensor_name":"input_0"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1024],"tensor_name":"output_0_0"}]},{"attr":[{"name":"dst_type","value":"float16"}],"impl_path":"","input_desc":[[{"data_type":"float32","name":"x","shape":[1024],"tensor_name":"input_1"}]],"name":"Cast","output_desc":[{"data_type":"float16","name":"output","shape":[1024],"tensor_name":"output_0_1"}]},{"attr":[{"name":"x_shape","value":[8192,1024]},{"name":"y_shape","value":[1024]},{"name":"data_format","value":["DefaultFormat","DefaultFormat"]}],"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[8192,1024],"tensor_name":"input_2"}],[{"data_type":"float16","name":"y","shape":[1024],"tensor_name":"output_0_1"}]],"name":"Mul","output_desc":[{"data_type":"float16","name":"output","shape":[8192,1024],"tensor_name":"output_0_2"}]},{"attr":null,"impl_path":"","input_desc":[[{"data_type":"float16","name":"x","shape":[8192,1024],"tensor_name":"output_0_2"}],[{"data_type":"float16","name":"y","shape":[1024],"tensor_name":"output_0_0"}]],"name":"TensorAdd","output_desc":[{"data_type":"float16","name":"output","shape":[8192,1024],"tensor_name":"output_0_3"}]}],"output_desc":[{"data_type":"float16","shape":[1024],"tensor_name":"output_0_1"},{"data_type":"float16","shape":[8192,1024],"tensor_name":"output_0_3"}],"platform":"AKG","process":"aicore"}
tests/perf_benchmark/benchmark/network_benchmark_op.py 0 → 100644
浏览文件 @ 4200d597
import boot
def test_compile_too_long():
boot.run("conv_backprop_filter_run_019", "conv_filter_ad_run", ((32, 128, 56, 56), (128, 128, 3, 3), (0, 1, 0, 1), (2, 2), (1, 1))),
boot.run("conv_backprop_filter_run_010", "conv_backprop_filter_run", ((1, 3, 224, 224),(64, 3, 7, 7),(3, 3, 3, 3),(2, 2),(1, 1))),
def test_resnet_benchmark():
boot.run("resnet50_maxpool_with_argmax_000", "maxpool_with_argmax_run", ((32, 4, 112, 112, 16), (3, 3), (2, 2), 'SAME', True, "float16")),
boot.run("resnet50_bn_split_005", "bn_split_run", ((32, 4, 112, 112, 16), "float32", 0.1, 1e-4, "resnet50_bn_split")),
boot.run("resnet50_conv_bn1_026", "conv_bn1_run", ((32, 3, 224, 224), (64, 3, 7, 7), (2, 3, 2, 3), (2, 2), (1, 1), False)),
boot.run("resnet50_four2five_003", "four2five_run", ([32, 3, 224, 224], "float16", "NCHW", "float16")),
boot.run("resnet50_softmax_004", "softmax_run", ((32, 1001), "float32", -1, "softmax_32")),
boot.run("resnet50_apply_momentum_002", "apply_momentum_run", ((128, 32, 16, 16), "float32", False)),
boot.run("resnet50_mean_000", "mean_run", ((32, 128, 7, 7, 16), "float32", (2, 3), True, "cce_mean")),
def test_bert_benchmark():
boot.run("bert_batch_matmul_003_242", "batchmatmul_run", ((), 4096, 3072, 768, (3072, ), "float32", False, True, "batch_matmul_output")),
boot.run("fused_layernorm_002_1280_1024", "fused_layernorm_run", ((1280, 1024), 1, -1, 'float16')),
boot.run("logsoftmax_grad_002", "logsoftmax_grad_run", ((160, 30522), "float32", -1, "cce_logsoftmax_fp16")),
boot.run("unsortedsegmentsum_002", "unsortedsegmentsum_run", ([1280, 1024], [1280], 8192, "float32")),
boot.run("transpose_002", "transpose_run", ((8, 16, 128, 64), (0, 2, 1, 3), "float32")),
boot.run("fused_layer_norm_grad_01", "fused_layer_norm_grad_run", ((8192, 1024), -1, -1, "float16")),
boot.run("logsoftmax_002_fp32", "logsoftmax_run", ((160, 30522), "float32", -1, "cce_logsoftmax_fp32")),
boot.run("strided_slice_grad_002", "strided_slice_grad_run",((128, 128, 768), [0, 0, 0], [128, 1, 768], [1, 1, 1], 0, 0, 0, 0, 0, (128, 1, 768), "int32"))
\ No newline at end of file
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或