p60975123
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

!18537 fix type error in profiler 

Merge pull request !18537 from yanghaitao/yht_fix_vm_type
This commit is contained in:
i-robot 2021-06-22 06:40:01 +00:00 committed by Gitee
parent 0a3f364372 d2c01a2ff1
commit 9dfc43cf32
2 changed files with 22 additions and 21 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

35
mindspore/profiler/parser/framework_parser.py
View File

@ -30,23 +30,24 @@ from mindspore.profiler.common.validator.validate_path import \
class VmDataType(enum.IntEnum):
"""Definition of vm data type."""
NUMBER_TYPE_BEGIN = 26
NUMBER_TYPE_BOOL = 27
NUMBER_TYPE_INT = 28
NUMBER_TYPE_INT8 = 29
NUMBER_TYPE_INT16 = 30
NUMBER_TYPE_INT32 = 31
NUMBER_TYPE_INT64 = 32
NUMBER_TYPE_UINT = 33
NUMBER_TYPE_UINT8 = 34
NUMBER_TYPE_UINT16 = 35
NUMBER_TYPE_UINT32 = 36
NUMBER_TYPE_UINT64 = 37
NUMBER_TYPE_FLOAT = 38
NUMBER_TYPE_FLOAT16 = 39
NUMBER_TYPE_FLOAT32 = 40
NUMBER_TYPE_FLOAT64 = 41
NUMBER_TYPE_END = 42
NUMBER_TYPE_BEGIN = 30
NUMBER_TYPE_BOOL = 31
NUMBER_TYPE_INT = 32
NUMBER_TYPE_INT8 = 33
NUMBER_TYPE_INT16 = 34
NUMBER_TYPE_INT32 = 35
NUMBER_TYPE_INT64 = 36
NUMBER_TYPE_UINT = 37
NUMBER_TYPE_UINT8 = 38
NUMBER_TYPE_UINT16 = 39
NUMBER_TYPE_UINT32 = 40
NUMBER_TYPE_UINT64 = 41
NUMBER_TYPE_FLOAT = 42
NUMBER_TYPE_FLOAT16 = 43
NUMBER_TYPE_FLOAT32 = 44
NUMBER_TYPE_FLOAT64 = 45
NUMBER_TYPE_COMPLEX = 46
NUMBER_TYPE_END = 47
@classmethod
def get_data_type_name(cls, num):

8
tests/ut/data/profiler_data/profiler/framework_raw_0.csv
View File

@ -1,5 +1,5 @@
task_id,stream_id,block_dim,full_op_name,op_name,op_type,subgraph,op_info
51517,0,32,Default/Cast-op6,Cast-op6,Cast,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,3,224,224""}}"
51518,0,32,Default/TransData-op7,TransData-op7,TransData,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""32,1,224,224,16""}}"
51519,0,32,Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5,Cast-op5,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""49,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""49,4,16,16""}}"
51522,0,4,Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28,Cast-op28,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT32"", ""shape"": ""4,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_FLOAT16"", ""shape"": ""4,4,16,16""}}"
51517,0,32,Default/Cast-op6,Cast-op6,Cast,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_UINT32"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_UINT16"", ""shape"": ""32,3,224,224""}}"
51518,0,32,Default/TransData-op7,TransData-op7,TransData,Default,"{""input_0"": {""format"": ""DefaultFormat"", ""data_type"": ""NUMBER_TYPE_UINT16"", ""shape"": ""32,3,224,224""}, ""output_0"": {""format"": ""NC1HWC0"", ""data_type"": ""NUMBER_TYPE_UINT16"", ""shape"": ""32,1,224,224,16""}}"
51519,0,32,Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5,Cast-op5,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_UINT32"", ""shape"": ""49,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_UINT16"", ""shape"": ""49,4,16,16""}}"
51522,0,4,Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28,Cast-op28,Cast,Default,"{""input_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_UINT32"", ""shape"": ""4,4,16,16""}, ""output_0"": {""format"": ""FracZ"", ""data_type"": ""NUMBER_TYPE_UINT16"", ""shape"": ""4,4,16,16""}}"

1 task_id stream_id block_dim full_op_name op_name op_type subgraph op_info
2 51517 0 32 Default/Cast-op6 Cast-op6 Cast Default {"input_0": {"format": "DefaultFormat", "data_type": "NUMBER_TYPE_FLOAT32", "shape": "32,3,224,224"}, "output_0": {"format": "DefaultFormat", "data_type": "NUMBER_TYPE_FLOAT16", "shape": "32,3,224,224"}} {"input_0": {"format": "DefaultFormat", "data_type": "NUMBER_TYPE_UINT32", "shape": "32,3,224,224"}, "output_0": {"format": "DefaultFormat", "data_type": "NUMBER_TYPE_UINT16", "shape": "32,3,224,224"}}
3 51518 0 32 Default/TransData-op7 TransData-op7 TransData Default {"input_0": {"format": "DefaultFormat", "data_type": "NUMBER_TYPE_FLOAT16", "shape": "32,3,224,224"}, "output_0": {"format": "NC1HWC0", "data_type": "NUMBER_TYPE_FLOAT16", "shape": "32,1,224,224,16"}} {"input_0": {"format": "DefaultFormat", "data_type": "NUMBER_TYPE_UINT16", "shape": "32,3,224,224"}, "output_0": {"format": "NC1HWC0", "data_type": "NUMBER_TYPE_UINT16", "shape": "32,1,224,224,16"}}
4 51519 0 32 Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5 Cast-op5 Cast Default {"input_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_FLOAT32", "shape": "49,4,16,16"}, "output_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_FLOAT16", "shape": "49,4,16,16"}} {"input_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_UINT32", "shape": "49,4,16,16"}, "output_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_UINT16", "shape": "49,4,16,16"}}
5 51522 0 4 Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28 Cast-op28 Cast Default {"input_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_FLOAT32", "shape": "4,4,16,16"}, "output_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_FLOAT16", "shape": "4,4,16,16"}} {"input_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_UINT32", "shape": "4,4,16,16"}, "output_0": {"format": "FracZ", "data_type": "NUMBER_TYPE_UINT16", "shape": "4,4,16,16"}}