Environment Variables
Linux Ascend GPU CPU Beginner Intermediate Expert
MindSpore environment variables are as follows:
Environment Variable |
Module |
Function |
Type |
Value Range |
Configuration Relationship |
Mandatory or Not |
|---|---|---|---|---|---|---|
MS_ENABLE_CACHE |
MindData |
Determines whether to enable the cache function for datasets during data processing to accelerate dataset reading and argumentation processing. |
String |
TRUE: enables the cache function during data processing. |
This variable is used together with MS_CACHE_HOST and MS_CACHE_PORT. |
Optional |
MS_CACHE_HOST |
MindData |
Specifies the IP address of the host where the cache server is located when the cache function is enabled. |
String |
IP address of the host where the cache server is located. |
This variable is used together with MS_ENABLE_CACHE=TRUE and MS_CACHE_PORT. |
Optional |
MS_CACHE_PORT |
MindData |
Specifies the port number of the host where the cache server is located when the cache function is enabled. |
String |
Port number of the host where the cache server is located. |
This variable is used together with MS_ENABLE_CACHE=TRUE and MS_CACHE_HOST. |
Optional |
PROFILING_MODE |
MindData |
Determines whether to enable dataset profiling for performance analysis. This variable is used together with MindInsight where the time consumed in each phase can be displayed. |
String |
true: enables the profiling function. |
This variable is used together with MINDDATA_PROFILING_DIR. |
Optional |
MINDDATA_PROFILING_DIR |
MindData |
Specifies the system path for storing the dataset profiling result. |
String |
System path. A relative path is supported. |
This variable is used together with PROFILING_MODE=true. |
Optional |
DATASET_ENABLE_NUMA |
MindData |
Determines whether to enable numa bind feature. Most of time this configuration can improve performance on distribute scenario. |
String |
True: Enables the numa bind feature. |
This variable is used together with libnuma.so. |
Optional |
OPTIMIZE |
MindData |
Determines whether to optimize the pipeline tree for dataset during data processing. This variable can improve the data processing efficiency in the data processing operator fusion scenario. |
String |
true: enables pipeline tree optimization. |
None |
Optional |
ENABLE_MS_DEBUGGER |
Debugger |
Determines whether to enable Debugger during training. |
Boolean |
1: enables Debugger. |
None |
Optional |
MS_DEBUGGER_PORT |
Debugger |
Specifies the port for connecting to the MindInsight Debugger Server. |
Integer |
Port number ranges from 1 to 65536. |
None |
Optional |
MS_DEBUGGER_PARTIAL_MEM |
Debugger |
Determines whether to enable partial memory overcommitment. (Memory overcommitment is disabled only for nodes selected on Debugger.) |
Boolean |
1: enables memory overcommitment for nodes selected on Debugger. |
None |
Optional |
MS_BUILD_PROCESS_NUM |
MindSpore |
Specifies the number of parallel operator build processes during Ascend backend compilation. |
Integer |
The number of parallel operator build processes ranges from 1 to 24. |
None |
Optional |
RANK_TABLE_FILE |
MindSpore |
Specifies the file to which a path points, including |
String |
File path, which can be a relative path or an absolute path. |
This variable is used together with RANK_SIZE. |
Mandatory (when the Ascend AI Processor is used) |
RANK_SIZE |
MindSpore |
Specifies the number of Ascend AI Processors to be called during deep learning. |
Integer |
The number of Ascend AI Processors to be called ranges from 1 to 8. |
This variable is used together with RANK_TABLE_FILE |
Mandatory (when the Ascend AI Processor is used) |
RANK_ID |
MindSpore |
Specifies the logical ID of the Ascend AI Processor called during deep learning. |
Integer |
The value ranges from 0 to 7. When multiple servers are running concurrently, |
None |
Optional |
MS_SUBMODULE_LOG_v |
MindSpore |
For details about the function and usage, see MS_SUBMODULE_LOG_v |
Dict{String:Integer…} |
LogLevel: 0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR |
None |
Optional |
OPTION_PROTO_LIB_PATH |
MindSpore |
Specifies the RPOTO dependent library path. |
String |
File path, which can be a relative path or an absolute path. |
None |
Optional |
MS_RDR_ENABLE |
MindSpore |
Determines whether to enable running data recorder (RDR). If a running exception occurs in MindSpore, the pre-recorded data in MindSpore is automatically exported to assist in locating the cause of the running exception. |
Integer |
1：enables RDR |
This variable is used together with MS_RDR_PATH |
Optional |
MS_RDR_PATH |
MindSpore |
Specifies the system path for storing the data recorded by running data recorder (RDR). |
String |
Directory path, which should be an absolute path. |
This variable is used together with MS_RDR_ENABLE=1 |
Optional |
GE_USE_STATIC_MEMORY |
GraphEngine |
When a network model has too many layers, the intermediate computing data of a feature map may exceed 25 GB, for example, on the BERT24 network. In the multi-device scenario, to ensure efficient memory collaboration, set this variable to 1, indicating that static memory allocation mode is used. For other networks, dynamic memory allocation mode is used by default. |
Integer |
1: static memory allocation mode |
None |
Optional |
DUMP_GE_GRAPH |
GraphEngine |
Outputs the graph description information of each phase in the entire process to a file. This environment variable controls contents of the dumped graph. |
Integer |
1: full dump |
None |
Optional |
DUMP_GRAPH_LEVEL |
GraphEngine |
Outputs the graph description information of each phase in the entire process to a file. This environment variable controls the number of dumped graphs. |
Integer |
1: dumps all graphs. |
None |
Optional |