forked from mindspore-Ecosystem/mindspore
!23668 Modify error format of docstring for set_context.
Merge pull request !23668 from zhangyi/code_docs_master
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@ -532,36 +532,61 @@ def set_context(**kwargs):
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Some configurations are device specific, see the below table for details:
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======================= =========================== =========================
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Function Classification Configuration Parameters Hardware Platform Support
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======================= =========================== =========================
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System Configuration device_id CPU/GPU/Ascend
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device_target CPU/GPU/Ascend
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max_device_memory GPU
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variable_memory_max_size Ascend
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Debug Configuration save_graphs CPU/GPU/Ascend
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save_graphs_path CPU/GPU/Ascend
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enable_dump Ascend
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save_dump_path Ascend
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enable_profiling Ascend
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profiling_options Ascend
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print_file_path Ascend
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env_config_path CPU/GPU/Ascend
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precompile_only CPU/GPU/Ascend
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reserve_class_name_in_scope CPU/GPU/Ascend
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pynative_synchronize GPU/Ascend
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Executive Control mode CPU/GPU/Ascend
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enable_graph_kernel Ascend/GPU
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graph_kernel_flags Ascend/GPU
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enable_reduce_precision Ascend
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auto_tune_mode Ascend
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check_bprop CPU/GPU/Ascend
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max_call_depth CPU/GPU/Ascend
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enable_sparse CPU/GPU/Ascend
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grad_for_scalar CPU/GPU/Ascend
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save_compile_cache CPU/GPU/Ascend
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load_compile_cache CPU/GPU/Ascend
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======================= =========================== =========================
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+-------------------------+------------------------------+----------------------------+
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| Function Classification | Configuration Parameters | Hardware Platform Support|
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+=========================+==============================+============================+
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| System Configuration | device_id | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | device_target | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | max_device_memory | GPU |
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| +------------------------------+----------------------------+
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| | variable_memory_max_size | Ascend |
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+-------------------------+------------------------------+----------------------------+
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| Debug Configuration | save_graphs | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | save_graphs_path | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | enable_dump | Ascend |
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| +------------------------------+----------------------------+
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| | save_dump_path | Ascend |
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| +------------------------------+----------------------------+
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| | enable_profiling | Ascend |
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| +------------------------------+----------------------------+
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| | profiling_options | Ascend |
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| +------------------------------+----------------------------+
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| | print_file_path | Ascend |
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| +------------------------------+----------------------------+
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| | env_config_path | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | precompile_only | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | reserve_class_name_in_scope | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | pynative_synchronize | GPU/Ascend |
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+-------------------------+------------------------------+----------------------------+
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| Executive Control | mode | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | enable_graph_kernel | Ascend/GPU |
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| +------------------------------+----------------------------+
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| | graph_kernel_flags | Ascend/GPU |
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| +------------------------------+----------------------------+
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| | enable_reduce_precision | Ascend |
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| +------------------------------+----------------------------+
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| | auto_tune_mode | Ascend |
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| +------------------------------+----------------------------+
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| | check_bprop | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | max_call_depth | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | enable_sparse | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | grad_for_scalar | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | save_compile_cache | CPU/GPU/Ascend |
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| +------------------------------+----------------------------+
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| | load_compile_cache | CPU/GPU/Ascend |
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+-------------------------+------------------------------+----------------------------+
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Args:
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device_id (int): ID of the target device, the value must be in [0, device_num_per_host-1],
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@ -617,18 +642,15 @@ def set_context(**kwargs):
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operator name.
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- aic_metrics:
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the values are as follows:
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ArithmeticUtilization:
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percentage statistics of various calculation indicators.
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PipeUtilization:
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the time-consuming ratio of calculation unit and handling unit, this item is
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the values are as follows:
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- ArithmeticUtilization: Percentage statistics of various calculation indicators.
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- PipeUtilization: The time-consuming ratio of calculation unit and handling unit, this item is
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the default value.
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Memory:
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percentage of external memory read and write instructions.
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MemoryL0:
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percentage of internal memory read and write instructions.
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ResourceConflictRatio:
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proportion of pipline queue instructions.
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- Memory: Percentage of external memory read and write instructions.
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- MemoryL0: Percentage of internal memory read and write instructions.
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- ResourceConflictRatio: Proportion of pipline queue instructions.
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The profiling_options is like '{"output":'/home/data/output', 'training_trace':'on'}'
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print_file_path (str): The path of saving print data. If this parameter is set, print data is saved to
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@ -638,21 +660,30 @@ def set_context(**kwargs):
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If it is not set, an error will be reported: prompt to set the upper absolute path.
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env_config_path (str): Config path for DFX.
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Through context.set_context(env_config_path="./mindspore_config.json")
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configure RDR:
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enable: controls whether the RDR is enabled to collects the key data during training and
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saves key data in the fault scenario. When set to true, the RDR will be turned on.
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When set to false, the RDR will be turned off.
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path: sets the path where RDR saves data. The current path must be absolute.
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- enable: controls whether the RDR is enabled to collects the key data during training and
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saves key data in the fault scenario. When set to true, the RDR will be turned on.
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When set to false, the RDR will be turned off.
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- path: sets the path where RDR saves data. The current path must be absolute.
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Memory reuse:
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mem_Reuse: controls whether the memory reuse function is turned on. When set to True,
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the memory reuse function is turned on. When set to False, the memory reuse function is turned off.
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- mem_Reuse: controls whether the memory reuse function is turned on. When set to True,
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- the memory reuse function is turned on. When set to False, the memory reuse function is turned off.
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precompile_only (bool): Whether to only precompile the network. Default: False.
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If set to True, the network will only be compiled, not executed.
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reserve_class_name_in_scope (bool) : Whether to save the network class name in the scope. Default: True.
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Each node has a scope. A scope of a subnode is the name of its parent node. If reserve_class_name_in_scope
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is set, the class name will be saved after keyword 'net-' in the scope.
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For example:Default/net-Net1/net-Net2 (reserve_class_name_in_scope=True)
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Default/net/net (reserve_class_name_in_scope=False)
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For example:
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Default/net-Net1/net-Net2 (reserve_class_name_in_scope=True)
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Default/net/net (reserve_class_name_in_scope=False)
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pynative_synchronize (bool): Whether to enable synchronous execution of the device in PyNative mode.
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Default: False. When the value is set to False, the operator is executed asynchronously on the device.
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When an error occurs in the execution of the operator, the specific error script code location cannot
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@ -673,28 +704,34 @@ def set_context(**kwargs):
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Optimization options of graph kernel fusion, and the priority is higher when it conflicts
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with enable_graph_kernel. Experienced user only.
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For example, context.set_context(graph_kernel_flags=”–opt_level=2 –dump_as_text”). Some general options:
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opt_level: Set the optimization level.
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Default: 2. Graph kernel fusion can be enabled equivalently by setting opt_level greater than 0.
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Available values are:
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0: Disable graph kernel fusion;
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1: enable the basic fusion of operators;
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2: includes all optimizations of level 1,
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and turns on more optimizations such as CSE, arithmetic simplication and so on;
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3: includes all optimizations of level 2, and turns on more optimizations such as SitchingFusion,
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ParallelFusion and so on. Optimizations of this level are radical and unstable in some scenarios.
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Be caution when using this level.
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dump_as_text: dump detail info as text files. Default: false.
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- opt_level: Set the optimization level.
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Default: 2. Graph kernel fusion can be enabled equivalently by setting opt_level greater than 0.
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Available values are:
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- 0: Disable graph kernel fusion;
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- 1: enable the basic fusion of operators;
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- 2: includes all optimizations of level 1,
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and turns on more optimizations such as CSE, arithmetic simplication and so on;
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- 3: includes all optimizations of level 2, and turns on more optimizations such as SitchingFusion,
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ParallelFusion and so on. Optimizations of this level are radical and unstable in some scenarios.
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Be caution when using this level.
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- dump_as_text: dump detail info as text files. Default: false.
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More options can refer to the implementation code. These options can also be set by environment
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variable MS_GRAPH_KERNEL_FLAGS, without modifying network source code.
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For example, export MS_GRAPH_KERNEL_FLAGS=”–opt_level=2 –dump_as_text”.
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enable_reduce_precision (bool): Whether to enable precision reduction. Default: True.
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auto_tune_mode (str): The mode of auto tune when op building, get the best tiling performance.
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Default: NO_TUNE. The value must be in ['RL', 'GA', 'RL,GA'].
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RL: Reinforcement Learning tune.
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GA: Genetic Algorithm tune.
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RL,GA: When both RL and GA optimization are enabled, the tool automatically selects RL or GA based on
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different types of operators in the network model. The sequence of RL and GA is not differentiated.
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(Automatic selection).
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- RL: Reinforcement Learning tune.
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- GA: Genetic Algorithm tune.
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- RL,GA: When both RL and GA optimization are enabled, the tool automatically selects RL or GA based on
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different types of operators in the network model. The sequence of RL and GA is not differentiated.
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(Automatic selection).
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For more information about the enable operator tuning tool settings, please check
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`Enable the operator optimization tool <https://www.mindspore.cn/docs/programming_guide/en
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/master/enable_auto_tune.html>`_.
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@ -706,7 +743,7 @@ def set_context(**kwargs):
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set larger too, otherwise a `core dumped` exception may be raised because of system stack overflow.
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enable_sparse (bool): Whether to enable sparsity feature. Default: False.
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For details of sparsity and sparse tensor, please check
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`sparse tensor <https://www.mindspore.cn/docs/programming_guide/en/master/tensor.html#sparse-tensor>`_.
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`sparse tensor <https://www.mindspore.cn/docs/programming_guide/en/master/tensor.html#sparse-tensor>`_.
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grad_for_scalar (bool): Whether to get gradient for scalar. Default: False.
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When grad_for_scalar is set to True, the function's scalar input can be derived.
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The default value is False. Because the back-end does not support scaling operations currently,
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