huajsj commented on a change in pull request #9846:
URL: https://github.com/apache/tvm/pull/9846#discussion_r784259867
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File path: python/tvm/contrib/pipeline_executor.py
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@@ -125,6 +130,33 @@ def get_input_pipeline_map(self, name):
"""
return self._get_input_pipeline_map(name)
+ def get_params_group_pipeline_map(self, name):
+ """Using the "name" of parameters group to get the corresponding
runtime module index.
+ Returns
+ -------
+ Runtime module index: Integer
+ Returning the index of the runtime module.
+ """
+ return self._get_params_group_pipeline_map(name)
+
+ def set_params(self, params_group_name, params_data):
+ """Pipeline executor uses a map of parameters groups and module
indexes to support
+ the "on the fly" parameters setting. For example, in order to declare
that runtime
+ module 1 using group parameters named "param0", pipeline executor maps
the parameters
+ group named "param0" with runtime 1. This function is used to set
parameters into
+ to correct runtime module by using the parameters group name.
+ ----------
+ params_group_name : str
+ It is the parameters group name.
+ params_data : dict of str to NDArray
+ There is a list of parameters data and params key name.
+ """
Review comment:
like the input logic in pipeline executor config, before call
set_params, user need to build a map for parameters group name and module
index, for example
"pipe_config["param_group"]["param0"].connect(pipe_config[mod1]["param"])",
then the pipeline executor would know "param0" is corresponding module 1.
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