huajsj commented on a change in pull request #9494:
URL: https://github.com/apache/tvm/pull/9494#discussion_r747997748
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File path: python/tvm/contrib/pipeline_executor.py
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@@ -93,8 +108,71 @@ def __init__(self, module):
else:
self.module = module
# Get the packed functions from the pipeline executor.
+ self._run = self.module["run"]
+ self._stop = self.module["stop"]
+ self._set_input = self.module["set_input"]
+ self._set_param = self.module["set_param"]
+ self._get_input = self.module["get_input"]
+ self._get_output = self.module["get_output"]
+ self._get_num_inputs = self.module["get_num_inputs"]
self._get_num_outputs = self.module["get_num_outputs"]
+ def run(self, sync=False):
+ """Run the pipeline executor."""
+ self._run(sync)
+
+ def stop(self):
+ """Stop the pipeline executor."""
+ self._stop()
+
+ def set_input(self, key, value):
+ """Set inputs to the module via "value".
+ Parameters
+ ----------
+ key : str
+ The input key
+
+ value : array_like.
+ The input value
+ """
+ self._set_input(key, tvm.nd.array(value, tvm.cpu()))
+
+ def set_params(self, params_name, params_data):
+ """Set params to the module via param name and params data.
+ Parameters
+ ----------
+ params_name : str
+ The params name
+
+ params_data : dict of str to NDArray
+ A list of params data and params key name.
+ """
+ if params_data:
+ keys = list(params_data.keys())
+ keys.sort(key=lambda x: -np.prod(params_data[x].shape))
+ for k in keys:
+ self._set_param(params_name, k, tvm.nd.array(params_data[k],
tvm.cpu()))
Review comment:
this logic is the same logic used in graph_executor.py that use such
logic to handle "a rpc memory issue", I assume such issue already fixed, then
just remove it.
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