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@ -255,7 +255,6 @@ def ms_function(fn=None, obj=None, input_signature=None):
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process_obj = obj
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if args and not isinstance(args[0], MsTensor) and hasattr(args[0], func.__name__):
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process_obj = args[0]
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args = (x.default_input if hasattr(x, 'default_input') else x for x in args)
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return _MindSporeFunction(func, input_signature, process_obj)(*args)
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return staging_specialize
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@ -354,28 +353,8 @@ class _Executor:
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raise RuntimeError("Failure to init and dataset subgraph!")
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return True
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def _build_data_graph(self, obj, params, phase):
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if params is None:
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self._executor.build_data_graph(obj.parameters_dict(), phase, obj.parameters_broadcast_dict())
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elif isinstance(params, OrderedDict):
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self._executor.build_data_graph(params, phase)
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else:
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raise TypeError('Parameters need OrderedDict type, but got {}'.
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format(type(params)))
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def _params_init_data(self, obj, params, auto_parallel_mode=False):
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"""Init parameters' data."""
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if params is not None:
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for key, param in params.items():
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if not auto_parallel_mode:
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param.init_data()
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elif key not in obj.parameter_layout_dict:
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logger.debug("Layout dict does not contain the key %s.", key)
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param.init_data(set_sliced=True)
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else:
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layout = obj.parameter_layout_dict[key]
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param.init_data(layout, set_sliced=True)
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obj.init_parameters_data(auto_parallel_mode=auto_parallel_mode)
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def _build_data_graph(self, obj, phase):
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self._executor.build_data_graph(obj.parameters_dict(), phase, obj.parameters_broadcast_dict())
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def _set_dataset_mode(self, args_list):
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"""set dataset mode."""
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@ -386,7 +365,7 @@ class _Executor:
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else:
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_set_dataset_mode_config('normal')
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def compile(self, obj, *args, phase='predict', params=None, do_convert=True, auto_parallel_mode=False):
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def compile(self, obj, *args, phase='predict', do_convert=True, auto_parallel_mode=False):
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"""
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Compiles graph.
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@ -394,7 +373,6 @@ class _Executor:
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obj (Function/Cell): The function or cell instance need compile.
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args (tuple): Function or cell input arguments.
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phase (str): The name of compile phase. Default: 'predict'.
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params (OrderedDict): The parameters dictionary used for init data graph. Default: None.
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do_convert (bool): When set to True, convert ME graph to GE graph after compiling graph.
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auto_parallel_mode: When set to True, use auto parallel mode to compile graph.
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@ -435,10 +413,8 @@ class _Executor:
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if auto_parallel_mode:
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obj.parameter_layout_dict = self._executor.get_parameter_layout(phase)
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self._params_init_data(obj, params, auto_parallel_mode)
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if not enable_debug_runtime or enable_ge:
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if auto_parallel_mode:
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obj.load_parameter_slice(params)
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replace = obj.init_parameters_data(auto_parallel_mode=auto_parallel_mode)
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self._updata_param_node_default_input(phase, replace)
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# set parallel inputs in sink mode
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if auto_parallel_mode and (args and isinstance(args[0], Tensor) and args[0].virtual_flag):
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@ -446,16 +422,20 @@ class _Executor:
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# the following GE init process is not needed when use vm or ms backend
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if enable_ge:
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self._build_data_graph(obj, params, phase)
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self._build_data_graph(obj, phase)
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if "export" not in phase:
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init_phase = "init_subgraph" + "." + str(obj.create_time)
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_exec_init_graph(obj, init_phase)
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elif not enable_ge and "export" in phase:
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self._build_data_graph(obj, params, phase)
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self._build_data_graph(obj, phase)
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return phase, True
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def _updata_param_node_default_input(self, phase, replace):
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new_param = {x.name: replace[x] for x in replace if id(x) != id(replace[x])}
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return self._executor.updata_param_node_default_input(phase, new_param)
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def _get_strategy(self, obj):
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real_phase = self.phase_prefix + obj.phase + '.' + str(obj.create_time)
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return self._executor.get_strategy(real_phase)
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Wei Luning
5 years ago