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@ -559,14 +559,14 @@ class ProgramTranslator(object):
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Args:
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dirname (str): the directory to save the inference model.
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feed (list[int], optional): the input variable indices of the saved
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inference model. If None, all input variables of the
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ProgramTranslator would be the inputs of the saved inference
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model. Default None.
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fetch (list[int], optional): the output variable indices of the
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saved inference model. If None, all output variables of the
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TracedLayer object would be the outputs of the saved inference
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model. Default None.
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feed (list[int], optional): the indices of the input variables of the
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dygraph functions which will be saved as input variables in
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inference model. If None, all input variables of the dygraph function
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would be the inputs of the saved inference model. Default None.
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fetch (list[int], optional): the indices of the returned variable of the
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dygraph functions which will be saved as output variables in
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inference model. If None, all output variables of the dygraph function
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would be the outputs of the saved inference model. Default None.
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Returns:
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None
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Examples:
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@ -599,12 +599,12 @@ class ProgramTranslator(object):
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adam.minimize(loss)
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net.clear_gradients()
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# Save inference model.
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# Note that fetch=[0] means we set 'y' as the inference output.
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# Note that fetch=[0] means we set 'z' as the inference output.
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prog_trans = ProgramTranslator()
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prog_trans.save_inference_model("./dy2stat_infer_model", fetch=[0])
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# In this example, the inference model will be pruned based on input (x) and
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# output (y). The pruned inference program is going to be saved in the folder
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# In this example, the inference model will be pruned based on output (z).
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# The pruned inference program is going to be saved in the folder
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# "./dy2stat_infer_model" and parameters are going to be saved in separate
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# files in the folder.
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"""
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