Add feed and fetch op to ProgramDesc before saving for inference#7636
Add feed and fetch op to ProgramDesc before saving for inference#7636kexinzhao merged 5 commits intoPaddlePaddle:developfrom
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sidgoyal78
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sidgoyal78
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Thanks for the PR, this looks good. I am just not sure if we should merge this, since the current PR addresses 1.1 and the already existing code addresses 1.2 in #7580 . So do we have a preference of 1.1 over 1.2?
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@sidgoyal78 I think it's fine to merge it for now. We can have both 1.1 and 1.2 supported via a PR in the future. |
Xreki
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Xreki
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I have some comments. However, we may change these in next PRs.
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| bool InferenceEngine::IsParameter(const framework::VarDesc* var) { | ||
| if (var->Persistable()) { | ||
| if (var->Persistable() && var->Name() != "feed" && var->Name() != "fetch") { |
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We should not use the name of Variable to decide whether the var is input or output of feed_op and fetch_op, because the name is not fixed, and it is possible to specify other names.
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Agree. And we don't need to check fetch because fetch will not be an input to an op.
We can get the feed var name from the feed op's input info.
Will fix in the future PR.
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| } | ||
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| void InferenceEngine::LoadInferenceModel( |
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I think we can remove this function. If there are not feed_op and fetch_op in the ProgramDesc, users can specify these when calling Run().
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Sorry, i don't understand this properly. Based on the updated design, the Run() function does not take as input the vector of fetch_var_name and feed_var_names. Right?
void Run(const ProgramDesc* program,
Scope* scope,
std::map<std::string, Tensor>& feeds,
std::map<std::string, Tensor>& fetchs,
std::string& feed_var_name = "feed",
std::string& fetch_var_name = "fetch") {
So can you please explain the idea that users can specify that information when calling Run().
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We can get the feed_var_names from the argument std::map<std::string, Tensor>& feeds, where the std::string represent a name and the Tensor is input data.
Why the argument is a std::map, because the corresponding argument in Python implementation is a dict.
Have a look at the example, where show the detailed usage of the Executor.Run().
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okay, will take a look. Thanks for the reply.
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Yes, will remove this function in the next PR.
| "fetch_var_names": fetch_var_names | ||
| }, f, -1) | ||
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| prepend_feed_ops(inference_program, feeded_var_names) |
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We can remove Line 265 - 270 now, and change the implementation of load_inference_model.
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Will do this in the next PR. Thanks!
| def prepend_feed_ops(inference_program, feeded_var_names): | ||
| global_block = inference_program.global_block() | ||
| feed_var = global_block.create_var( | ||
| name='feed', type=core.VarDesc.VarType.FEED_MINIBATCH, persistable=True) |
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There might be some problem if fixed the name to feed.
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Will fix this in the next PR.
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fix #7550