add GetPlaces operator #6732
add GetPlaces operator #6732
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paddle/operators/get_places_op.cc
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| : OperatorBase(type, inputs, outputs, attrs) {} | ||
| void Run(const framework::Scope &scope, | ||
| const platform::DeviceContext &dev_ctx) const override { | ||
| auto use_gpu = Attr<bool>("use_gpu"); |
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use_gpu => use_cuda?
since we wanna support AMD in the future.
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Done. Change this attribute to a string. Now support "CPU" and "CUDA".
paddle/operators/get_places_op.cc
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| places.resize(trainer_count); | ||
| if (use_gpu) { | ||
| for (int i = 0; i < trainer_count; i++) { | ||
| places.emplace_back(platform::GPUPlace(i)); |
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Also check if there are enough GPUs.
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We now have GPUPlace in place.h. Will change it together in next PR.
paddle/operators/get_places_op.cc
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| AddAttr<bool>("use_gpu", "(bool)use gpu").SetDefault(false); | ||
| AddComment(R"DOC( | ||
| GetPlaces Operator. | ||
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Doc "Returns a list of places based on flags. The list will be used for parallel execution."
paddle/operators/get_places_op.cc
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| framework::OpAttrChecker *op_checker) | ||
| : OpProtoAndCheckerMaker(proto, op_checker) { | ||
| AddOutput("Out", "vector of Place"); | ||
| AddAttr<int>("trainer_count", "(int)trainer count").SetDefault(1); |
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Maybe trainer_count is not a suitable name since trainer/pserver is used in distributed training, and trainer_count is confusing with the count of trainers.
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It's actually trainer count in local machine. I have not think out a proper name yet. Is there any suggestion?
| @@ -8,10 +8,13 @@ | |||
| from tensor import * | |||
| import control_flow | |||
| from control_flow import * | |||
| import utils | |||
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Maybe device? utils is too general
paddle/operators/get_places_op.cc
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| #else | ||
| PADDLE_THROW("'GPUPlace' is not supported in CPU only device."); | ||
| #endif | ||
| } else if (device_type == "CPU") { |
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What is the relationship between device_count and CPU cores？Or do we need to limit the device_count to a ratio large than CPU cores?
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I'm confusing why to specify a ratio number, but I think the device_count means the CPU cores when device_type="CPU".
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If device_count = 0, then it will use all devices of CPUs or GPUs.
Fix #6728