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[onert/train] Register LayerScopeTensor to registry #14235
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Original file line number | Diff line number | Diff line change |
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@@ -262,7 +262,43 @@ FunctionMap BackendContext::generateFunctionMap() | |
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void BackendContext::planLayerScopeTensors([[maybe_unused]] const FunctionMap &fn_map) | ||
{ | ||
// TODO: Register LayerScopeTensors | ||
const auto &ops = trainable_graph()->operations(); | ||
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auto register_tensors = [this](const ir::OperationIndex &op_idx, | ||
std::optional<LayerScopeTensors> &&tensors) { | ||
if (not tensors.has_value()) | ||
return; | ||
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auto ls_tensors = tensors.value(); | ||
for (auto i = 0u; i < ls_tensors.size(); ++i) | ||
{ | ||
LayerScopeTensorIndex tensor_idx(op_idx, i); | ||
_tensor_builder->registerLayerScopeTensor(tensor_idx, ls_tensors[i]); | ||
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VERBOSE(BackendContext) << "(idx:" << tensor_idx << ") registered" << std::endl; | ||
} | ||
return; | ||
}; | ||
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for (auto &pair : fn_map) | ||
{ | ||
const auto &op_idx = pair.first; | ||
auto &fn_seq = pair.second; | ||
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const ir::IOperation *op = &ops.at(op_idx); | ||
const auto trainable_op = dynamic_cast<const ir::train::TrainableOperation *>(op); | ||
assert(trainable_op != nullptr); | ||
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if (not trainable_op->isRequiredForBackward()) | ||
continue; | ||
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VERBOSE(BackendContext) << "register layerscope tensor for " << trainable_op->name() | ||
<< std::endl; | ||
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fn_seq->iterate([&](exec::train::ITrainableFunction &fn) { | ||
register_tensors(op_idx, (&fn)->registerLayerScopeTensors()); | ||
}); | ||
} | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I'll show log like this : [ BackendContext ] register layerscope tensor for CategoricalCrossentropyLoss
[ BackendContext ] register layerscope tensor for Softmax
[ BackendContext ] register layerscope tensor for FullyConnected
[ BackendContext ] (idx: @8-0) registered
[ BackendContext ] (idx: @8-1) registered
[ BackendContext ] (idx: @8-2) registered
[ BackendContext ] register layerscope tensor for FullyConnected
[ BackendContext ] (idx: @7-0) registered
[ BackendContext ] (idx: @7-1) registered
[ BackendContext ] (idx: @7-2) registered
[ BackendContext ] (idx: @7-3) registered
[ BackendContext ] register layerscope tensor for Reshape
[ BackendContext ] register layerscope tensor for MaxPool2D
[ BackendContext ] (idx: @5-0) registered
[ BackendContext ] register layerscope tensor for Conv2D
[ BackendContext ] (idx: @4-0) registered
[ BackendContext ] (idx: @4-1) registered
[ BackendContext ] (idx: @4-2) registered
[ BackendContext ] (idx: @4-3) registered
[ BackendContext ] register layerscope tensor for Conv2D
[ BackendContext ] (idx: @3-0) registered
[ BackendContext ] (idx: @3-1) registered
[ BackendContext ] (idx: @3-2) registered
[ BackendContext ] (idx: @3-3) registered |
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const auto ctx_data = data(); | ||
TensorPlanner tensor_planner{*ctx_data->tgraph.get(), ctx_data->external_operands}; | ||
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(&fn)->registerLayerScopeTensors()
call this functions and each layer will override this function.ONE/runtime/onert/core/include/exec/train/ITrainableFunction.h
Lines 39 to 43 in 190b538