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Support model with multiple SCE loss nodes #20016

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merged 1 commit into from
Mar 22, 2024
Merged

Support model with multiple SCE loss nodes #20016

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5 changes: 5 additions & 0 deletions orttraining/orttraining/core/framework/gradient_graph_builder.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -210,6 +210,11 @@ NodeSet GradientGraphBuilder::ReverseBFSWithStopGradient(const NodeSet& nodes) c
continue;
}
const NodeArg* node_arg = n->InputDefs()[edge_it->GetDstArgIndex()];
if (!node_arg) {
LOGS(logger_, VERBOSE) << "Skip building gradient for input_" << edge_it->GetDstArgIndex()
<< " of node: " << n->Name() << " because it is not found in the graph.";
continue;
}
const auto [is_tensor_type, is_allowed_type_for_grad, type] = IsAllowedForGradient(graph_, node_arg);
if (is_tensor_type) {
if (!is_allowed_type_for_grad) {
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2 changes: 1 addition & 1 deletion orttraining/orttraining/core/optimizer/insert_output_rewriter.cc
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Expand Up @@ -44,7 +44,7 @@ Status InsertSoftmaxCrossEntropyLossOutput::Apply(Graph& graph, Node& node, Rewr
t.mutable_tensor_type()->mutable_shape()->CopyFrom(*X->Shape()); // log probability should have the same shape as logits.
}

NodeArg& node_arg = graph.GetOrCreateNodeArg(X->Name() + "_log_prob", &t);
NodeArg& node_arg = graph.GetOrCreateNodeArg(graph.GenerateNodeArgName(X->Name() + "_log_prob"), &t);

outputs.push_back(&node_arg);

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