Add partial data propagation to enhance shape inference

include/onnxruntime/core/graph/graph.h

@@ -1760,6 +1760,12 @@ class Graph {  // NOLINT(clang-analyzer-optin.performance.Padding): preserve exi
                                                     std::vector<const ONNX_NAMESPACE::TypeProto*>& output_types,
                                                     const Graph::ResolveOptions& options);
 
+  // If the shape values are inferred after executing ONNX operator's PartialDataPropagationFunction(),
+  // save them to the output NodeArg as a TensorShapeProto or a scalar value so that downstream (consumer) nodes
+  // can use them later for their TypeAndShapeInferenceFunction() and PartialDataPropagationFunction().
+  common::Status SaveShapeValuesFromDataPropagation(Node& node, NodeArg& output_def,
+                                                    const ONNX_NAMESPACE::TypeProto& propagated_value_as_type_proto) const;
+
   // Apply type-inference and type-checking to all inputs and initializers:
   common::Status TypeCheckInputsAndInitializers();
 

include/onnxruntime/core/graph/node_arg.h

@@ -107,6 +107,9 @@ class NodeArg {
   /** Gets this NodeArg as a NodeArgInfo, AKA ValueInfoProto. */
   const NodeArgInfo& ToProto() const noexcept { return node_arg_info_; }
 
+  /** Gets the inferred shape values as a TensorShapeProto. */
+  const std::optional<ONNX_NAMESPACE::TensorShapeProto>& GetInferredShapeValues() const noexcept { return inferred_shape_values_; }
+
   /** Gets a flag indicating whether this NodeArg exists or not.
   Optional inputs are allowed in ONNX and an empty #Name represents a non-existent input argument. */
   bool Exists() const noexcept;
@@ -128,6 +131,22 @@ class NodeArg {
   // Node arg name, type and shape.
   NodeArgInfo node_arg_info_;
 
+  // This variable stores the inferred shape data as a TensorShapeProto after executing
+  // the ONNX operator's PartialDataPropagationFunction().
+  //
+  // Calling an operator's TypeAndShapeInferenceFunction() alone is sometimes insufficient
+  // for complete shape inference. For example, the Shape operator only provides the
+  // output's rank (1-dimensional) but not its actual dimension values.
+  // The PartialDataPropagationFunction(), defined in the ONNX operator schema, must also
+  // be executed to obtain the concrete output shape values, allowing accurate propagation
+  // of shape information throughout the graph.
+  std::optional<ONNX_NAMESPACE::TensorShapeProto> inferred_shape_values_;
+
+  // This variable stores the inferred scalar output.
+  // It is also used for shape inference and data propagation to ensure consistent shape and
+  // value information throughout the graph.
+  std::optional<int64_t> inferred_scalar_value_;
+
   // Flag indicates whether <*this> node arg exists or not.
   bool exists_;
 };