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#pragma once
#include <c10/util/variant.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/jit/ir/ir.h>
#include <unordered_map>
namespace torch {
namespace jit {
// CAUTION NOT TO BE USED, STILL A WIP, NOT STABLE
TORCH_API void PropagateShapesOnGraph(std::shared_ptr<Graph>& graph);
// CAUTION NOT TO BE USED, STILL A WIP, NOT STABLE
// From [beg, end) attempt to propagate shapes and
// build up a graph that will compute all remaining symbolic
// shapes in [beg, end) that can be executed before beg
struct ShapeComputeGraphMapping {
ShapeComputeGraphMapping(
std::shared_ptr<Graph> partial_eval_shape_graph,
std::unordered_map<Value*, Value*>
enclosing_graph_value_to_shape_graph_input,
std::unordered_map<Value*, int64_t> graph_output_to_symbolic_shape_dim)
: partial_eval_shape_graph(partial_eval_shape_graph),
enclosing_graph_value_to_shape_graph_input_(
enclosing_graph_value_to_shape_graph_input),
graph_output_to_symbolic_shape_dim_(
graph_output_to_symbolic_shape_dim){};
std::shared_ptr<Graph> partial_eval_shape_graph;
std::unordered_map<Value*, Value*>
enclosing_graph_value_to_shape_graph_input_;
std::unordered_map<Value*, int64_t> graph_output_to_symbolic_shape_dim_;
};
TORCH_API c10::optional<ShapeComputeGraphMapping>
PropagateShapesAndBuildLargeShapeComputeGraph(
std::shared_ptr<Graph>& graph,
Node* beg,
Node* end);
// don't insert complete tensor shapes in shape compute graphs and instead
// rely on our partial evaluation pipeline to propagate information.
// this is a good proxy for our ability to propagate non-complete shape
// information.
TORCH_API bool setSymbolicShapeAnalysisTestMode(bool value);
TORCH_API bool symbolicShapeAnalysisTestModeEnabled();
using SSAInput = c10::variant<IValue, c10::SymbolicShape>;
TORCH_API c10::optional<std::vector<c10::SymbolicShape>>
calculateSymbolicShapesOnOp(
const FunctionSchema* schema,
const std::vector<SSAInput>& inputs);
} // namespace jit
} // namespace torch
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