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#pragma once
#include <memory>
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>
#include <torch/csrc/lazy/backend/backend_data.h>
#include <torch/csrc/lazy/backend/backend_device.h>
#include <torch/csrc/lazy/core/ir.h>
#include <torch/csrc/lazy/core/ir_util.h>
namespace torch {
namespace lazy {
class TORCH_API Computation {
public:
virtual int parameters_size() const = 0;
virtual const std::vector<Shape>& parameter_shapes() const = 0;
virtual const std::vector<std::string>& parameter_names() const = 0;
virtual const Shape& result_shape() const = 0;
virtual const std::string to_string() const = 0;
virtual ~Computation() = default;
// Indicates whether this computation is being executed inside a mark step
// Assume false unless set otherwise
bool in_mark_step = false;
};
using ComputationPtr = std::shared_ptr<Computation>;
// Keeps track of the code generation state.
class TORCH_API LoweringContext {
public:
LoweringContext(const std::string& name, BackendDevice device);
LoweringContext(
const std::string& name,
BackendDevice device,
c10::ArrayRef<torch::lazy::Node*> post_order,
Util::EmissionMap emit_status);
virtual ~LoweringContext() = default;
static std::unique_ptr<LoweringContext> Create(
const std::string& name,
BackendDevice device,
c10::ArrayRef<torch::lazy::Node*> post_order,
Util::EmissionMap emit_status);
static std::unique_ptr<LoweringContext> Create(
const std::string& name,
BackendDevice device);
const BackendDevice& device() const {
return device_;
};
// Retrieves the vector holding all the tensors associated with the parameter
// instructions which have been created.
const std::vector<BackendDataPtr>& GetParametersData() const;
// Adds a new input/output alias.
virtual void SetUpAlias(
const std::vector<int64_t>& output_index,
int64_t param_number,
const std::vector<int64_t>& param_index,
bool must_alias = false) {
// Dummy default implementation to do nothing.
}
// Check if parameter shape matches result at index.
virtual bool CheckResultShape(
const BackendDataPtr& parameter_data,
size_t result_idx) {
// Dummy default implementation to do nothing.
return false;
}
// Adds the given output as a component of the result tuple and returns its
// assigned position within the tuple.
virtual size_t AddResult(const torch::lazy::Output& output) = 0;
// Associates the given output with the input parameter of the given index and
// shape. Only used for the operator-by-operator execution, mostly for
// debugging purposes.
virtual void AddParameter(
const torch::lazy::Output& output,
size_t index,
const Shape& shape,
const std::string& name) = 0;
// Build the computation capturing all the operations created with the
// embedded builder (returned by the builder() API).
virtual ComputationPtr Build() = 0;
size_t GetEmittedNodeCount() const {
return emit_status_.size();
}
protected:
BackendDevice device_;
std::vector<BackendDataPtr> parameters_;
std::vector<size_t> parameter_sequence_;
Util::EmissionMap emit_status_;
};
} // namespace lazy
} // namespace torch
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