#pragma once
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// @generated from tools/autograd/templates/VariableType.h
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#include <ATen/ATen.h>
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#include <c10/util/intrusive_ptr.h>
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#include <torch/csrc/WindowsTorchApiMacro.h>
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#include <ATen/core/EnableNamedTensor.h>
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#include <cstdint> // for size_t
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#include <functional> // for function
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#include <memory> // for unique_ptr
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#include <string>
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#include <vector>
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namespace at {
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struct Quantizer;
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};
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namespace torch { namespace autograd {
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struct Variable;
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using at::Context;
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using at::Device;
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#ifdef BUILD_NAMEDTENSOR
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using at::Dimname;
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using at::DimnameList;
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#endif
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using at::Generator;
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using at::IntArrayRef;
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using at::MemoryFormat;
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using at::QScheme;
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using at::Scalar;
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using at::ScalarType;
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using at::Storage;
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using at::Tensor;
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using at::TensorList;
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using at::TensorOptions;
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using at::Quantizer;
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// This is temporary typedef to enable Quantizer in aten native function API
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// we'll remove them when we are actually exposing Quantizer class
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// to frontend
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using ConstQuantizerPtr = const c10::intrusive_ptr<Quantizer>&;
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using c10::optional;
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namespace VariableType {
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TORCH_API std::vector<at::DeprecatedTypeProperties*> allCUDATypes();
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TORCH_API std::vector<at::DeprecatedTypeProperties*> allCPUTypes();
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// checks that t is actually a Variable
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const Variable & checked_cast_variable(const Tensor & t, const char * name, int pos);
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Variable & checked_cast_variable(Tensor & t, const char * name, int pos);
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// TODO These are only needed in the header because they're defined in
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// VariableTypeManual.cpp but registered from one of the codegened
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// VariableType_X.cpp. Instead, we should register them from
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// VariableTypeManual.cpp and then we can remove these declarations
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// from the header.
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at::Tensor & unpack(Tensor & t, const char * name, int pos);
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const at::Tensor & unpack(const Tensor & t, const char * name, int pos);
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at::Tensor unpack_opt(const Tensor & t, const char * name, int pos);
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std::vector<at::Tensor> unpack(at::TensorList tl, const char *name, int pos);
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void backward(const Tensor& self, const Tensor& gradient, bool keep_graph, bool create_graph);
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void set_data(const Tensor & self, const Tensor & new_data);
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Tensor data(const Tensor & self);
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bool is_leaf(const Tensor & self);
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int64_t output_nr(const Tensor & self);
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int64_t _version(const Tensor & self);
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Tensor & copy_(Tensor & self, const Tensor & src, bool non_blocking);
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Tensor & resize_(Tensor & self, IntArrayRef size);
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Tensor & resize_as_(Tensor & self, const Tensor & the_template);
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Tensor detach(const Tensor & self);
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Tensor & detach_(Tensor & self);
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};
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}} // namespace torch::autograd
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