torch::autograd Namespace Reference

Namespaces
namespace	_functions
namespace	anomaly_mode
namespace	detail
namespace	forward_ad
namespace	function
namespace	functional
namespace	generated
namespace	grad_mode
namespace	gradcheck
namespace	impl
namespace	profiler
namespace	python
namespace	utils
namespace	variable
namespace	VariableType

Classes
struct	AccumulateGrad
struct	AnomalyMetadata
struct	AnomalyMode
struct	AutogradContext
	Context to save information during forward that can be accessed in backward in custom autograd operations (see torch::autograd::Function for details). More...
struct	ComputeRequiresGrad
struct	CopyBackwards
struct	CopySlices
struct	CppFunctionPreHook
struct	CppNode
struct	DefaultFunctionType
struct	DelayedError
class	DetectAnomalyGuard
	A RAII guard that enables Anomaly Detection Mode. More...
struct	Edge
	Represents a particular input of a function. More...
struct	Engine
struct	Error
struct	ExtractVariables
struct	Flatten
struct	ForwardADLevel
struct	ForwardGrad
struct	Function
	To use custom autograd operations, implement a Function subclass with static forward and backward functions: More...
struct	FunctionPostHook
struct	FunctionPreHook
struct	Gather
struct	GraphRoot
struct	GraphTask
class	GraphTaskGuard
struct	Identity
struct	InputBuffer
struct	InputMetadata
	Records type, shape, and device of tensor and, where applicable, the stream the correspondingoperation took place on. More...
struct	Node
class	NodeGuard
struct	NodeTask
struct	NotImplemented
struct	PyAnomalyMetadata
struct	PyFunctionPostHook
struct	PyFunctionPreHook
struct	PyNode
struct	ReadyQueue
class	SavedVariable
	A snapshot of a variable at a certain version. More...
struct	Scatter
struct	symbolic_unconvertible
struct	SymbolicContext
struct	THPCppFunction
struct	TraceableFunction
	See Node::is_traceable() for definition. More...
struct	UndefinedGrad
struct	UndefinedGradBackward
struct	VariableHooks
struct	VariableInfo

Typedefs
using	Variable = at::Tensor
	Variable is exactly the same as Tensor (i.e. More...
using	ConstQuantizerPtr = const c10::intrusive_ptr< Quantizer > &
using	hooks_list = std::vector< std::function< Variable(const Variable &)> >
template<typename X , typename... Args>
using	forward_t = decltype(X::forward(nullptr, std::declval< Args >()...))
using	EngineStub = Engine &(*)()
using	tensor_list = std::vector< at::Tensor >
using	variable_list = std::vector< Variable >
using	edge_list = std::vector< Edge >
using	saved_variable_list = std::vector< SavedVariable >
using	IndexRange = std::pair< size_t, size_t >
using	function_constructor = std::function< std::shared_ptr< Node >(edge_list &&)>
using	GradMode = at::GradMode
using	AutoGradMode = at::AutoGradMode

Functions
void	initFFTFunctions (PyObject *module)
void	initLinalgFunctions (PyObject *module)
static PyObject *	THPVariable__parse_to (PyObject *module, PyObject *args, PyObject *kwargs)
void	initNNFunctions (PyObject *module)
Tensor	dispatch_arange (Scalar end, Tensor result)
Tensor	dispatch_arange (Scalar end, const TensorOptions &options)
Tensor	dispatch_arange (Scalar start, Scalar end, Scalar step, Tensor result)
Tensor	dispatch_arange (Scalar start, Scalar end, Scalar step, const TensorOptions &options)
static PyObject *	THPVariable_arange (PyObject *self, PyObject *args, PyObject *kwargs)
Tensor	dispatch_range (Scalar start, Scalar end, Scalar step, Tensor result)
Tensor	dispatch_range (Scalar start, Scalar end, Scalar step, const TensorOptions &options)
static PyObject *	THPVariable_range (PyObject *self, PyObject *args, PyObject *kwargs)
Tensor	dispatch_full (IntArrayRef size, Scalar fill_val, const TensorOptions &options)
Tensor	dispatch_full (IntArrayRef size, Scalar fill_val, c10::optional< DimnameList > names, const TensorOptions &options)
Tensor	dispatch_full (IntArrayRef size, Scalar fill_val, Tensor result)
static PyObject *	THPVariable_full (PyObject *self, PyObject *args, PyObject *kwargs)
Tensor	dispatch_randint (int64_t high, IntArrayRef size, c10::optional< Generator > generator, Tensor result)
Tensor	dispatch_randint (int64_t high, IntArrayRef size, c10::optional< Generator > generator, const TensorOptions &options)
Tensor	dispatch_randint (int64_t high, IntArrayRef size, Tensor result)
Tensor	dispatch_randint (int64_t high, IntArrayRef size, const TensorOptions &options)
Tensor	dispatch_randint (int64_t low, int64_t high, IntArrayRef size, c10::optional< Generator > generator, Tensor result)
Tensor	dispatch_randint (int64_t low, int64_t high, IntArrayRef size, c10::optional< Generator > generator, const TensorOptions &options)
Tensor	dispatch_randint (int64_t low, int64_t high, IntArrayRef size, Tensor result)
Tensor	dispatch_randint (int64_t low, int64_t high, IntArrayRef size, const TensorOptions &options)
static PyObject *	THPVariable_randint (PyObject *self_, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_as_tensor (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_from_numpy (PyObject *module, PyObject *arg)
static Tensor	dispatch_nonzero (const Tensor &self)
static Tensor	dispatch_nonzero (const Tensor &self, Tensor out)
static std::vector< Tensor >	dispatch_nonzero_numpy (const Tensor &self)
static PyObject *	THPVariable_nonzero (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_sparse_coo_tensor (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable__sparse_coo_tensor_unsafe (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_tensor (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_get_device (PyObject *self_, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_numel (PyObject *self_, PyObject *args, PyObject *kwargs)
void	initTorchFunctions (PyObject *module)
static PyObject *	THPVariable__is_view (PyObject *self, PyObject *args)
static PyObject *	THPVariable_apply_ (PyObject *self, PyObject *arg)
static PyObject *	THPVariable_size (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_stride (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_get_device (PyObject *self_, PyObject *args)
static PyObject *	THPVariable_has_names (PyObject *self_, PyObject *args)
static PyObject *	THPVariable_data_ptr (PyObject *self_, PyObject *args)
static PyObject *	THPVariable_storage_offset (PyObject *self_, PyObject *args)
static PyObject *	THPVariable_dim (PyObject *self, PyObject *args)
static PyObject *	THPVariable_numel (PyObject *self, PyObject *args)
static Tensor	dispatch_contiguous (const Tensor &self, at::MemoryFormat memory_format)
static PyObject *	THPVariable_contiguous (PyObject *self, PyObject *args, PyObject *kwargs)
static Tensor	dispatch_copy_ (Tensor &self, const Tensor &other, bool non_blocking)
static PyObject *	THPVariable_copy_ (PyObject *self, PyObject *args, PyObject *kwargs)
static double	dispatch_to_CDouble (const Tensor &self)
static c10::complex< double >	dispatch_to_CComplexDouble (const Tensor &self)
static int64_t	dispatch_to_CLong (const Tensor &self)
static bool	dispatch_to_Bool (const Tensor &self)
static PyObject *	THPVariable_float_scalar (PyObject *self, PyObject *args)
static PyObject *	THPVariable_complex_scalar (PyObject *self, PyObject *args)
static PyObject *	THPVariable_integral_scalar (PyObject *self, PyObject *args)
static PyObject *	THPVariable_index_scalar (PyObject *self, PyObject *args)
static Tensor	dispatch_invert (const Tensor &self)
static PyObject *	THPVariable_invert (PyObject *self, PyObject *args)
static Tensor	dispatch_to (const Tensor &self, Device device, bool non_blocking, bool copy, c10::optional< c10::MemoryFormat > optional_memory_format)
static Tensor	dispatch_to (const Tensor &self, bool non_blocking, bool copy, c10::optional< c10::MemoryFormat > optional_memory_format)
static Tensor	dispatch_to (const Tensor &self, ScalarType dtype, bool non_blocking, bool copy, c10::optional< c10::MemoryFormat > optional_memory_format)
static Tensor	dispatch_to (const Tensor &self, Device device, ScalarType dtype, bool non_blocking, bool copy, c10::optional< c10::MemoryFormat > optional_memory_format)
static PyObject *	THPVariable_cpu (PyObject *self, PyObject *args, PyObject *kwargs)
static Tensor	dispatch_nonzero (const Tensor &self)
static std::vector< Tensor >	dispatch_nonzero_numpy (const Tensor &self)
static PyObject *	THPVariable_nonzero (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_cuda (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_xpu (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_to_type (PyObject *self, ScalarType scalarType, c10::optional< c10::MemoryFormat > optional_memory_format)
static PyObject *	THPVariable_byte (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_char (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_double (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_float (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_half (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_int (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_long (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_short (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_bool (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_bfloat16 (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_element_size (PyObject *self, PyObject *args)
static PyObject *	THPVariable_numpy (PyObject *self, PyObject *arg)
static PyObject *	THPVariable_requires_grad_ (PyObject *self, PyObject *args, PyObject *kwargs)
bool	dispatch_is_contiguous (Tensor &self, MemoryFormat memory_format)
static PyObject *	THPVariable_is_contiguous (PyObject *self_, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_item (PyObject *self, PyObject *args)
static PyObject *	THPVariable_map_ (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_map2_ (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_new (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_new_ones (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_new_tensor (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_storage (PyObject *self, PyObject *arg)
static PyObject *	THPVariable_storage_type (PyObject *self, PyObject *arg)
static PyObject *	THPVariable_to (PyObject *self, PyObject *args, PyObject *kwargs)
static PyObject *	THPVariable_tolist (PyObject *self, PyObject *args)
static PyObject *	THPVariable_type (PyObject *self, PyObject *args, PyObject *kwargs)
Tuple[_OptionalTensor,...]	_make_grads (Sequence[torch.Tensor] outputs, Sequence[_OptionalTensor] grads)
Tuple[_OptionalTensor,...]	_tensor_or_tensors_to_tuple (Optional[_TensorOrTensors] tensors, int length)
None	backward (_TensorOrTensors tensors, Optional[_TensorOrTensors] grad_tensors=None, Optional[bool] retain_graph=None, bool create_graph=False, Optional[_TensorOrTensors] grad_variables=None, Optional[Sequence[torch.Tensor]] inputs=None)
Tuple[torch.Tensor,...]	grad (_TensorOrTensors outputs, _TensorOrTensors inputs, Optional[_TensorOrTensors] grad_outputs=None, Optional[bool] retain_graph=None, bool create_graph=False, bool only_inputs=True, bool allow_unused=False)
def	_is_checkpoint_valid ()
def	variable (*args, **kwargs)
variable_list	_make_grads (const variable_list &outputs, const variable_list &grad_outputs)
variable_list	run_backward (const variable_list &outputs, const variable_list &grad_outputs, bool keep_graph, bool create_graph, const variable_list &inputs, bool allow_unused, bool accumulate_grad)
void	backward (const variable_list &tensors, const variable_list &grad_tensors={}, c10::optional< bool > retain_graph=c10::nullopt, bool create_graph=false, const variable_list &inputs={})
	Computes the sum of gradients of given tensors with respect to graph leaves. More...
variable_list	grad (const variable_list &outputs, const variable_list &inputs, const variable_list &grad_outputs={}, c10::optional< bool > retain_graph=c10::nullopt, bool create_graph=false, bool allow_unused=false)
	Computes and returns the sum of gradients of outputs with respect to the inputs. More...
variable_list	_wrap_outputs (const variable_list &input_vars, const std::unordered_set< at::TensorImpl * > &non_differentiable, const std::unordered_set< at::TensorImpl * > &dirty_inputs, const at::ArrayRef< Variable > raw_outputs, const std::shared_ptr< Node > &cdata)
void	check_variable_result (const Variable &original, const Variable &result, std::string hook_name)
template<typename... Args>
void	extract_vars (std::vector< bool > &is_var, variable_list &list, Args &&... args)
template<typename T >
std::enable_if< std::is_same< T, variable_list >::value, T & >::type	to_output_type (variable_list &output_list)
template<typename T >
std::enable_if< std::is_same< T, Variable >::value, T >::type	to_output_type (variable_list &output_list)
static variable_list	call_pre_hooks (Node &fn, variable_list inputs)
static variable_list	call_post_hooks (Node &fn, variable_list outputs, const variable_list &inputs)
static bool	is_compatible_type (const at::TensorOptions &expected, const at::TensorOptions &actual)
void	set_device (int device)
void	validate_outputs (const edge_list &edges, variable_list &grads, const std::function< std::string(const std::string &)> &format_error)
static variable_list	call_function (std::shared_ptr< GraphTask > &graph_task, Node *func, InputBuffer &inputBuffer)
std::atomic< EngineStub >	engine_stub (Engine::get_base_engine)
void	set_default_engine_stub (EngineStub stub)
bool	isForwardADEnabled ()
void	setForwardADEnabled (bool value)
static void	gatherFunctions (Node *func, std::vector< std::shared_ptr< Node > > &stack)
void	deleteNode (Node *function)
void	create_gradient_edge (Variable &variable, std::shared_ptr< Node > function)
	Create an Edge between the given variable and the function, which is assumed to be the gradient function of this variable (i.e. More...
bool	any_variable_requires_grad (const variable_list &variables)
	Return true if any of the variables in the list require a gradient. More...
template<typename... Variables>
edge_list	collect_next_edges (Variables &&... variables)
	Return the next edges of all the given variables, or tuples of variables. More...
variable_list	wrap_outputs (const variable_list &inputs, tensor_list &&outputs, const function_constructor &ctr)
	Wraps the tensor outputs in variables and creates the grad_fn and sets the grad_fn if necessary. More...
void	check_input_variables (const char *name, const variable_list &inputs, int args, int required_args=-1, bool allow_undefined=false)
	Checks that inputs contains exactly args items and that the first required_args items are not nullptr. More...
template<typename... Args>
bool	compute_requires_grad (Args &&... args)
void	set_history (at::Tensor &variable, const std::shared_ptr< Node > &grad_fn)
void	set_history (std::vector< Variable > &&variables, const std::shared_ptr< Node > &grad_fn)
void	set_history (std::vector< Variable > &variables, const std::shared_ptr< Node > &grad_fn)
static PyObject *	set_autocast_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	is_autocast_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	clear_autocast_cache (PyObject *_unused, PyObject *arg)
static PyObject *	autocast_increment_nesting (PyObject *_unused, PyObject *arg)
static PyObject *	autocast_decrement_nesting (PyObject *_unused, PyObject *arg)
static PyObject *	set_forward_AD_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	is_forward_AD_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	set_grad_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	is_grad_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	set_anomaly_mode_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	is_anomaly_mode_enabled (PyObject *_unused, PyObject *arg)
static PyObject *	python_enter_dual_level (PyObject *_unused, PyObject *arg)
static PyObject *	python_exit_dual_level (PyObject *_unused, PyObject *args, PyObject *kwargs)
PyMethodDef *	python_functions ()
static void	accumulate (std::vector< Variable > &buffer, const size_t pos, Variable &&var)
void	_print_stack (PyObject *stack, const std::string &current_node_name, bool is_parent)
PyObject *	THPCppFunction_next_functions (THPCppFunction *self, PyObject *hook)
PyObject *	THPCppFunction_metadata (THPCppFunction *self, void *_unused)
PyObject *	THPCppFunction_requires_grad (THPCppFunction *self, void *unused)
PyObject *	THPCppFunction_register_hook_dict (PyObject *self, PyObject *_var)
PyObject *	THPCppFunction_register_hook (PyObject *self, PyObject *hook)
PyObject *	THPCppFunction_name (PyObject *self, PyObject *noargs)
PyTypeObject *	_initFunctionPyTypeObject (PyTypeObject &type, const char *name, PyGetSetDef *function_properties, PyMethodDef *function_methods)
PyObject *	functionToPyObject (const std::shared_ptr< Node > &cdata)
void	registerCppFunction (const std::type_info &type, PyTypeObject *pytype)
PyObject *	registerFunctionHook (Node &fn, PyObject *hook)
template<typename Ctor >
PyObject *	CppFunction_pynew (PyTypeObject *type, PyObject *args, PyObject *kwds)
template<typename Ctor >
PyTypeObject *	createForwardFunctionPyTypeObject (PyTypeObject &type, const char *name, PyGetSetDef *function_properties=nullptr, PyMethodDef *function_methods=nullptr)
bool	ensure_tuple (THPObjectPtr &obj)
	Cast an object into a tuple, if it is not a tuple already. More...
static PyObject *	THPVariable_pynew (PyTypeObject *type, PyObject *args, PyObject *kwds)
void	init_legacy_variable (PyObject *module)
void	initTensorImplConversion (PyObject *module)
Py_ssize_t	THPVariable_length (PyObject *self)
static int64_t	count_specified_dimensions (PyObject *index)
static void	invalid_index (PyObject *obj)
static Variable	sequenceToVariable (c10::DispatchKey dispatch_key, PyObject *seq)
static Variable	valueToTensor (c10::TensorOptions options, PyObject *value, const at::Device &device)
static void	checkUnpackSlice (PyObject *index, Py_ssize_t *start_ptr, Py_ssize_t *stop_ptr, Py_ssize_t *step_ptr)
static void	recordSliceTrace (PyObject *obj)
static void	recordSelectTrace (const Tensor &index_tensor)
static Variable	applySlicing (const Variable &self, PyObject *index, variable_list &outIndices, bool is_tracing, const at::Device &self_device, const IntArrayRef &self_sizes, int64_t specified_dims)
static bool	treatSequenceAsTuple (PyObject *index)
static THPObjectPtr	wrapTuple (PyObject *index)
PyObject *	THPVariable_getitem (PyObject *self, PyObject *index)
int	THPVariable_setitem (PyObject *self, PyObject *index, PyObject *py_value)
void	handle_view_on_rebase (DifferentiableViewMeta *diff_view_meta, bool indirect)
void	check_inplace (const Tensor &tensor, bool requires_grad)
void	check_inplace (const TensorList tensors, bool requires_grad)
void	throw_error_out_requires_grad (const char *name)
void	throw_error_for_complex_autograd (const Tensor &tensor, const char *name)
void	throw_error_for_complex_autograd (const TensorList &tensorlist, const char *name)
void	rebase_history (Variable &var, std::shared_ptr< Node > grad_fn)
void	rebase_history (std::vector< Variable > &&vars, std::shared_ptr< Node > grad_fn)
void	increment_version (Tensor &t)
template<typename... Args>
variable_list	flatten_tensor_args (Args &&... args)
Tensor	as_view (const Tensor &base, const Tensor &tensor, bool is_bw_differentiable, bool is_fw_differentiable, std::function< Tensor(const Tensor &)> view_func=nullptr, CreationMeta creation_meta=CreationMeta::DEFAULT, bool allow_tensor_metadata_change=true)
std::vector< Tensor >	as_view (const Tensor &base, std::vector< Tensor > &tensors, bool is_bw_differentiable, bool is_fw_differentiable, CreationMeta creation_meta=CreationMeta::DEFAULT)
void	check_no_requires_grad (const Tensor &tensor, const char *name)
void	check_no_requires_grad (const c10::optional< Tensor > &tensor, const char *name)
void	check_no_requires_grad (TensorList tensors, const char *name)
void	check_no_requires_grad (const c10::List< c10::optional< Tensor > > &tensors, const char *name)
std::vector< SavedVariable >	make_saved_variable_list (TensorList tensors)
std::vector< SavedVariable >	make_saved_variable_list (const c10::List< c10::optional< at::Tensor > > &tensors)
std::vector< std::vector< int64_t > >	to_args_sizes (TensorList tensors)
std::vector< ScalarType >	to_args_scalartypes (TensorList tensors)

Variables
	$
static PyObject *	THPFFTVariableFunctionsModule = NULL
static PyObject *	THPLinalgVariableFunctionsModule = NULL
static PyObject *	THPNNVariableFunctionsModule = NULL
static PyObject *	THPVariableFunctionsModule = NULL
static PyTypeObject	THPVariableFunctions
list	__all__ = ['Variable', 'Function', 'backward', 'grad_mode']
	_OptionalTensor = Optional[torch.Tensor]
static thread_local int	worker_device = NO_DEVICE
static thread_local bool	checkpoint_valid = true
static thread_local int	current_depth = 0
static thread_local int	total_depth = 0
static thread_local std::shared_ptr< GraphTask >	current_graph_task = nullptr
static thread_local std::shared_ptr< ReadyQueue >	local_ready_queue = nullptr
static constexpr int	NO_DEVICE = -2
static constexpr int	CPU_DEVICE = -1
static constexpr int	MAX_DEPTH = 60
static thread_local std::shared_ptr< Node >	current_evaluating_node = nullptr
static PyMethodDef	methods []
static struct PyMethodDef	default_methods []
static struct PyGetSetDef	default_properties []
static std::unordered_map< std::type_index, THPObjectPtr >	cpp_function_types
PyTypeObject	THPLegacyVariableType
PyMethodDef	variable_methods []
const char *	ERR_BACKWARD_TWICE
VariableHooks	variableHooks

Detailed Description

``torch.autograd`` provides classes and functions implementing automatic
differentiation of arbitrary scalar valued functions. It requires minimal
changes to the existing code - you only need to declare :class:`Tensor` s
for which gradients should be computed with the ``requires_grad=True`` keyword.
As of now, we only support autograd for floating point :class:`Tensor` types (
half, float, double and bfloat16) and complex :class:`Tensor` types (cfloat, cdouble).

Typedef Documentation

AutoGradMode

using torch::autograd::AutoGradMode = typedef at::AutoGradMode

Definition at line 9 of file grad_mode.h.

ConstQuantizerPtr

using torch::autograd::ConstQuantizerPtr = typedef const c10::intrusive_ptr<Quantizer>&

Definition at line 42 of file VariableType.h.

edge_list

using torch::autograd::edge_list = typedef std::vector<Edge>

Definition at line 33 of file function.h.

EngineStub

using torch::autograd::EngineStub = typedef Engine& (*)()

Definition at line 390 of file engine.h.

forward_t

template<typename X , typename... Args>

using torch::autograd::forward_t = typedef decltype(X::forward(nullptr, std::declval<Args>()...))

Definition at line 23 of file custom_function.h.

function_constructor

using torch::autograd::function_constructor = typedef std::function<std::shared_ptr<Node>(edge_list&&)>

Definition at line 17 of file utils.h.

GradMode

using torch::autograd::GradMode = typedef at::GradMode

Definition at line 8 of file grad_mode.h.

hooks_list

using torch::autograd::hooks_list = typedef std::vector<std::function<Variable(const Variable&)> >

Definition at line 8 of file cpp_hook.h.

IndexRange

using torch::autograd::IndexRange = typedef std::pair<size_t, size_t>

Definition at line 35 of file function.h.

saved_variable_list

using torch::autograd::saved_variable_list = typedef std::vector<SavedVariable>

Definition at line 34 of file function.h.

tensor_list

using torch::autograd::tensor_list = typedef std::vector<at::Tensor>

Definition at line 31 of file function.h.

Variable

typedef at::Tensor torch::autograd::Variable

Variable is exactly the same as Tensor (i.e.

we have using Variable = at::Tensor). This means you can perform all the usual mathematical and other operations you can perform on Tensors also on Variables.

The only reason we are keeping the Variable class is backward compatibility with external user's legacy C++ frontend code. Our intention is to eliminate the Variable class in the near future.

Definition at line 23 of file VariableType.h.

variable_list

typedef std::vector< Variable > torch::autograd::variable_list

Definition at line 32 of file function.h.

Function Documentation

_initFunctionPyTypeObject()

PyTypeObject * torch::autograd::_initFunctionPyTypeObject	(	PyTypeObject &	type,
		const char *	name,
		PyGetSetDef *	function_properties,
		PyMethodDef *	function_methods
	)

Definition at line 172 of file python_cpp_function.cpp.

References default_methods, default_properties, name, and type.

Referenced by torch::autograd::generated::addClass(), createForwardFunctionPyTypeObject(), and torch::autograd::DefaultFunctionType::DefaultFunctionType().

_is_checkpoint_valid()

def torch.autograd._is_checkpoint_valid ( )

private

Definition at line 242 of file __init__.py.

References _is_checkpoint_valid().

Referenced by _is_checkpoint_valid(), and torch.utils.checkpoint.CheckpointFunction.backward().

_make_grads() [1/2]

variable_list torch::autograd::_make_grads	(	const variable_list &	outputs,
		const variable_list &	grad_outputs
	)

Definition at line 17 of file autograd.cpp.

References LEGACY_CONTIGUOUS_MEMORY_FORMAT, at::native::ones_like(), at::native::metal::mpscnn::output, outputs, and TORCH_CHECK.

_make_grads() [2/2]

Tuple[_OptionalTensor, ...] torch.autograd._make_grads ( Sequence[torch.Tensor]  outputs, Sequence[_OptionalTensor]  grads  )

private

Definition at line 28 of file __init__.py.

References _make_grads(), torch::jit.isinstance(), compare-fastrnn-results.str, type, and c10::prim.zip().

Referenced by _make_grads(), backward(), and grad().

_print_stack()

void torch::autograd::_print_stack	(	PyObject *	stack,
		const std::string &	current_node_name,
		bool	is_parent
	)

Definition at line 81 of file python_anomaly_mode.cpp.

References THPPointer< T >::get(), torch.distributions.constraints::stack, THPUtils_unpackString(), and TORCH_WARN.

Referenced by torch::autograd::PyAnomalyMetadata::print_stack().

_tensor_or_tensors_to_tuple()

Tuple[_OptionalTensor, ...] torch.autograd._tensor_or_tensors_to_tuple ( Optional[_TensorOrTensors]  tensors, int  length  )

private

Definition at line 60 of file __init__.py.

References _tensor_or_tensors_to_tuple(), and torch::jit.isinstance().

Referenced by _tensor_or_tensors_to_tuple(), backward(), and grad().

_wrap_outputs()

TORCH_API variable_list torch::autograd::_wrap_outputs	(	const variable_list &	input_vars,
		const std::unordered_set< at::TensorImpl * > &	non_differentiable,
		const std::unordered_set< at::TensorImpl * > &	dirty_inputs,
		const at::ArrayRef< Variable >	raw_outputs,
		const std::shared_ptr< Node > &	cdata
	)

Definition at line 20 of file custom_function.cpp.

References AT_ASSERT, torch::autograd::impl::clear_hooks(), torch::autograd::impl::get_autograd_meta(), inputs, num_outputs, at::native::output_nr(), outputs, torch::autograd::impl::rebase_history(), torch::autograd::impl::set_gradient_edge(), set_history(), c10::ArrayRef< T >::size(), TORCH_CHECK, TORCH_WARN, torch::autograd::impl::try_get_grad_accumulator(), caffe2::var, and torch::autograd::AccumulateGrad::variable.

Referenced by torch::autograd::Function< T >::apply().

accumulate()

static void torch::autograd::accumulate ( std::vector< Variable > &  buffer, const size_t  pos, Variable &&  var  )

static

Definition at line 14 of file input_buffer.cpp.

References TORCH_INTERNAL_ASSERT, and caffe2::var.

Referenced by at::native::_index_put_impl_(), at::native::legacy::cuda::_th_put_(), at::native::legacy::cpu::_th_put_(), torch::autograd::InputBuffer::add(), caffe2::DivFunctor< Context >::Backward(), caffe2::MulFunctor< Context >::Backward(), caffe2::MeanReducer< Context >::Backward(), caffe2::CanonicalDims(), at::native::cat_sparse(), torch::autograd::generated::details::cat_tensors_backward(), c10d::checkSplitSizes(), caffe2::MomentsGradientOp< T, Context >::Compute(), caffe2::math::CopyMatrix< std::uint16_t, CPUContext >(), caffe2::BatchMatMulFP16FakeOp< Context, Engine, USE_ACC_FP16, USE_TMP_ACCUMULATOR, USE_CUSTOM_ACC32 >::DoRunWithType(), caffe2::SpatialBNFakeLoweredFp16Op::DoRunWithType(), caffe2::SpatialBNFakeFp16Op::DoRunWithType(), caffe2::BatchMatMulOp< Context, Engine >::DoRunWithType(), caffe2::RemovePaddingOp< Context >::DoRunWithType(), caffe2::SpatialBNOp< Context >::DoRunWithType(), caffe2::SpatialBNGradientOp< Context >::DoRunWithType(), caffe2::UnpackSegmentsOp< Context >::DoRunWithType2(), c10::TensorImpl::Extend(), at::native::flatten_out(), caffe2::CoshGradientFunctor< Context >::Forward(), caffe2::SinhGradientFunctor< Context >::Forward(), caffe2::CubeGradientFunctor< Context >::Forward(), caffe2::GeluGradientFunctor< Context >::Forward(), caffe2::CbrtGradientFunctor< Context >::Forward(), caffe2::RsqrtGradientFunctor< Context >::Forward(), caffe2::AbsGradientFunctor< Context >::Forward(), caffe2::AcosGradientFunctor< Context >::Forward(), caffe2::AsinGradientFunctor< Context >::Forward(), caffe2::AtanGradientFunctor< Context >::Forward(), caffe2::CosGradientFunctor< Context >::Forward(), caffe2::ErfGradientFunctor< Context >::Forward(), caffe2::SinGradientFunctor< Context >::Forward(), caffe2::SoftsignGradientFunctor< Context >::Forward(), caffe2::TanGradientFunctor< Context >::Forward(), caffe2::TanhGradientFunctor< Context >::Forward(), caffe2::EluGradientFunctor< Context >::Forward(), caffe2::HardSigmoidGradientFunctor< Context >::Forward(), caffe2::ReciprocalGradientFunctor< Context >::Forward(), caffe2::ReluNGradientFunctor< Context >::Forward(), caffe2::ReluGradientFunctor< Context >::Forward(), caffe2::SigmoidGradientFunctor< Context >::Forward(), caffe2::emulator::StdOutputFormatter::get_mean(), caffe2::ConvPoolOpBase< Context >::GetDimsSize(), caffe2::HSoftmaxOpBase< T, Context >::getIntermediateOutputSize(), caffe2::DiagonalFillOp< Context >::GetStepSize(), caffe2::math::Im2ColNdNCHW(), at::native::index_put(), at::native::index_put_(), caffe2::math::utils::IsBothEndsBroadcastBinaryOp(), caffe2::math::utils::IsColwiseBroadcastBinaryOp(), caffe2::ConvDNNLowPOp< T, ReluFused >::IsConvGEMM_(), caffe2::math::utils::IsRowwiseBroadcastBinaryOp(), at::native::linalg_tensorinv(), at::native::linalg_tensorsolve(), caffe2::TensorRTOp::MaybeAdjustOutputShape(), c10::multiply_integers(), caffe2::ConvDNNLowPOp< T, ReluFused >::NoIm2ColNHWC_(), at::prod_intlist(), c10::TensorImpl::ReserveSpace(), caffe2::QTensor< Context >::Resize(), caffe2::BatchBucketOneHotOp< Context >::RunOnDevice(), caffe2::PercentileOp< Context >::RunOnDevice(), caffe2::SplitOp< Context >::RunOnDevice(), caffe2::SplitByLengthsOp< Context >::RunOnDevice(), caffe2::LengthsRangeFillOp< Context >::RunOnDevice(), caffe2::TTSparseLengthsSumGradientOp< T, Context >::RunOnDevice(), caffe2::TopKOp< T, Context >::RunOnDevice(), caffe2::TopKGradientOp< T, Context >::RunOnDevice(), caffe2::LengthsToSegmentIdsOp< Context >::RunOnDevice(), caffe2::utils::ConstTensorView< T >::size(), caffe2::SliceImpl(), c10::sum_integers(), at::sum_intlist(), caffe2::ConvDNNLowPPackWeightOp::TakeDepthWise3x3x3FastPath_(), caffe2::TensorInferenceFunction(), caffe2::SimpleNet::TEST_Benchmark(), and caffe2::WeightedSampleDequeueBlobsOp< Context >::WeightedSampleDequeueBlobsOp().

any_variable_requires_grad()

bool torch::autograd::any_variable_requires_grad ( const variable_list &  variables )

inline

Return true if any of the variables in the list require a gradient.

Definition at line 497 of file function.h.

References variable().

Referenced by torch::autograd::Function< T >::apply(), unpack_input(), and wrap_outputs().

applySlicing()

static Variable torch::autograd::applySlicing ( const Variable &  self, PyObject *  index, variable_list &  outIndices, bool  is_tracing, const at::Device &  self_device, const IntArrayRef &  self_sizes, int64_t  specified_dims  )

inlinestatic

Definition at line 134 of file python_variable_indexing.cpp.

References checkUnpackSlice(), dim, at::Tensor::dim(), at::indexing::Ellipsis, at::indexing::handleDimInMultiDimIndexing(), c10::attr::idx(), index, caffe2::int64_t, invalid_index(), torch.jit._trace::is_tracing(), c10::isIntegralType(), c10::kByte, at::legacyExtractDispatchKey(), at::indexing::None, recordSelectTrace(), recordSliceTrace(), at::Tensor::scalar_type(), detail::scalar_type(), sequenceToVariable(), size, c10::ArrayRef< T >::size(), torch.cuda.profiler::start(), step, torch.cuda.profiler::stop(), torch::tensor(), THPUtils_checkLong(), THPUtils_unpackLong(), THPVariable_Check(), and THPVariable_Unpack().

Referenced by THPVariable_getitem(), and THPVariable_setitem().

as_view() [1/2]

Tensor torch::autograd::as_view ( const Tensor &  base, const Tensor &  tensor, bool  is_bw_differentiable, bool  is_fw_differentiable, std::function< Tensor(const Tensor &)>  view_func = nullptr, CreationMeta  creation_meta = CreationMeta::DEFAULT, bool  allow_tensor_metadata_change = true  )

inline

Definition at line 137 of file VariableTypeUtils.h.

References torch::autograd::impl::get_autograd_meta(), at::Tensor::is_view(), isForwardADEnabled(), c10::nullopt, torch::tensor(), and TORCH_CHECK.

as_view() [2/2]

std::vector<Tensor> torch::autograd::as_view ( const Tensor &  base, std::vector< Tensor > &  tensors, bool  is_bw_differentiable, bool  is_fw_differentiable, CreationMeta  creation_meta = CreationMeta::DEFAULT  )

inline

Definition at line 204 of file VariableTypeUtils.h.

References torch::autograd::impl::get_autograd_meta(), at::Tensor::is_view(), isForwardADEnabled(), c10::nullopt, torch::tensor(), caffe2::tensors, TORCH_CHECK, and TORCH_INTERNAL_ASSERT.

autocast_decrement_nesting()

static PyObject* torch::autograd::autocast_decrement_nesting ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 243 of file init.cpp.

References at::autocast::decrement_nesting(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and THPUtils_packInt64().

autocast_increment_nesting()

static PyObject* torch::autograd::autocast_increment_nesting ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 237 of file init.cpp.

References END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, at::autocast::increment_nesting(), and THPUtils_packInt64().

backward() [1/2]

None torch.autograd.backward	(	_TensorOrTensors	tensors,
		Optional[_TensorOrTensors]	grad_tensors = None,
		Optional[bool]	retain_graph = None,
		bool	create_graph = False,
		Optional[_TensorOrTensors]	grad_variables = None,
		Optional[Sequence[torch.Tensor]]	inputs = None
	)

Computes the sum of gradients of given tensors w.r.t. graph leaves.

The graph is differentiated using the chain rule. If any of ``tensors``
are non-scalar (i.e. their data has more than one element) and require
gradient, then the Jacobian-vector product would be computed, in this
case the function additionally requires specifying ``grad_tensors``.
It should be a sequence of matching length, that contains the "vector"
in the Jacobian-vector product, usually the gradient of the differentiated
function w.r.t. corresponding tensors (``None`` is an acceptable value for
all tensors that don't need gradient tensors).

This function accumulates gradients in the leaves - you might need to zero
``.grad`` attributes or set them to ``None`` before calling it.
See :ref:`Default gradient layouts<default-grad-layouts>`
for details on the memory layout of accumulated gradients.

.. note::
    Using this method with ``create_graph=True`` will create a reference cycle
    between the parameter and its gradient which can cause a memory leak.
    We recommend using ``autograd.grad`` when creating the graph to avoid this.
    If you have to use this function, make sure to reset the ``.grad`` fields of your
    parameters to ``None`` after use to break the cycle and avoid the leak.

.. note::

    If you run any forward ops, create ``grad_tensors``, and/or call ``backward``
    in a user-specified CUDA stream context, see
    :ref:`Stream semantics of backward passes<bwd-cuda-stream-semantics>`.

Args:
    tensors (sequence of Tensor): Tensors of which the derivative will be
        computed.
    grad_tensors (sequence of (Tensor or None)): The "vector" in the Jacobian-vector
        product, usually gradients w.r.t. each element of corresponding tensors.
        None values can be specified for scalar Tensors or ones that don't require
        grad. If a None value would be acceptable for all grad_tensors, then this
        argument is optional.
    retain_graph (bool, optional): If ``False``, the graph used to compute the grad
        will be freed. Note that in nearly all cases setting this option to ``True``
        is not needed and often can be worked around in a much more efficient
        way. Defaults to the value of ``create_graph``.
    create_graph (bool, optional): If ``True``, graph of the derivative will
        be constructed, allowing to compute higher order derivative products.
        Defaults to ``False``.
    inputs (sequence of Tensor): Inputs w.r.t. which the gradient will be
        accumulated into ``.grad``. All other Tensors will be ignored. If not
        provided, the gradient is accumulated into all the leaf Tensors that were
        used to compute the attr::tensors. All the provided inputs must be leaf
        Tensors.

Definition at line 68 of file __init__.py.

References _make_grads(), _tensor_or_tensors_to_tuple(), backward(), torch::jit.isinstance(), and c10::aten.len().

Referenced by torch.autograd.function.BackwardCFunction.apply(), backward(), torch.distributed.pipeline.sync.checkpoint.Checkpoint.backward(), torch.utils.checkpoint.CheckpointFunction.backward(), torch::distributed::rpc::PyRRef.backward(), torch.tensor.Tensor.backward(), pt_engine.TorchTensorEngine.backward(), torch.sparse.mm(), and torch.distributed.pipeline.sync._balance.profile.profile_times().

backward() [2/2]

TORCH_API void torch::autograd::backward	(	const variable_list &	tensors,
		const variable_list &	grad_tensors = {},
		c10::optional< bool >	retain_graph = c10::nullopt,
		bool	create_graph = false,
		const variable_list &	inputs = {}
	)

Computes the sum of gradients of given tensors with respect to graph leaves.

The graph is differentiated using the chain rule. If any of tensors are non-scalar (i.e. their data has more than one element) and require gradient, then the Jacobian-vector product would be computed, in this case the function additionally requires specifying grad_tensors. It should be a sequence of matching length, that contains the "vector" in the Jacobian-vector product, usually the gradient of the differentiated function w.r.t. corresponding tensors (torch::Tensor() is an acceptable value for all tensors that don't need gradient tensors).

This function accumulates gradients in the leaves - you might need to zero them before calling it.

Parameters

tensors	Tensors of which the derivative will be computed.
grad_tensors	The "vector" in the Jacobian-vector product, usually gradients w.r.t. each element of corresponding tensors. torch::Tensor() values can be specified for scalar Tensors or ones that don't require grad. If a torch::Tensor() value would be acceptable for all grad_tensors, then this argument is optional.
retain_graph	If false, the graph used to compute the grad will be freed. Note that in nearly all cases setting this option to true is not needed and often can be worked around in a much more efficient way. Defaults to the value of create_graph.
create_graph	If true, graph of the derivative will be constructed, allowing to compute higher order derivative products. Defaults to false.
inputs	Inputs w.r.t. which the gradient will be accumulated into at::Tensor::grad. All other Tensors will be ignored. If not provided, the gradient is accumulated into all the leaf Tensors that were used to compute param tensors. All the provided inputs must be leaf Tensors.

Definition at line 130 of file autograd.cpp.

References _make_grads(), inputs, run_backward(), caffe2::tensors, and c10::optional< T >::value().

call_function()

static variable_list torch::autograd::call_function ( std::shared_ptr< GraphTask > &  graph_task, Node *  func, InputBuffer &  inputBuffer  )

static

Definition at line 635 of file engine.cpp.

References call_post_hooks(), call_pre_hooks(), checkpoint_valid, caffe2.perfkernels.hp_emblookup_codegen::fn, inputs, outputs, validate_outputs(), and torch::autograd::InputBuffer::variables().

Referenced by torch::autograd::Engine::evaluate_function().

call_post_hooks()

static variable_list torch::autograd::call_post_hooks ( Node &  fn, variable_list  outputs, const variable_list &  inputs  )

static

Definition at line 539 of file engine.cpp.

References caffe2.perfkernels.hp_emblookup_codegen::fn, inputs, and outputs.

Referenced by call_function().

call_pre_hooks()

static variable_list torch::autograd::call_pre_hooks ( Node &  fn, variable_list  inputs  )

static

Definition at line 532 of file engine.cpp.

References caffe2.perfkernels.hp_emblookup_codegen::fn, and inputs.

Referenced by call_function().

check_inplace() [1/2]

void torch::autograd::check_inplace ( const Tensor &  tensor, bool  requires_grad  )

inline

Definition at line 49 of file VariableTypeUtils.h.

References at::Tensor::_base(), AT_ERROR, torch::autograd::impl::get_autograd_meta(), handle_view_on_rebase(), at::GradMode::is_enabled(), at::Tensor::is_view(), at::Tensor::requires_grad(), fastrnns.scratch::requires_grad, and torch::tensor().

Referenced by check_inplace().

check_inplace() [2/2]

void torch::autograd::check_inplace ( const TensorList  tensors, bool  requires_grad  )

inline

Definition at line 68 of file VariableTypeUtils.h.

References check_inplace(), fastrnns.scratch::requires_grad, torch::tensor(), and caffe2::tensors.

check_input_variables()

TORCH_API void torch::autograd::check_input_variables	(	const char *	name,
		const variable_list &	inputs,
		int	args,
		int	required_args = -1,
		bool	allow_undefined = false
	)

Checks that inputs contains exactly args items and that the first required_args items are not nullptr.

If not specified, required_args defaults to args.

Definition at line 40 of file utils.cpp.

References compare-fastrnn-results::args, inputs, and name.

Referenced by torch::autograd::AccumulateGrad::apply(), torch::autograd::CopyBackwards::apply(), and torch::autograd::CopySlices::apply().

check_no_requires_grad() [1/4]

void torch::autograd::check_no_requires_grad ( const c10::List< c10::optional< Tensor > > &  tensors, const char *  name  )

inline

Definition at line 279 of file VariableTypeUtils.h.

References check_no_requires_grad(), name, torch::tensor(), and caffe2::tensors.

check_no_requires_grad() [2/4]

void torch::autograd::check_no_requires_grad ( const c10::optional< Tensor > &  tensor, const char *  name  )

inline

Definition at line 267 of file VariableTypeUtils.h.

References check_no_requires_grad(), name, and torch::tensor().

check_no_requires_grad() [3/4]

void torch::autograd::check_no_requires_grad ( const Tensor &  tensor, const char *  name  )

inline

Definition at line 257 of file VariableTypeUtils.h.

References name, torch::tensor(), and caffe2::var.

Referenced by check_no_requires_grad().

check_no_requires_grad() [4/4]

void torch::autograd::check_no_requires_grad ( TensorList  tensors, const char *  name  )

inline

Definition at line 273 of file VariableTypeUtils.h.

References check_no_requires_grad(), name, torch::tensor(), and caffe2::tensors.

check_variable_result()

TORCH_API void torch::autograd::check_variable_result	(	const Variable &	original,
		const Variable &	result,
		std::string	hook_name
	)

Definition at line 160 of file custom_function.cpp.

References hook_name().

Referenced by check_single_result().

checkUnpackSlice()

static void torch::autograd::checkUnpackSlice ( PyObject *  index, Py_ssize_t *  start_ptr, Py_ssize_t *  stop_ptr, Py_ssize_t *  step_ptr  )

inlinestatic

Definition at line 111 of file python_variable_indexing.cpp.

References index, and THPUtils_unpackSlice.

Referenced by applySlicing(), THPVariable_getitem(), and THPVariable_setitem().

clear_autocast_cache()

static PyObject* torch::autograd::clear_autocast_cache ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 230 of file init.cpp.

References at::autocast::clear_cache(), END_HANDLE_TH_ERRORS, and HANDLE_TH_ERRORS.

collect_next_edges()

template<typename... Variables>

edge_list torch::autograd::collect_next_edges

(

Variables &&...

variables

)

Return the next edges of all the given variables, or tuples of variables.

Definition at line 506 of file function.h.

References at::IterArgs< F >::apply(), and torch::autograd::detail::MakeNextFunctionList::next_edges.

Referenced by torch::distributed::autograd::addSendRpcBackward(), torch::autograd::Function< T >::apply(), torch::autograd::Scatter::apply(), torch::autograd::Gather::apply(), torch::autograd::VariableHooks::grad_fn(), unpack_input(), and wrap_outputs().

compute_requires_grad()

template<typename... Args>

bool torch::autograd::compute_requires_grad ( Args &&...  args )

inline

Definition at line 50 of file utils.h.

References at::IterArgs< F >::apply(), compare-fastrnn-results::args, at::GradMode::is_enabled(), and torch::autograd::ComputeRequiresGrad::out.

Referenced by torch::distributed::autograd::addRecvRpcBackward(), torch::autograd::Scatter::apply(), torch::autograd::Gather::apply(), and torch::distributed::autograd::getMessageWithAutograd().

count_specified_dimensions()

static int64_t torch::autograd::count_specified_dimensions ( PyObject *  index )

inlinestatic

Definition at line 56 of file python_variable_indexing.cpp.

References torch::check_has_torch_function(), index, caffe2::int64_t, c10::kBool, c10::kByte, size, THPVariable_Check(), THPVariable_CheckExact(), and caffe2::var.

Referenced by THPVariable_getitem(), and THPVariable_setitem().

CppFunction_pynew()

template<typename Ctor >

PyObject* torch::autograd::CppFunction_pynew	(	PyTypeObject *	type,
		PyObject *	args,
		PyObject *	kwds
	)

Definition at line 19 of file python_cpp_function.h.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, THPPointer< T >::get(), HANDLE_TH_ERRORS, THPPointer< T >::release(), and type.

create_gradient_edge()

void torch::autograd::create_gradient_edge ( Variable &  variable, std::shared_ptr< Node >  function  )

inline

Create an Edge between the given variable and the function, which is assumed to be the gradient function of this variable (i.e.

the function through which this variable is backpropagated during the backward pass). This sets the grad_fn property of the variable. This function assumes that the Variable is a new input to the gradient function and its input_nr thus equal to function->num_inputs(). Additionally, it increments the Node's number of inputs by one. Approximately equivalent to variable.set_gradient_edge(function, function->add_input_metadata(variable.dispatch_type(), variable.sizes())). If you don't want the Node's num_inputs to be incremented, use set_gradient_edge directly.

Definition at line 488 of file function.h.

References torch::autograd::impl::set_gradient_edge(), and variable().

Referenced by wrap_outputs().

createForwardFunctionPyTypeObject()

template<typename Ctor >

PyTypeObject* torch::autograd::createForwardFunctionPyTypeObject	(	PyTypeObject &	type,
		const char *	name,
		PyGetSetDef *	function_properties = nullptr,
		PyMethodDef *	function_methods = nullptr
	)

Definition at line 56 of file python_cpp_function.h.

References _initFunctionPyTypeObject(), name, and type.

deleteNode()

TORCH_API void torch::autograd::deleteNode

(

Node *

function

)

Definition at line 81 of file function.cpp.

References gatherFunctions(), and torch.distributions.constraints::stack.

Referenced by torch::autograd::Function< T >::apply().

dispatch_arange() [1/4]

Tensor torch::autograd::dispatch_arange ( Scalar  end, const TensorOptions &  options  )

inline

Definition at line 69 of file python_torch_functions.cpp.

References at::native::arange(), matmul_dlmc_bench::end, torch::utils::maybe_initialize_cuda(), and caffe2.perfkernels.hp_emblookup_codegen::options.

dispatch_arange() [2/4]

Tensor torch::autograd::dispatch_arange ( Scalar  end, Tensor  result  )

inline

Definition at line 64 of file python_torch_functions.cpp.

References at::native::arange_out(), and matmul_dlmc_bench::end.

Referenced by THPVariable_arange().

dispatch_arange() [3/4]

Tensor torch::autograd::dispatch_arange ( Scalar  start, Scalar  end, Scalar  step, const TensorOptions &  options  )

inline

Definition at line 80 of file python_torch_functions.cpp.

References at::native::arange(), matmul_dlmc_bench::end, torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, torch.cuda.profiler::start(), and step.

dispatch_arange() [4/4]

Tensor torch::autograd::dispatch_arange ( Scalar  start, Scalar  end, Scalar  step, Tensor  result  )

inline

Definition at line 75 of file python_torch_functions.cpp.

References at::native::arange_out(), matmul_dlmc_bench::end, torch.cuda.profiler::start(), and step.

dispatch_contiguous()

static Tensor torch::autograd::dispatch_contiguous ( const Tensor &  self, at::MemoryFormat  memory_format  )

static

Definition at line 229 of file python_variable_methods.cpp.

References at::device_of(), and c10::memory_format().

Referenced by THPVariable_contiguous().

dispatch_copy_()

static Tensor torch::autograd::dispatch_copy_ ( Tensor &  self, const Tensor &  other, bool  non_blocking  )

static

Definition at line 272 of file python_variable_methods.cpp.

References at::device_of(), and at::meta::other.

Referenced by THPVariable_copy_().

dispatch_full() [1/3]

Tensor torch::autograd::dispatch_full ( IntArrayRef  size, Scalar  fill_val, c10::optional< DimnameList >  names, const TensorOptions &  options  )

inline

Definition at line 201 of file python_torch_functions.cpp.

References torch::jit::full, torch::utils::maybe_initialize_cuda(), microbenchmarks::names, caffe2.perfkernels.hp_emblookup_codegen::options, and size.

dispatch_full() [2/3]

Tensor torch::autograd::dispatch_full ( IntArrayRef  size, Scalar  fill_val, const TensorOptions &  options  )

inline

Definition at line 192 of file python_torch_functions.cpp.

References torch::jit::full, torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, and size.

Referenced by THPVariable_full().

dispatch_full() [3/3]

Tensor torch::autograd::dispatch_full ( IntArrayRef  size, Scalar  fill_val, Tensor  result  )

inline

Definition at line 211 of file python_torch_functions.cpp.

References torch::jit::full_out, and size.

dispatch_invert()

static Tensor torch::autograd::dispatch_invert ( const Tensor &  self )

static

Definition at line 389 of file python_variable_methods.cpp.

References at::device_of().

Referenced by THPVariable_invert().

dispatch_is_contiguous()

bool torch::autograd::dispatch_is_contiguous ( Tensor &  self, MemoryFormat  memory_format  )

inline

Definition at line 764 of file python_variable_methods.cpp.

References c10::memory_format().

Referenced by THPVariable_is_contiguous().

dispatch_nonzero() [1/3]

static Tensor torch::autograd::dispatch_nonzero ( const Tensor &  self )

static

Definition at line 389 of file python_torch_functions.cpp.

References at::device_of().

Referenced by THPVariable_nonzero().

dispatch_nonzero() [2/3]

static Tensor torch::autograd::dispatch_nonzero ( const Tensor &  self )

static

Definition at line 454 of file python_variable_methods.cpp.

References at::device_of().

dispatch_nonzero() [3/3]

static Tensor torch::autograd::dispatch_nonzero ( const Tensor &  self, Tensor  out  )

static

Definition at line 395 of file python_torch_functions.cpp.

References at::device_of(), and out.

dispatch_nonzero_numpy() [1/2]

static std::vector<Tensor> torch::autograd::dispatch_nonzero_numpy ( const Tensor &  self )

static

Definition at line 401 of file python_torch_functions.cpp.

References at::device_of().

Referenced by THPVariable_nonzero().

dispatch_nonzero_numpy() [2/2]

static std::vector<Tensor> torch::autograd::dispatch_nonzero_numpy ( const Tensor &  self )

static

Definition at line 460 of file python_variable_methods.cpp.

References at::device_of().

dispatch_randint() [1/8]

Tensor torch::autograd::dispatch_randint ( int64_t  high, IntArrayRef  size, c10::optional< Generator >  generator, const TensorOptions &  options  )

inline

Definition at line 277 of file python_torch_functions.cpp.

References torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, at::native::randint(), and size.

dispatch_randint() [2/8]

Tensor torch::autograd::dispatch_randint ( int64_t  high, IntArrayRef  size, c10::optional< Generator >  generator, Tensor  result  )

inline

Definition at line 273 of file python_torch_functions.cpp.

References at::native::randint_out(), and size.

Referenced by THPVariable_randint().

dispatch_randint() [3/8]

Tensor torch::autograd::dispatch_randint ( int64_t  high, IntArrayRef  size, const TensorOptions &  options  )

inline

Definition at line 286 of file python_torch_functions.cpp.

References torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, at::native::randint(), and size.

dispatch_randint() [4/8]

Tensor torch::autograd::dispatch_randint ( int64_t  high, IntArrayRef  size, Tensor  result  )

inline

Definition at line 282 of file python_torch_functions.cpp.

References at::native::randint_out(), and size.

dispatch_randint() [5/8]

Tensor torch::autograd::dispatch_randint ( int64_t  low, int64_t  high, IntArrayRef  size, c10::optional< Generator >  generator, const TensorOptions &  options  )

inline

Definition at line 295 of file python_torch_functions.cpp.

References torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, at::native::randint(), and size.

dispatch_randint() [6/8]

Tensor torch::autograd::dispatch_randint ( int64_t  low, int64_t  high, IntArrayRef  size, c10::optional< Generator >  generator, Tensor  result  )

inline

Definition at line 291 of file python_torch_functions.cpp.

References at::native::randint_out(), and size.

dispatch_randint() [7/8]

Tensor torch::autograd::dispatch_randint ( int64_t  low, int64_t  high, IntArrayRef  size, const TensorOptions &  options  )

inline

Definition at line 304 of file python_torch_functions.cpp.

References torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, at::native::randint(), and size.

dispatch_randint() [8/8]

Tensor torch::autograd::dispatch_randint ( int64_t  low, int64_t  high, IntArrayRef  size, Tensor  result  )

inline

Definition at line 300 of file python_torch_functions.cpp.

References at::native::randint_out(), and size.

dispatch_range() [1/2]

Tensor torch::autograd::dispatch_range ( Scalar  start, Scalar  end, Scalar  step, const TensorOptions &  options  )

inline

Definition at line 150 of file python_torch_functions.cpp.

References matmul_dlmc_bench::end, torch::utils::maybe_initialize_cuda(), caffe2.perfkernels.hp_emblookup_codegen::options, c10::prim::range(), torch.cuda.profiler::start(), and step.

dispatch_range() [2/2]

Tensor torch::autograd::dispatch_range ( Scalar  start, Scalar  end, Scalar  step, Tensor  result  )

inline

Definition at line 144 of file python_torch_functions.cpp.

References at::device_of(), matmul_dlmc_bench::end, torch.cuda.profiler::start(), and step.

Referenced by THPVariable_range().

dispatch_to() [1/4]

static Tensor torch::autograd::dispatch_to ( const Tensor &  self, bool  non_blocking, bool  copy, c10::optional< c10::MemoryFormat >  optional_memory_format  )

static

Definition at line 418 of file python_variable_methods.cpp.

References c10::aten::copy(), c10::memory_format(), and caffe2.perfkernels.hp_emblookup_codegen::options.

dispatch_to() [2/4]

static Tensor torch::autograd::dispatch_to ( const Tensor &  self, Device  device, bool  non_blocking, bool  copy, c10::optional< c10::MemoryFormat >  optional_memory_format  )

static

Definition at line 408 of file python_variable_methods.cpp.

References c10::aten::copy(), device, c10::memory_format(), and caffe2.perfkernels.hp_emblookup_codegen::options.

Referenced by THPVariable_cpu(), THPVariable_cuda(), THPVariable_to(), THPVariable_to_type(), THPVariable_type(), and THPVariable_xpu().

dispatch_to() [3/4]

static Tensor torch::autograd::dispatch_to ( const Tensor &  self, Device  device, ScalarType  dtype, bool  non_blocking, bool  copy, c10::optional< c10::MemoryFormat >  optional_memory_format  )

static

Definition at line 429 of file python_variable_methods.cpp.

References c10::aten::copy(), device, and caffe2::dtype.

dispatch_to() [4/4]

static Tensor torch::autograd::dispatch_to ( const Tensor &  self, ScalarType  dtype, bool  non_blocking, bool  copy, c10::optional< c10::MemoryFormat >  optional_memory_format  )

static

Definition at line 423 of file python_variable_methods.cpp.

References c10::aten::copy(), and caffe2::dtype.

dispatch_to_Bool()

static bool torch::autograd::dispatch_to_Bool ( const Tensor &  self )

static

Definition at line 324 of file python_variable_methods.cpp.

References at::device_of(), and at::native::numel().

Referenced by THPVariable_item().

dispatch_to_CComplexDouble()

static c10::complex<double> torch::autograd::dispatch_to_CComplexDouble ( const Tensor &  self )

static

Definition at line 306 of file python_variable_methods.cpp.

References at::device_of(), and at::native::numel().

Referenced by THPVariable_complex_scalar(), and THPVariable_item().

dispatch_to_CDouble()

static double torch::autograd::dispatch_to_CDouble ( const Tensor &  self )

static

Definition at line 297 of file python_variable_methods.cpp.

References at::device_of(), and at::native::numel().

Referenced by THPVariable_float_scalar(), THPVariable_integral_scalar(), and THPVariable_item().

dispatch_to_CLong()

static int64_t torch::autograd::dispatch_to_CLong ( const Tensor &  self )

static

Definition at line 315 of file python_variable_methods.cpp.

References at::device_of(), caffe2::int64_t, and at::native::numel().

Referenced by THPVariable_index_scalar(), THPVariable_integral_scalar(), and THPVariable_item().

engine_stub()

std::atomic<EngineStub> torch::autograd::engine_stub

(

Engine::get_base_engine

)

Referenced by torch::autograd::Engine::get_default_engine(), and set_default_engine_stub().

ensure_tuple()

bool torch::autograd::ensure_tuple ( THPObjectPtr &  obj )

inline

Cast an object into a tuple, if it is not a tuple already.

Returns true if the original object was not a tuple.

Definition at line 61 of file python_function.h.

References THPPointer< T >::get(), and THPPointer< T >::release().

Referenced by torch::autograd::PyNode::apply(), process_outputs(), and THPFunction_do_backward().

extract_vars()

template<typename... Args>

void torch::autograd::extract_vars ( std::vector< bool > &  is_var, variable_list &  list, Args &&...  args  )

inline

Definition at line 192 of file custom_function.h.

References at::IterArgs< F >::apply(), compare-fastrnn-results::args, and c10::prim::list().

Referenced by torch::autograd::Function< T >::apply().

flatten_tensor_args()

template<typename... Args>

variable_list torch::autograd::flatten_tensor_args ( Args &&...  args )

inline

Definition at line 129 of file VariableTypeUtils.h.

References compare-fastrnn-results::args, torch::count_tensors(), Flatten, and out.

functionToPyObject()

PyObject * torch::autograd::functionToPyObject

(

const std::shared_ptr< Node > &

cdata

)

Definition at line 202 of file python_cpp_function.cpp.

References cpp_function_types, caffe2.perfkernels.hp_emblookup_codegen::fn, THPPointer< T >::get(), caffe2::it, THPPointer< T >::release(), type, and torch::autograd::DefaultFunctionType::type.

Referenced by torch::autograd::PyAnomalyMetadata::assign_parent(), THPCppFunction_next_functions(), THPFunction_next_functions(), and THPVariable_get_grad_fn().

gatherFunctions()

static void torch::autograd::gatherFunctions ( Node *  func, std::vector< std::shared_ptr< Node > > &  stack  )

static

Definition at line 47 of file function.cpp.

References torch::autograd::Node::next_edges(), torch::autograd::Node::release_variables(), and torch.distributions.constraints::stack.

Referenced by deleteNode().

grad() [1/2]

Tuple[torch.Tensor, ...] torch.autograd.grad	(	_TensorOrTensors	outputs,
		_TensorOrTensors	inputs,
		Optional[_TensorOrTensors]	grad_outputs = None,
		Optional[bool]	retain_graph = None,
		bool	create_graph = False,
		bool	only_inputs = True,
		bool	allow_unused = False
	)

Computes and returns the sum of gradients of outputs w.r.t. the inputs.

``grad_outputs`` should be a sequence of length matching ``output``
containing the "vector" in Jacobian-vector product, usually the pre-computed
gradients w.r.t. each of the outputs. If an output doesn't require_grad,
then the gradient can be ``None``).

If ``only_inputs`` is ``True``, the function will only return a list of gradients
w.r.t the specified inputs. If it's ``False``, then gradient w.r.t. all remaining
leaves will still be computed, and will be accumulated into their ``.grad``
attribute.

.. note::

    If you run any forward ops, create ``grad_outputs``, and/or call ``grad``
    in a user-specified CUDA stream context, see
    :ref:`Stream semantics of backward passes<bwd-cuda-stream-semantics>`.

Args:
    outputs (sequence of Tensor): outputs of the differentiated function.
    inputs (sequence of Tensor): Inputs w.r.t. which the gradient will be
        returned (and not accumulated into ``.grad``).
    grad_outputs (sequence of Tensor): The "vector" in the Jacobian-vector product.
        Usually gradients w.r.t. each output. None values can be specified for scalar
        Tensors or ones that don't require grad. If a None value would be acceptable
        for all grad_tensors, then this argument is optional. Default: None.
    retain_graph (bool, optional): If ``False``, the graph used to compute the grad
        will be freed. Note that in nearly all cases setting this option to ``True``
        is not needed and often can be worked around in a much more efficient
        way. Defaults to the value of ``create_graph``.
    create_graph (bool, optional): If ``True``, graph of the derivative will
        be constructed, allowing to compute higher order derivative products.
        Default: ``False``.
    allow_unused (bool, optional): If ``False``, specifying inputs that were not
        used when computing outputs (and therefore their grad is always zero)
        is an error. Defaults to ``False``.

Definition at line 150 of file __init__.py.

References _make_grads(), _tensor_or_tensors_to_tuple(), grad(), torch.handle_torch_function(), torch.overrides.has_torch_function, torch::jit.isinstance(), and c10::aten.len().

Referenced by torch.autograd.functional._autograd_grad(), torch::autograd::generated::details._euclidean_dist_backward(), torch::autograd::generated::details._fused_dropout_backward(), torch.distributions.kl._kl_expfamily_expfamily(), torch::autograd::generated::details._sparse_addmm_sparse_backward(), torch::autograd::generated::details.angle_backward(), torch::autograd::AccumulateGrad.apply(), torch::autograd::CopyBackwards.apply(), torch::autograd::UndefinedGradBackward.apply(), torch::autograd::CopySlices.apply(), torch::autograd::generated::details.as_strided_backward(), torch::autograd::generated::details.atan2_backward(), torch::autograd::generated::details.binary_cross_entropy_double_backward(), torch::autograd::generated::details.binary_cross_entropy_double_backward_grad_output(), torch::autograd::generated::details.cat_tensors_backward(), torch::autograd::generated::details.cholesky_backward(), torch::autograd::generated::details.cholesky_inverse_backward(), torch::autograd::generated::details.clamp_backward(), torch::autograd::generated::details.constant_pad_nd_backward(), torch.nn.grad.conv1d_input(), torch.nn.grad.conv1d_weight(), torch.nn.grad.conv2d_input(), torch.nn.grad.conv2d_weight(), torch.nn.grad.conv3d_input(), torch.nn.grad.conv3d_weight(), torch::autograd::generated::details.copysign_tensor_self_backward(), torch::autograd::generated::details.deg2rad_backward(), torch::autograd::generated::details.det_backward(), torch::autograd::generated::details.div_tensor_other_backward(), torch::autograd::generated::details.div_tensor_self_backward(), torch::autograd::generated::details.elu_double_backward(), torch::autograd::generated::details.embedding_dense_double_backward(), torch.distributions.exp_family.ExponentialFamily.entropy(), torch::autograd::ForwardADLevel.erase(), torch::autograd::generated::details.evenly_distribute_backward(), torch::autograd::generated::details.fft_c2r_backward(), torch::autograd::generated::details.fft_r2c_backward(), torch.autograd.gradcheck.get_analytical_jacobian(), torch::autograd::generated::details.glu_double_backward(), torch::autograd::generated::details.glu_double_backward_grad_output(), grad(), torch.autograd.gradcheck.gradcheck(), torch.autograd.gradcheck.gradgradcheck(), torch::autograd::generated::details.index_backward(), torch::autograd::generated::details.infinitely_differentiable_logit_backward(), torch::autograd::ForwardADLevel.insert(), torch::autograd::generated::details.kl_div_double_backward_grad_output(), torch::autograd::generated::details.l1_loss_double_backward(), torch::autograd::generated::details.l1_loss_double_backward_grad_output(), torch::autograd::generated::details.log1p_backward(), torch::autograd::generated::details.log_sigmoid_double_backward(), torch::autograd::generated::details.log_softmax_double_backward(), torch::autograd::generated::details.logcumsumexp_backward(), torch::autograd::generated::details.logdet_backward(), torch::autograd::generated::details.logsumexp_backward(), torch::autograd::generated::details.masked_scatter_backward(), torch::autograd::generated::details.max_pool_double_backward(), torch::autograd::generated::details.mean_backward(), torch::autograd::generated::details.mm_mat1_backward(), torch::autograd::generated::details.mm_mat2_backward(), torch::autograd::generated::details.mse_loss_double_backward(), torch::autograd::generated::details.mse_loss_double_backward_grad_output(), torch::autograd::generated::details.mul_tensor_backward(), torch::autograd::generated::details.mvlgamma_backward(), torch::autograd::generated::details.nansum_backward(), torch::autograd::generated::details.norm_backward(), torch::autograd::utils.obeys_layout_contract(), torch::autograd::generated::details.permute_backwards(), torch::autograd::generated::details.pow_backward(), torch::autograd::generated::details.pow_backward_exponent(), torch::autograd::generated::details.pow_backward_self(), torch::autograd::generated::details.prod_backward(), torch::autograd::generated::details.prod_safe_zeros_backward(), torch::autograd::generated::details.rad2deg_backward(), torch::autograd::generated::details.renorm_backward(), torch::autograd::generated::details.repeat_backward(), torch::autograd::generated::details.scale_grad_by_count(), torch::autograd::generated::details.sgn_backward(), torch::autograd::generated::details.slice_backward_wrapper(), torch::autograd::generated::details.smooth_l1_loss_double_backward(), torch::autograd::generated::details.smooth_l1_loss_double_backward_grad_output(), torch::autograd::generated::details.soft_margin_loss_double_backward(), torch::autograd::generated::details.soft_margin_loss_double_backward_grad_output(), torch::autograd::generated::details.softmax_double_backward(), torch::autograd::generated::details.softplus_double_backward(), torch::autograd::generated::details.solve_backward_A(), torch::autograd::generated::details.solve_backward_self(), torch::autograd::generated::details.sparse_sparse_matmul_backward(), torch::autograd::generated::details.std_backward(), torch::autograd::generated::details.sum_backward(), torch.autograd.gradcheck.test_batched_grad(), validate_outputs(), torch::autograd::generated::details.var_backward(), torch::autograd::generated::details.var_std_mean_backward(), torch.jit._trace.verify(), and torch._vmap_internals.vmap().

grad() [2/2]

TORCH_API variable_list torch::autograd::grad	(	const variable_list &	outputs,
		const variable_list &	inputs,
		const variable_list &	grad_outputs = {},
		c10::optional< bool >	retain_graph = c10::nullopt,
		bool	create_graph = false,
		bool	allow_unused = false
	)

Computes and returns the sum of gradients of outputs with respect to the inputs.

grad_outputs should be a sequence of length matching output containing the "vector" in Jacobian-vector product, usually the pre-computed gradients w.r.t. each of the outputs. If an output doesn't require_grad, then the gradient can be torch::Tensor()).

Parameters

outputs	outputs of the differentiated function.
inputs	Inputs w.r.t. which the gradient will be returned (and not accumulated into at::Tensor::grad).
grad_outputs	The "vector" in the Jacobian-vector product. Usually gradients w.r.t. each output. torch::Tensor() values can be specified for scalar Tensors or ones that don't require grad. If a torch::Tensor() value would be acceptable for all grad_tensors, then this argument is optional. Default: {}.
retain_graph	If false, the graph used to compute the grad will be freed. Note that in nearly all cases setting this option to true is not needed and often can be worked around in a much more efficient way. Defaults to the value of create_graph.
create_graph	If true, graph of the derivative will be constructed, allowing to compute higher order derivative products. Default: false.
allow_unused	If false, specifying inputs that were not used when computing outputs (and therefore their grad is always zero) is an error. Defaults to false.

Definition at line 143 of file autograd.cpp.

References _make_grads(), inputs, outputs, run_backward(), and c10::optional< T >::value().

handle_view_on_rebase()

void torch::autograd::handle_view_on_rebase	(	DifferentiableViewMeta *	diff_view_meta,
		bool	indirect
	)

See NOTE [ View + Inplace detection ] for justification of the logic below

Definition at line 493 of file variable.cpp.

References c10::str(), TORCH_CHECK, TORCH_INTERNAL_ASSERT, and TORCH_WARN.

Referenced by check_inplace(), and torch::autograd::VariableHooks::grad_fn().

increment_version()

void torch::autograd::increment_version ( Tensor &  t )

inline

Definition at line 116 of file VariableTypeUtils.h.

References torch::autograd::impl::bump_version().

init_legacy_variable()

void torch::autograd::init_legacy_variable

(

PyObject *

module

)

Definition at line 132 of file python_legacy_variable.cpp.

References module, and THPLegacyVariableType.

Referenced by initModule().

initFFTFunctions()

void torch::autograd::initFFTFunctions

(

PyObject *

module

)

Definition at line 50 of file python_fft_functions.cpp.

References torch::fft::fft, module, and THPFFTVariableFunctionsModule.

Referenced by initModule().

initLinalgFunctions()

void torch::autograd::initLinalgFunctions

(

PyObject *

module

)

Definition at line 36 of file python_linalg_functions.cpp.

References module, and THPLinalgVariableFunctionsModule.

Referenced by initModule().

initNNFunctions()

void torch::autograd::initNNFunctions

(

PyObject *

module

)

Definition at line 81 of file python_nn_functions.cpp.

References module, and THPNNVariableFunctionsModule.

Referenced by initModule().

initTensorImplConversion()

void torch::autograd::initTensorImplConversion

(

PyObject *

module

)

Definition at line 801 of file python_variable.cpp.

References at::cpp_custom_type_hack::cast(), c10::intrusive_ptr< TTarget, NullType >::get(), at::Tensor::getIntrusivePtr(), handle, matmul_dlmc_bench::m, module, diagnose_protobuf::p, ptr, torch::tensor(), TORCH_CHECK, c10::intrusive_ptr< TTarget, NullType >::unsafe_reclaim_from_nonowning(), and at::Tensor::wrap_tensor_impl().

Referenced by THPVariable_initModule().

initTorchFunctions()

void torch::autograd::initTorchFunctions

(

PyObject *

module

)

Definition at line 539 of file python_torch_functions.cpp.

References module, THPVariableFunctions, and THPVariableFunctionsModule.

Referenced by THPVariable_initModule().

invalid_index()

static void torch::autograd::invalid_index ( PyObject *  obj )

inlinestatic

Definition at line 80 of file python_variable_indexing.cpp.

Referenced by applySlicing().

is_anomaly_mode_enabled()

static PyObject* torch::autograd::is_anomaly_mode_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 299 of file init.cpp.

References END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and torch::autograd::AnomalyMode::is_enabled().

is_autocast_enabled()

static PyObject* torch::autograd::is_autocast_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 220 of file init.cpp.

References END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and at::autocast::is_enabled().

is_compatible_type()

static bool torch::autograd::is_compatible_type ( const at::TensorOptions &  expected, const at::TensorOptions &  actual  )

static

Definition at line 546 of file engine.cpp.

References c10::TensorOptions::device(), c10::TensorOptions::is_sparse(), and c10::TensorOptions::type_equal().

Referenced by validate_outputs().

is_forward_AD_enabled()

static PyObject* torch::autograd::is_forward_AD_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 259 of file init.cpp.

References END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and isForwardADEnabled().

is_grad_enabled()

static PyObject* torch::autograd::is_grad_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 279 of file init.cpp.

References END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and at::GradMode::is_enabled().

isForwardADEnabled()

bool TORCH_API torch::autograd::isForwardADEnabled

(

)

Definition at line 82 of file forward_grad.cpp.

Referenced by as_view(), and is_forward_AD_enabled().

make_saved_variable_list() [1/2]

std::vector<SavedVariable> torch::autograd::make_saved_variable_list ( const c10::List< c10::optional< at::Tensor > > &  tensors )

inline

Definition at line 294 of file VariableTypeUtils.h.

References c10::fmap(), torch::tensor(), and caffe2::tensors.

make_saved_variable_list() [2/2]

std::vector<SavedVariable> torch::autograd::make_saved_variable_list ( TensorList  tensors )

inline

Definition at line 288 of file VariableTypeUtils.h.

References c10::fmap(), torch::tensor(), and caffe2::tensors.

python_enter_dual_level()

static PyObject* torch::autograd::python_enter_dual_level ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 309 of file init.cpp.

References END_HANDLE_TH_ERRORS, torch.autograd.forward_ad::enter_dual_level(), HANDLE_TH_ERRORS, caffe2::int64_t, and torch::autograd::utils::wrap().

python_exit_dual_level()

static PyObject* torch::autograd::python_exit_dual_level ( PyObject *  _unused, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 317 of file init.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, torch.autograd.forward_ad::exit_dual_level(), HANDLE_TH_ERRORS, and configure::parser.

python_functions()

PyMethodDef * torch::autograd::python_functions

(

)

Definition at line 349 of file init.cpp.

References methods.

Referenced by initModule().

rebase_history() [1/2]

void torch::autograd::rebase_history ( std::vector< Variable > &&  vars, std::shared_ptr< Node >  grad_fn  )

inline

Definition at line 102 of file VariableTypeUtils.h.

References at::native::output_nr(), torch::autograd::impl::rebase_history(), and caffe2::var.

rebase_history() [2/2]

void torch::autograd::rebase_history ( Variable &  var, std::shared_ptr< Node >  grad_fn  )

inline

Definition at line 95 of file VariableTypeUtils.h.

References torch::autograd::impl::rebase_history(), and caffe2::var.

recordSelectTrace()

static void torch::autograd::recordSelectTrace ( const Tensor &  index_tensor )

inlinestatic

Definition at line 130 of file python_variable_indexing.cpp.

References c10::IntType::get(), and torch::jit::tracer::ArgumentStash::stashValue().

Referenced by applySlicing(), THPVariable_getitem(), and THPVariable_setitem().

recordSliceTrace()

static void torch::autograd::recordSliceTrace ( PyObject *  obj )

inlinestatic

Definition at line 117 of file python_variable_indexing.cpp.

References c10::IntType::get(), torch::jit::tracer::ArgumentStash::stashValue(), THPVariable_Check(), and THPVariable_Unpack().

Referenced by applySlicing(), THPVariable_getitem(), and THPVariable_setitem().

registerCppFunction()

void torch::autograd::registerCppFunction	(	const std::type_info &	type,
		PyTypeObject *	pytype
	)

Definition at line 240 of file python_cpp_function.cpp.

References cpp_function_types, and type.

Referenced by addClass(), and torch::autograd::generated::addClass().

registerFunctionHook()

PyObject * torch::autograd::registerFunctionHook	(	Node &	fn,
		PyObject *	hook
	)

Definition at line 246 of file python_cpp_function.cpp.

References caffe2.perfkernels.hp_emblookup_codegen::fn, THPPointer< T >::get(), handle, torch::res, and THPFunctionClass.

Referenced by THPCppFunction_register_hook(), and THPFunction_register_hook().

run_backward()

variable_list torch::autograd::run_backward	(	const variable_list &	outputs,
		const variable_list &	grad_outputs,
		bool	keep_graph,
		bool	create_graph,
		const variable_list &	inputs,
		bool	allow_unused,
		bool	accumulate_grad
	)

Definition at line 65 of file autograd.cpp.

References torch::autograd::Engine::execute(), torch::autograd::Edge::function, torch::autograd::Engine::get_default_engine(), torch::autograd::impl::gradient_edge(), caffe2::input, inputs, num_inputs, at::native::metal::mpscnn::output, at::native::output_nr(), outputs, TORCH_CHECK, and torch::autograd::impl::try_get_grad_accumulator().

Referenced by backward(), and grad().

sequenceToVariable()

static Variable torch::autograd::sequenceToVariable ( c10::DispatchKey  dispatch_key, PyObject *  seq  )

inlinestatic

Definition at line 86 of file python_variable_indexing.cpp.

References torch::utils::indexing_tensor_from_data(), c10::kLong, and c10::nullopt.

Referenced by applySlicing().

set_anomaly_mode_enabled()

static PyObject* torch::autograd::set_anomaly_mode_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 289 of file init.cpp.

References setup::arg, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and torch::autograd::AnomalyMode::set_enabled().

set_autocast_enabled()

static PyObject* torch::autograd::set_autocast_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 210 of file init.cpp.

References setup::arg, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and at::autocast::set_enabled().

set_default_engine_stub()

TORCH_API void torch::autograd::set_default_engine_stub

(

EngineStub

stub

)

Definition at line 994 of file engine.cpp.

References engine_stub().

Referenced by THPEngine_initModule().

set_device()

void torch::autograd::set_device

(

int

device

)

Definition at line 552 of file engine.cpp.

References c10::COMPILE_TIME_MAX_DEVICE_TYPES, CPU_DEVICE, device, c10::impl::device_guard_impl_registry, c10::lib::cpp17::detail_::has_addressof_impl::impl(), and worker_device.

Referenced by torch::distributed::autograd::DistEngine::execute_graph_task_until_ready_queue_empty(), torch::autograd::Engine::execute_with_graph_task(), torch::autograd::Engine::reentrant_thread_init(), and torch::autograd::Engine::thread_init().

set_forward_AD_enabled()

static PyObject* torch::autograd::set_forward_AD_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 249 of file init.cpp.

References setup::arg, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and setForwardADEnabled().

set_grad_enabled()

static PyObject* torch::autograd::set_grad_enabled ( PyObject *  _unused, PyObject *  arg  )

static

Definition at line 269 of file init.cpp.

References setup::arg, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and at::GradMode::set_enabled().

set_history() [1/3]

void torch::autograd::set_history ( at::Tensor &  variable, const std::shared_ptr< Node > &  grad_fn  )

inline

Definition at line 57 of file utils.h.

References AT_ASSERT, at::native::output_nr(), torch::autograd::impl::set_gradient_edge(), TORCH_INTERNAL_ASSERT, and variable().

Referenced by _wrap_outputs(), torch::distributed::autograd::addRecvRpcBackward(), torch::autograd::Scatter::apply(), torch::autograd::Gather::apply(), and set_history().

set_history() [2/3]

void torch::autograd::set_history ( std::vector< Variable > &&  variables, const std::shared_ptr< Node > &  grad_fn  )

inline

Definition at line 73 of file utils.h.

References set_history(), and variable().

set_history() [3/3]

void torch::autograd::set_history ( std::vector< Variable > &  variables, const std::shared_ptr< Node > &  grad_fn  )

inline

Definition at line 81 of file utils.h.

References set_history(), and variable().

setForwardADEnabled()

void TORCH_API torch::autograd::setForwardADEnabled

(

bool

value

)

Definition at line 86 of file forward_grad.cpp.

References value.

Referenced by set_forward_AD_enabled().

THPCppFunction_metadata()

PyObject * torch::autograd::THPCppFunction_metadata	(	THPCppFunction *	self,
		void *	_unused
	)

Definition at line 126 of file python_cpp_function.cpp.

References matmul_dlmc_bench::metadata.

THPCppFunction_name()

PyObject * torch::autograd::THPCppFunction_name	(	PyObject *	self,
		PyObject *	noargs
	)

Definition at line 157 of file python_cpp_function.cpp.

References caffe2.perfkernels.hp_emblookup_codegen::fn, and THPUtils_packString().

THPCppFunction_next_functions()

PyObject * torch::autograd::THPCppFunction_next_functions	(	THPCppFunction *	self,
		PyObject *	hook
	)

Definition at line 106 of file python_cpp_function.cpp.

References functionToPyObject(), THPPointer< T >::get(), THPPointer< T >::release(), and THPUtils_packUInt32().

THPCppFunction_register_hook()

PyObject * torch::autograd::THPCppFunction_register_hook	(	PyObject *	self,
		PyObject *	hook
	)

Definition at line 151 of file python_cpp_function.cpp.

References caffe2.perfkernels.hp_emblookup_codegen::fn, and registerFunctionHook().

THPCppFunction_register_hook_dict()

PyObject * torch::autograd::THPCppFunction_register_hook_dict	(	PyObject *	self,
		PyObject *	_var
	)

Definition at line 138 of file python_cpp_function.cpp.

References caffe2.perfkernels.hp_emblookup_codegen::fn, THPVariable_Check(), and caffe2::var.

THPCppFunction_requires_grad()

PyObject * torch::autograd::THPCppFunction_requires_grad	(	THPCppFunction *	self,
		void *	unused
	)

Definition at line 134 of file python_cpp_function.cpp.

THPVariable__is_view()

static PyObject* torch::autograd::THPVariable__is_view ( PyObject *  self, PyObject *  args  )

static

Definition at line 55 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and torch::handle_torch_function().

THPVariable__parse_to()

static PyObject* torch::autograd::THPVariable__parse_to ( PyObject *  module, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 27 of file python_nn_functions.cpp.

References compare-fastrnn-results::args, device, END_HANDLE_TH_ERRORS, torch::getTHPDtype(), HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::autograd::utils::parse_to_conversion(), configure::parser, r, THPDevice_New(), THPMemoryFormat_New(), THPNNVariableFunctionsModule, and torch::autograd::utils::wrap().

THPVariable__sparse_coo_tensor_unsafe()

static PyObject* torch::autograd::THPVariable__sparse_coo_tensor_unsafe ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 417 of file python_torch_functions.cpp.

References torch::utils::_sparse_coo_tensor_unsafe_ctor(), compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, torch::tensors::get_default_dispatch_key(), torch::tensors::get_default_scalar_type(), HANDLE_TH_ERRORS, THPVariable_Wrap(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_CONSTRUCTOR.

THPVariable_apply_()

static PyObject* torch::autograd::THPVariable_apply_ ( PyObject *  self, PyObject *  arg  )

static

Definition at line 72 of file python_variable_methods.cpp.

References torch::utils::apply_(), setup::arg, compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, handle, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch.jit._trace::make_tuple(), and THPVariable_Wrap().

THPVariable_arange()

static PyObject* torch::autograd::THPVariable_arange ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 86 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, torch::utils::check_out_type_matches(), c10::TensorOptions::device(), dispatch_arange(), c10::TensorOptions::dtype(), matmul_dlmc_bench::end, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::TensorOptions::layout(), caffe2.perfkernels.hp_emblookup_codegen::options, configure::parser, c10::TensorOptions::pinned_memory(), r, c10::TensorOptions::requires_grad(), at::Tensor::set_requires_grad(), torch.cuda.profiler::start(), step, THPVariableFunctionsModule, TORCH_CHECK, and torch::autograd::utils::wrap().

THPVariable_as_tensor()

static PyObject* torch::autograd::THPVariable_as_tensor ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 371 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, torch::utils::as_tensor(), END_HANDLE_TH_ERRORS, torch::tensors::get_default_dispatch_key(), torch::tensors::get_default_scalar_type(), HANDLE_TH_ERRORS, THPVariable_Wrap(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_CONSTRUCTOR.

THPVariable_bfloat16()

static PyObject* torch::autograd::THPVariable_bfloat16 ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 694 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::BFloat16, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_bool()

static PyObject* torch::autograd::THPVariable_bool ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 677 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::Bool, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_byte()

static PyObject* torch::autograd::THPVariable_byte ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 541 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_char()

static PyObject* torch::autograd::THPVariable_char ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 558 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_complex_scalar()

static PyObject* torch::autograd::THPVariable_complex_scalar ( PyObject *  self, PyObject *  args  )

static

Definition at line 344 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), dispatch_to_CComplexDouble(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::jit::tracer::warn(), torch::jit::tracer::WARN_PYTHON_DATAFLOW, and torch::autograd::utils::wrap().

THPVariable_contiguous()

static PyObject* torch::autograd::THPVariable_contiguous ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 235 of file python_variable_methods.cpp.

References torch::jit::tracer::addInputs(), torch::jit::tracer::addOutput(), compare-fastrnn-results::args, at::native::contiguous(), dispatch_contiguous(), END_HANDLE_TH_ERRORS, torch::jit::tracer::getTracingState(), HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::jit::tracer::isTracing(), c10::memory_format(), node, configure::parser, r, torch::jit::tracer::recordSourceLocation(), THPVariable_Wrap(), and THPVariableClass.

THPVariable_copy_()

static PyObject* torch::autograd::THPVariable_copy_ ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 278 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, dispatch_copy_(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_Wrap(), and THPVariableClass.

THPVariable_cpu()

static PyObject* torch::autograd::THPVariable_cpu ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 435 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::CPU, dispatch_to(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_Wrap(), and THPVariableClass.

THPVariable_cuda()

static PyObject* torch::autograd::THPVariable_cuda ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 489 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::CUDA, torch::utils::cuda_lazy_init(), device, torch.distributed.pipeline.sync._balance::Device, dispatch_to(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_Wrap(), THPVariableClass, and TORCH_CHECK.

THPVariable_data_ptr()

static PyObject* torch::autograd::THPVariable_data_ptr ( PyObject *  self_, PyObject *  args  )

static

Definition at line 182 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), data_ptr, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), and torch::autograd::utils::wrap().

THPVariable_dim()

static PyObject* torch::autograd::THPVariable_dim ( PyObject *  self, PyObject *  args  )

static

Definition at line 206 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), and THPUtils_packInt64().

THPVariable_double()

static PyObject* torch::autograd::THPVariable_double ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 575 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::Double, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_element_size()

static PyObject* torch::autograd::THPVariable_element_size ( PyObject *  self, PyObject *  args  )

static

Definition at line 711 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), and THPUtils_packInt64().

THPVariable_float()

static PyObject* torch::autograd::THPVariable_float ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 592 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, c10::Float, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_float_scalar()

static PyObject* torch::autograd::THPVariable_float_scalar ( PyObject *  self, PyObject *  args  )

static

Definition at line 333 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), dispatch_to_CDouble(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::jit::tracer::warn(), torch::jit::tracer::WARN_PYTHON_DATAFLOW, and torch::autograd::utils::wrap().

THPVariable_from_numpy()

static PyObject* torch::autograd::THPVariable_from_numpy ( PyObject *  module, PyObject *  arg  )

static

Definition at line 381 of file python_torch_functions.cpp.

References setup::arg, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::utils::tensor_from_numpy(), THPVariable_Wrap(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_CONSTRUCTOR.

THPVariable_full()

static PyObject* torch::autograd::THPVariable_full ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 219 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, torch::utils::check_out_type_matches(), c10::TensorOptions::device(), dispatch_full(), c10::TensorOptions::dtype(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::TensorOptions::layout(), microbenchmarks::names, c10::nullopt, caffe2.perfkernels.hp_emblookup_codegen::options, configure::parser, c10::TensorOptions::pinned_memory(), r, size, THPVariableFunctionsModule, TORCH_CHECK, and torch::autograd::utils::wrap().

THPVariable_get_device() [1/2]

static PyObject* torch::autograd::THPVariable_get_device ( PyObject *  self_, PyObject *  args  )

static

Definition at line 159 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, at::get_device(), HANDLE_TH_ERRORS, torch::handle_torch_function(), and torch::autograd::utils::wrap().

THPVariable_get_device() [2/2]

static PyObject* torch::autograd::THPVariable_get_device ( PyObject *  self_, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 435 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, configure::parser, r, and torch::autograd::utils::wrap().

THPVariable_getitem()

PyObject * torch::autograd::THPVariable_getitem	(	PyObject *	self,
		PyObject *	index
	)

Definition at line 270 of file python_variable_indexing.cpp.

References at::native::alias(), applySlicing(), torch::check_has_torch_function(), checkUnpackSlice(), count_specified_dimensions(), at::device_of(), at::indexing::dispatch_index(), at::indexing::Ellipsis, END_HANDLE_TH_ERRORS, THPPointer< T >::get(), at::indexing::get_item(), HANDLE_TH_ERRORS, torch::handle_torch_function_indexing(), index, caffe2::int64_t, torch.jit._trace::is_tracing(), torch::jit::tracer::isTracing(), at::indexing::None, recordSelectTrace(), recordSliceTrace(), torch.cuda.profiler::start(), step, torch.cuda.profiler::stop(), THPUtils_checkLong(), THPUtils_unpackLong(), THPVariable_Check(), THPVariable_CheckExact(), THPVariable_Unpack(), THPVariable_Wrap(), and wrapTuple().

THPVariable_half()

static PyObject* torch::autograd::THPVariable_half ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 609 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, c10::Half, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_has_names()

static PyObject* torch::autograd::THPVariable_has_names ( PyObject *  self_, PyObject *  args  )

static

Definition at line 170 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), at::impl::has_names(), and torch::autograd::utils::wrap().

THPVariable_index_scalar()

static PyObject* torch::autograd::THPVariable_index_scalar ( PyObject *  self, PyObject *  args  )

static

Definition at line 374 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), dispatch_to_CLong(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::isIntegralType(), and torch::autograd::utils::wrap().

THPVariable_int()

static PyObject* torch::autograd::THPVariable_int ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 626 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::Int, configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_integral_scalar()

static PyObject* torch::autograd::THPVariable_integral_scalar ( PyObject *  self, PyObject *  args  )

static

Definition at line 355 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), dispatch_to_CDouble(), dispatch_to_CLong(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::isFloatingType(), THPUtils_packDoubleAsInt(), torch::jit::tracer::warn(), torch::jit::tracer::WARN_PYTHON_DATAFLOW, and torch::autograd::utils::wrap().

THPVariable_invert()

static PyObject* torch::autograd::THPVariable_invert ( PyObject *  self, PyObject *  args  )

static

Definition at line 395 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), dispatch_invert(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::isIntegralType(), and THPVariable_Wrap().

THPVariable_is_contiguous()

static PyObject* torch::autograd::THPVariable_is_contiguous ( PyObject *  self_, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 769 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, dispatch_is_contiguous(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::memory_format(), configure::parser, r, and torch::autograd::utils::wrap().

THPVariable_item()

static PyObject* torch::autograd::THPVariable_item ( PyObject *  self, PyObject *  args  )

static

Definition at line 789 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::Bool, torch::check_has_torch_function(), dispatch_to_Bool(), dispatch_to_CComplexDouble(), dispatch_to_CDouble(), dispatch_to_CLong(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::jit::tracer::warn(), torch::jit::tracer::WARN_PYTHON_DATAFLOW, and torch::autograd::utils::wrap().

THPVariable_length()

Py_ssize_t torch::autograd::THPVariable_length

(

PyObject *

self

)

Definition at line 33 of file python_variable_indexing.cpp.

References torch::check_has_torch_function(), END_HANDLE_TH_ERRORS_RET, HANDLE_TH_ERRORS, torch::handle_torch_function(), and caffe2.contrib.playground.AnyExpOnTerm::ret.

THPVariable_long()

static PyObject* torch::autograd::THPVariable_long ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 643 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_map2_()

static PyObject* torch::autograd::THPVariable_map2_ ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 835 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::utils::map2_(), configure::parser, r, THPVariable_Wrap(), THPVariableClass, bench_ops::x, and at::native::metal::mpscnn::y.

THPVariable_map_()

static PyObject* torch::autograd::THPVariable_map_ ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 811 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::utils::map_(), at::meta::other, configure::parser, r, at::Tensor::requires_grad(), THPVariable_Wrap(), and THPVariableClass.

THPVariable_new()

static PyObject* torch::autograd::THPVariable_new ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 858 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), at::device_of(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::utils::legacy_tensor_new(), at::legacyExtractDispatchKey(), and THPVariable_Wrap().

THPVariable_new_ones()

static PyObject* torch::autograd::THPVariable_new_ones ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 870 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), at::device_of(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), at::legacyExtractDispatchKey(), torch::utils::new_ones(), and THPVariable_Wrap().

THPVariable_new_tensor()

static PyObject* torch::autograd::THPVariable_new_tensor ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 882 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), at::device_of(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), at::legacyExtractDispatchKey(), torch::utils::new_tensor(), and THPVariable_Wrap().

THPVariable_nonzero() [1/2]

static PyObject* torch::autograd::THPVariable_nonzero ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

THPVariable_nonzero() [2/2]

static PyObject* torch::autograd::THPVariable_nonzero ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 466 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, dispatch_nonzero(), dispatch_nonzero_numpy(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariableClass, and torch::autograd::utils::wrap().

THPVariable_numel() [1/2]

static PyObject* torch::autograd::THPVariable_numel ( PyObject *  self, PyObject *  args  )

static

Definition at line 218 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), and THPUtils_packInt64().

THPVariable_numel() [2/2]

static PyObject* torch::autograd::THPVariable_numel ( PyObject *  self_, PyObject *  args, PyObject *  kwargs  )

static

THPVariable_numpy()

static PyObject* torch::autograd::THPVariable_numpy ( PyObject *  self, PyObject *  arg  )

static

Definition at line 724 of file python_variable_methods.cpp.

References torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::utils::tensor_to_numpy(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_PYTHON_DATAFLOW.

THPVariable_pynew()

static PyObject* torch::autograd::THPVariable_pynew ( PyTypeObject *  type, PyObject *  args, PyObject *  kwds  )

static

Definition at line 15 of file python_legacy_variable.cpp.

References compare-fastrnn-results::args, c10::computeDeviceType(), data, c10::TensorOptions::device(), c10::dispatchKeyToBackend(), at::native::metal::empty(), END_HANDLE_TH_ERRORS, torch::tensors::get_default_dispatch_key(), torch::tensors::get_default_scalar_type(), torch::jit::tracer::getValueTrace(), HANDLE_TH_ERRORS, torch::jit::tracer::isTracing(), c10::TensorOptions::layout(), c10::layout_from_backend(), name, caffe2.perfkernels.hp_emblookup_codegen::options, r, fastrnns.scratch::requires_grad, detail::scalar_type(), torch::autograd::impl::set_name(), torch::jit::tracer::setValueTrace(), THPFunction_Check(), THPVariable_Check(), THPVariable_Wrap(), TORCH_CHECK, and caffe2::var.

THPVariable_randint()

static PyObject* torch::autograd::THPVariable_randint ( PyObject *  self_, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 310 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, torch::utils::check_out_type_matches(), c10::TensorOptions::device(), device, dispatch_randint(), c10::TensorOptions::dtype(), caffe2::dtype, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), c10::TensorOptions::layout(), caffe2.perfkernels.hp_emblookup_codegen::options, configure::parser, r, c10::TensorOptions::requires_grad(), at::Tensor::set_requires_grad(), size, THPVariableFunctionsModule, and torch::autograd::utils::wrap().

THPVariable_range()

static PyObject* torch::autograd::THPVariable_range ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 157 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, torch::utils::check_out_type_matches(), c10::TensorOptions::device(), dispatch_range(), c10::TensorOptions::dtype(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, c10::TensorOptions::layout(), caffe2.perfkernels.hp_emblookup_codegen::options, configure::parser, r, c10::TensorOptions::requires_grad(), caffe2.contrib.playground.AnyExpOnTerm::ret, at::Tensor::set_requires_grad(), and torch::autograd::utils::wrap().

THPVariable_requires_grad_()

static PyObject* torch::autograd::THPVariable_requires_grad_ ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 736 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, fastrnns.scratch::requires_grad, torch::autograd::utils::requires_grad_leaf_error(), THPVariable_Wrap(), THPVariableClass, and c10::typeMetaToScalarType().

THPVariable_setitem()

int torch::autograd::THPVariable_setitem	(	PyObject *	self,
		PyObject *	index,
		PyObject *	py_value
	)

Definition at line 347 of file python_variable_indexing.cpp.

References applySlicing(), torch::check_has_torch_function(), checkUnpackSlice(), at::indexing::copy_to(), count_specified_dimensions(), device, at::device_of(), at::indexing::dispatch_index_put_(), caffe2::dtype, at::indexing::Ellipsis, END_HANDLE_TH_ERRORS_RET, c10::ArrayRef< T >::equals(), THPPointer< T >::get(), HANDLE_TH_ERRORS, torch::handle_torch_function_indexing(), index, caffe2::int64_t, torch.jit._trace::is_tracing(), c10::isQIntType(), torch::jit::tracer::isTracing(), c10::kCPU, c10::kFloat, at::indexing::None, recordSelectTrace(), recordSliceTrace(), caffe2.contrib.playground.AnyExpOnTerm::ret, at::indexing::set_item(), at::indexing::slicePrefix1sSize(), torch.cuda.profiler::start(), step, torch.cuda.profiler::stop(), THPUtils_checkLong(), THPUtils_unpackLong(), THPVariable_Check(), THPVariable_CheckExact(), THPVariable_Unpack(), val, value, valueToTensor(), and wrapTuple().

THPVariable_short()

static PyObject* torch::autograd::THPVariable_short ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 660 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_to_type(), and THPVariableClass.

THPVariable_size()

static PyObject* torch::autograd::THPVariable_size ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 89 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, torch::jit::tracer::getSizeOf(), HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::jit::tracer::isTracing(), configure::parser, r, THPSize_New(), THPVariableClass, TORCH_INTERNAL_ASSERT, and torch::autograd::utils::wrap().

THPVariable_sparse_coo_tensor()

static PyObject* torch::autograd::THPVariable_sparse_coo_tensor ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 409 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, torch::tensors::get_default_dispatch_key(), torch::tensors::get_default_scalar_type(), HANDLE_TH_ERRORS, torch::utils::sparse_coo_tensor_ctor(), THPVariable_Wrap(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_CONSTRUCTOR.

THPVariable_storage()

static PyObject* torch::autograd::THPVariable_storage ( PyObject *  self, PyObject *  arg  )

static

Definition at line 894 of file python_variable_methods.cpp.

References torch::check_has_torch_function(), torch::createPyObject(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and torch::handle_torch_function().

THPVariable_storage_offset()

static PyObject* torch::autograd::THPVariable_storage_offset ( PyObject *  self_, PyObject *  args  )

static

Definition at line 194 of file python_variable_methods.cpp.

References torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), and torch::autograd::utils::wrap().

THPVariable_storage_type()

static PyObject* torch::autograd::THPVariable_storage_type ( PyObject *  self, PyObject *  arg  )

static

Definition at line 905 of file python_variable_methods.cpp.

References torch::check_has_torch_function(), torch::createPyObject(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), and caffe2::storage.

THPVariable_stride()

static PyObject* torch::autograd::THPVariable_stride ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 126 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, strides, THPUtils_packInt64Array(), THPVariableClass, and torch::autograd::utils::wrap().

THPVariable_tensor()

static PyObject* torch::autograd::THPVariable_tensor ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 427 of file python_torch_functions.cpp.

References compare-fastrnn-results::args, END_HANDLE_TH_ERRORS, torch::tensors::get_default_dispatch_key(), torch::tensors::get_default_scalar_type(), HANDLE_TH_ERRORS, torch::utils::tensor_ctor(), THPVariable_Wrap(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_CONSTRUCTOR.

THPVariable_to()

static PyObject* torch::autograd::THPVariable_to ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 919 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, c10::aten::copy(), torch::utils::cuda_lazy_init(), device, dispatch_to(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::autograd::utils::parse_to_conversion(), configure::parser, r, THPVariable_Wrap(), and THPVariableClass.

THPVariable_to_type()

static PyObject* torch::autograd::THPVariable_to_type ( PyObject *  self, ScalarType  scalarType, c10::optional< c10::MemoryFormat >  optional_memory_format  )

static

Definition at line 534 of file python_variable_methods.cpp.

References dispatch_to(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, and THPVariable_Wrap().

Referenced by THPVariable_bfloat16(), THPVariable_bool(), THPVariable_byte(), THPVariable_char(), THPVariable_double(), THPVariable_float(), THPVariable_half(), THPVariable_int(), THPVariable_long(), and THPVariable_short().

THPVariable_tolist()

static PyObject* torch::autograd::THPVariable_tolist ( PyObject *  self, PyObject *  args  )

static

Definition at line 961 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::check_has_torch_function(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), torch::utils::tensor_to_list(), torch::jit::tracer::warn(), and torch::jit::tracer::WARN_PYTHON_DATAFLOW.

THPVariable_type()

static PyObject* torch::autograd::THPVariable_type ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 973 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, torch::utils::cuda_lazy_init(), device, torch.distributed.pipeline.sync._balance::Device, caffe2.python.gradient_check_test::device_type, dispatch_to(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), caffe2.perfkernels.hp_emblookup_codegen::options, torch::utils::options_from_string(), torch::utils::options_to_string(), configure::parser, r, detail::scalar_type(), THPDtype_Check(), THPUtils_checkString(), THPUtils_packString(), THPUtils_unpackString(), THPVariable_Wrap(), THPVariableClass, and c10::typeMetaToScalarType().

THPVariable_xpu()

static PyObject* torch::autograd::THPVariable_xpu ( PyObject *  self, PyObject *  args, PyObject *  kwargs  )

static

Definition at line 512 of file python_variable_methods.cpp.

References compare-fastrnn-results::args, device, torch.distributed.pipeline.sync._balance::Device, dispatch_to(), END_HANDLE_TH_ERRORS, HANDLE_TH_ERRORS, torch::handle_torch_function(), configure::parser, r, THPVariable_Wrap(), THPVariableClass, TORCH_CHECK, and c10::XPU.

throw_error_for_complex_autograd() [1/2]

void torch::autograd::throw_error_for_complex_autograd ( const Tensor &  tensor, const char *  name  )

inline

Definition at line 80 of file VariableTypeUtils.h.

References name, at::Tensor::requires_grad(), torch::tensor(), and TORCH_CHECK.

Referenced by throw_error_for_complex_autograd().

throw_error_for_complex_autograd() [2/2]

void torch::autograd::throw_error_for_complex_autograd ( const TensorList &  tensorlist, const char *  name  )

inline

Definition at line 87 of file VariableTypeUtils.h.

References name, torch::tensor(), and throw_error_for_complex_autograd().

throw_error_out_requires_grad()

void torch::autograd::throw_error_out_requires_grad ( const char *  name )

inline

Definition at line 74 of file VariableTypeUtils.h.

References AT_ERROR, and name.

to_args_scalartypes()

std::vector<ScalarType> torch::autograd::to_args_scalartypes ( TensorList  tensors )

inline

Definition at line 312 of file VariableTypeUtils.h.

References caffe2::tensors.

to_args_sizes()

std::vector<std::vector<int64_t> > torch::autograd::to_args_sizes ( TensorList  tensors )

inline

Definition at line 304 of file VariableTypeUtils.h.

References caffe2::tensors.

to_output_type() [1/2]

template<typename T >

std::enable_if<std::is_same<T,variable_list>::value,T&>::type torch::autograd::to_output_type

(

variable_list &

output_list

)

Definition at line 197 of file custom_function.h.

to_output_type() [2/2]

template<typename T >

std::enable_if<std::is_same<T,Variable>::value,T>::type torch::autograd::to_output_type

(

variable_list &

output_list

)

Definition at line 200 of file custom_function.h.

treatSequenceAsTuple()

static bool torch::autograd::treatSequenceAsTuple ( PyObject *  index )

inlinestatic

Definition at line 211 of file python_variable_indexing.cpp.

References index, and THPVariable_Check().

Referenced by wrapTuple().

validate_outputs()

void torch::autograd::validate_outputs	(	const edge_list &	edges,
		variable_list &	grads,
		const std::function< std::string(const std::string &)> &	format_error
	)

Definition at line 572 of file engine.cpp.

References AT_ERROR, at::Tensor::defined(), at::Tensor::device(), at::Tensor::dim(), c10::ArrayRef< T >::equals(), grad(), is_compatible_type(), at::is_expandable_to(), c10::isComplexType(), c10::isFloatingType(), matmul_dlmc_bench::metadata, at::Tensor::options(), at::Tensor::scalar_type(), at::Tensor::sizes(), at::sum_to(), TORCH_CHECK, TORCH_INTERNAL_ASSERT, and c10::typeMetaToScalarType().

Referenced by call_function(), torch::autograd::Engine::execute(), and torch::distributed::autograd::DistEngine::validateRootsAndRetrieveEdges().

valueToTensor()

static Variable torch::autograd::valueToTensor ( c10::TensorOptions  options, PyObject *  value, const at::Device &  device  )

inlinestatic

Definition at line 90 of file python_variable_indexing.cpp.

References device, caffe2.perfkernels.hp_emblookup_codegen::options, torch::utils::options_to_string(), at::indexing::scalarToTensor(), THPUtils_checkLong(), THPUtils_unpackComplexDouble(), THPUtils_unpackDouble(), THPUtils_unpackLong(), THPVariable_Check(), and value.

Referenced by THPVariable_setitem().

variable()

def torch.autograd.variable	(	*	args,
		**	kwargs
	)

Definition at line 246 of file __init__.py.

References variable().

Referenced by _mark_dirty(), _save_variables(), torch::distributed::autograd::DistAutogradContext.accumulateGrad(), torch::autograd::AccumulateGrad.accumulateGrad(), torch::autograd::generated::details.any_variable_defined(), any_variable_requires_grad(), torch::autograd::AccumulateGrad.apply(), torch::autograd::Gather.apply(), torch::autograd::AccumulateGrad.callHooks(), torch::autograd::utils.clone_obey_contract(), c10d::Reducer.copy_bucket_to_grad(), create_gradient_edge(), c10d::Reducer.finalize_bucket_dense(), c10d::Reducer.initialize_buckets(), torch::jit.initPythonIRBindings(), c10::detail.make_filename(), c10d::Reducer.mark_variable_ready_dense(), c10d::Reducer.mark_variable_ready_sparse(), torch::jit.module_state_to(), torch::jit::tensorexpr::PolynomialTransformer.mutate(), torch::autograd::utils.obeys_layout_contract(), torch::autograd::detail::MakeNextFunctionList.operator()(), c10d::Reducer.Reducer(), torch::distributed::autograd::DistAutogradContext.runGradCallbackForVariable(), c10d::Reducer.runGradCallbackForVariable(), torch::autograd::SavedVariable.SavedVariable(), set_history(), THPEngine_run_backward(), unpack_input(), variable(), and wrap_outputs().

wrap_outputs()

TORCH_API variable_list torch::autograd::wrap_outputs	(	const variable_list &	inputs,
		tensor_list &&	outputs,
		const function_constructor &	ctr
	)

Wraps the tensor outputs in variables and creates the grad_fn and sets the grad_fn if necessary.

Definition at line 12 of file utils.cpp.

References any_variable_requires_grad(), collect_next_edges(), create_gradient_edge(), inputs, at::GradMode::is_enabled(), at::native::metal::mpscnn::output, outputs, and variable().

Referenced by torch::autograd::DelayedError::apply(), torch::autograd::UndefinedGrad::apply(), and torch::autograd::PyNode::legacy_apply().

wrapTuple()

static THPObjectPtr torch::autograd::wrapTuple ( PyObject *  index )

inlinestatic

Definition at line 251 of file python_variable_indexing.cpp.

References index, torch::res, and treatSequenceAsTuple().

Referenced by THPVariable_getitem(), and THPVariable_setitem().

Variable Documentation

$

torch::autograd::$

Initial value:

{py_forwards}
 
static PyMethodDef fft_functions[] = {
  ${py_method_defs}
  {NULL}
}

Definition at line 41 of file python_fft_functions.cpp.

Referenced by torch::autograd::generated::initialize_autogenerated_functions().

__all__

list torch.autograd.__all__ = ['Variable', 'Function', 'backward', 'grad_mode']

private

Definition at line 24 of file __init__.py.

_OptionalTensor

torch.autograd._OptionalTensor = Optional[torch.Tensor]

private

Definition at line 26 of file __init__.py.

checkpoint_valid

thread_local bool torch::autograd::checkpoint_valid = true

static

Definition at line 70 of file engine.cpp.

Referenced by call_function(), and torch::autograd::Engine::is_checkpoint_valid().

cpp_function_types

std::unordered_map<std::type_index, THPObjectPtr> torch::autograd::cpp_function_types

static

Definition at line 191 of file python_cpp_function.cpp.

Referenced by functionToPyObject(), and registerCppFunction().

CPU_DEVICE

constexpr int torch::autograd::CPU_DEVICE = -1

staticconstexpr

Definition at line 32 of file engine.h.

Referenced by torch::distributed::autograd::DistEngine::execute_graph_task_until_ready_queue_empty(), torch::autograd::Engine::execute_with_graph_task(), torch::autograd::Engine::ready_queue_by_index(), and set_device().

current_depth

thread_local int torch::autograd::current_depth = 0

static

Definition at line 73 of file engine.cpp.

Referenced by torch::autograd::Engine::execute_with_graph_task().

current_evaluating_node

thread_local std::shared_ptr<Node> torch::autograd::current_evaluating_node = nullptr

static

Definition at line 21 of file function.cpp.

Referenced by torch::autograd::Node::assign_parent(), torch::autograd::NodeGuard::NodeGuard(), and torch::autograd::NodeGuard::~NodeGuard().

current_graph_task

thread_local std::shared_ptr<GraphTask> torch::autograd::current_graph_task = nullptr

static

Definition at line 82 of file engine.cpp.

Referenced by torch::autograd::GraphTaskGuard::GraphTaskGuard(), torch::autograd::Engine::queue_callback(), and torch::autograd::GraphTaskGuard::restore_current_graph_task().

default_methods

struct PyMethodDef torch::autograd::default_methods[]

static

Initial value:

= {
  THP_FUNCTION_DEFAULT_METHODS,
  {nullptr}
}

Definition at line 162 of file python_cpp_function.cpp.

Referenced by _initFunctionPyTypeObject().

default_properties

struct PyGetSetDef torch::autograd::default_properties[]

static

Initial value:

= {
  THP_FUNCTION_DEFAULT_PROPERTIES,
  {nullptr}
}

Definition at line 167 of file python_cpp_function.cpp.

Referenced by _initFunctionPyTypeObject().

ERR_BACKWARD_TWICE

TORCH_API const char * torch::autograd::ERR_BACKWARD_TWICE

Initial value:

=
    "Trying to backward through the graph a second time, but the saved intermediate "
    "results have already been freed. Specify retain_graph=True when calling "
    ".backward() or autograd.grad() the first time."

Definition at line 122 of file saved_variable.cpp.

Referenced by torch::autograd::CopySlices::apply(), torch::autograd::AutogradContext::get_saved_variables(), torch::autograd::SavedVariable::unpack(), and unpack_saved_variables().

local_ready_queue

thread_local std::shared_ptr<ReadyQueue> torch::autograd::local_ready_queue = nullptr

static

Definition at line 98 of file engine.cpp.

Referenced by torch::autograd::Engine::execute(), torch::autograd::Engine::init_local_ready_queue(), torch::autograd::Engine::reentrant_thread_init(), and torch::autograd::Engine::thread_main().

MAX_DEPTH

constexpr int torch::autograd::MAX_DEPTH = 60

staticconstexpr

Definition at line 40 of file engine.h.

methods

PyMethodDef torch::autograd::methods[]

static

Initial value:

= { 
  {"_set_grad_enabled", set_grad_enabled, METH_O, nullptr},
  {"is_grad_enabled", is_grad_enabled, METH_NOARGS, nullptr},
  {"_set_forward_AD_enabled", set_forward_AD_enabled, METH_O, nullptr},
  {"_is_forward_AD_enabled", is_forward_AD_enabled, METH_NOARGS, nullptr},
  {"set_autocast_enabled", set_autocast_enabled, METH_O, nullptr},
  {"is_autocast_enabled", is_autocast_enabled, METH_NOARGS, nullptr},
  {"clear_autocast_cache", clear_autocast_cache, METH_NOARGS, nullptr},
  {"autocast_increment_nesting", autocast_increment_nesting, METH_NOARGS, nullptr},
  {"autocast_decrement_nesting", autocast_decrement_nesting, METH_NOARGS, nullptr},
  {"set_anomaly_enabled", set_anomaly_mode_enabled, METH_O, nullptr},
  {"is_anomaly_enabled", is_anomaly_mode_enabled, METH_NOARGS, nullptr},
  {"_enter_dual_level", python_enter_dual_level, METH_NOARGS, nullptr},
  {"_exit_dual_level", castPyCFunctionWithKeywords(python_exit_dual_level), METH_VARARGS | METH_KEYWORDS, nullptr},
  {nullptr, nullptr, 0, nullptr}
}

Definition at line 332 of file init.cpp.

Referenced by python_functions().

NO_DEVICE

constexpr int torch::autograd::NO_DEVICE = -2

staticconstexpr

Definition at line 31 of file engine.h.

Referenced by torch::autograd::Engine::execute(), and torch::autograd::Engine::execute_with_graph_task().

THPFFTVariableFunctionsModule

PyObject* torch::autograd::THPFFTVariableFunctionsModule = NULL

static

Definition at line 48 of file python_fft_functions.cpp.

Referenced by initFFTFunctions().

THPLegacyVariableType

PyTypeObject torch::autograd::THPLegacyVariableType

Definition at line 91 of file python_legacy_variable.cpp.

Referenced by init_legacy_variable().

THPLinalgVariableFunctionsModule

PyObject* torch::autograd::THPLinalgVariableFunctionsModule = NULL

static

Definition at line 34 of file python_linalg_functions.cpp.

Referenced by initLinalgFunctions().

THPNNVariableFunctionsModule

PyObject* torch::autograd::THPNNVariableFunctionsModule = NULL

static

Definition at line 25 of file python_nn_functions.cpp.

Referenced by initNNFunctions(), and THPVariable__parse_to().

THPVariableFunctions

PyTypeObject torch::autograd::THPVariableFunctions

static

Definition at line 498 of file python_torch_functions.cpp.

Referenced by initTorchFunctions().

THPVariableFunctionsModule

PyObject* torch::autograd::THPVariableFunctionsModule = NULL

static

Definition at line 62 of file python_torch_functions.cpp.

Referenced by initTorchFunctions(), THPVariable_arange(), THPVariable_full(), and THPVariable_randint().

total_depth

thread_local int torch::autograd::total_depth = 0

static

Definition at line 78 of file engine.cpp.

Referenced by torch::autograd::Engine::execute(), torch::autograd::Engine::execute_with_graph_task(), and torch::autograd::Engine::reentrant_thread_init().

variable_methods

PyMethodDef torch::autograd::variable_methods[]

extern

Referenced by THPVariable_initModule().

variableHooks

at::impl::VariableHooksRegisterer registerVariableHooks & torch::autograd::variableHooks

Definition at line 340 of file variable.cpp.

worker_device

thread_local int torch::autograd::worker_device = NO_DEVICE

static

Definition at line 65 of file engine.cpp.

Referenced by torch::autograd::Engine::execute(), torch::autograd::Engine::execute_with_graph_task(), set_device(), and torch::autograd::Engine::thread_main().