Uses of Class
org.bytedeco.pytorch.TensorBase

Packages that use TensorBase

Package	Description
org.bytedeco.pytorch
org.bytedeco.pytorch.global

Uses of TensorBase in org.bytedeco.pytorch

Subclasses of TensorBase in org.bytedeco.pytorch

Modifier and Type	Class and Description
class	Tensor

Methods in org.bytedeco.pytorch that return TensorBase

Modifier and Type	Method and Description
TensorBase	TensorBase._base() Returns the Variable that this Variable is a view of.
TensorBase	TensorBaseMaybeOwned.access()
TensorBase	VariableHooksInterface.base(TensorBase arg0)
TensorBase	TensorTensorRefHook.call(TensorBase a)
TensorBase	TensorTensorHook.call(TensorBase a)
TensorBase	TensorBase.contiguous()
TensorBase	TensorBase.contiguous(byte memory_format)
TensorBase	TensorBase.contiguous(torch.MemoryFormat memory_format)
TensorBase	TensorBase.data()
TensorBase	VariableHooksInterface.data(TensorBase arg0)
TensorBase	TensorBase.fill_(Scalar scalar) Should be used if *this can reasonably be expected to be contiguous and performance is important.
TensorBase	TensorBase.getPointer(long i)
TensorBase	TensorIteratorBase.input_base()
TensorBase	TensorIteratorBase.input_base(long arg)
TensorBase	TensorBaseMaybeOwned.multiply()
TensorBase	OperandInfo.original_tensor_base()
TensorBase	TensorIteratorBase.output_base()
TensorBase	TensorIteratorBase.output_base(long arg)
TensorBase	TensorBase.position(long position)
TensorBase	TensorBase.put(TensorBase x)
TensorBase	TensorBase.requires_grad_()
TensorBase	TensorBase.requires_grad_(boolean _requires_grad)
TensorBase	TensorBase.set_requires_grad(boolean requires_grad) \fn bool is_leaf() const; All Tensors that have requires_grad() which is false will be leaf Tensors by convention.
TensorBase	OperandInfo.tensor_base()
TensorBase	TensorIteratorBase.tensor_base(long arg)
TensorBase	TensorBase.tensor_data() NOTE: This is similar to the legacy .data() function on Variable, and is intended to be used from functions that need to access the Variable's equivalent Tensor (i.e.
TensorBase	VariableHooksInterface.tensor_data(TensorBase arg0)
TensorBase	TensorBase.to()
TensorBase	TensorBase.to(TensorOptions options, boolean non_blocking, boolean copy, MemoryFormatOptional memory_format)
TensorBase	TensorBase.variable_data() NOTE: var.variable_data() in C++ has the same semantics as tensor.data in Python, which create a new Variable that shares the same storage and tensor metadata with the original Variable, but with a completely new autograd history.
TensorBase	VariableHooksInterface.variable_data(TensorBase arg0)
static TensorBase	TensorBase.wrap_tensor_impl(TensorImpl tensor_impl)
TensorBase	TensorBase.zero_()

Methods in org.bytedeco.pytorch with parameters of type TensorBase

Modifier and Type	Method and Description
Tensor	TensorImpl._fw_grad(long level, TensorBase self) Return the accumulated gradient of a tensor.
void	TensorImpl._set_fw_grad(TensorBase new_grad, TensorBase self, long level, boolean is_inplace_op) Sets the forward gradient for this Tensor.
long	VariableHooksInterface._version(TensorBase arg0)
TensorIteratorConfig	TensorIteratorConfig.add_borrowed_const_input(TensorBase input)
TensorIteratorConfig	TensorIteratorConfig.add_borrowed_input(TensorBase input)
TensorIteratorConfig	TensorIteratorConfig.add_borrowed_output(TensorBase output)
TensorIteratorConfig	TensorIteratorConfig.add_const_input(TensorBase input)
TensorIteratorConfig	TensorIteratorConfig.add_input(TensorBase input)
TensorIteratorConfig	TensorIteratorConfig.add_output(TensorBase output) Construction
TensorIteratorConfig	TensorIteratorConfig.add_owned_const_input(TensorBase input)
TensorIteratorConfig	TensorIteratorConfig.add_owned_input(TensorBase input)
TensorIteratorConfig	TensorIteratorConfig.add_owned_output(TensorBase output)
TensorBase	VariableHooksInterface.base(TensorBase arg0)
static TensorIterator	TensorIterator.binary_float_op(TensorBase out, TensorBase a, TensorBase b)
static TensorIterator	TensorIterator.binary_op(TensorBase out, TensorBase a, TensorBase b)
static TensorBaseMaybeOwned	TensorBaseMaybeOwned.borrowed(TensorBase t)
static TensorIterator	TensorIterator.borrowing_binary_op(TensorBase out, TensorBase a, TensorBase b)
static TensorIterator	TensorIterator.borrowing_nullary_op(TensorBase out)
void	TensorIteratorBase.build_binary_float_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_binary_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_borrowing_binary_float_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_borrowing_binary_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_borrowing_comparison_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_borrowing_except_last_argument_comparison_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_borrowing_unary_float_op(TensorBase out, TensorBase a)
void	TensorIteratorBase.build_borrowing_unary_force_boolean_op(TensorBase out, TensorBase a)
void	TensorIteratorBase.build_borrowing_unary_op(TensorBase out, TensorBase a)
void	TensorIteratorBase.build_comparison_op(TensorBase out, TensorBase a, TensorBase b)
void	TensorIteratorBase.build_output_borrowing_argument_owning_unary_op(TensorBase out, TensorBase a)
void	TensorIteratorBase.build_ternary_op(TensorBase out, TensorBase a, TensorBase b, TensorBase c)
void	TensorIteratorBase.build_unary_float_op(TensorBase out, TensorBase a)
void	TensorIteratorBase.build_unary_op(TensorBase out, TensorBase a)
void	VoidTensorHook.call(TensorBase a)
TensorBase	TensorTensorRefHook.call(TensorBase a)
TensorBase	TensorTensorHook.call(TensorBase a)
static TensorIterator	TensorIterator.comparison_op(TensorBase out, TensorBase a, TensorBase b)
TensorBase	VariableHooksInterface.data(TensorBase arg0)
Tensor	AutogradMetaInterface.fw_grad(long level, TensorBase self)
Node	VariableHooksInterface.grad_fn(TensorBase arg0)
boolean	TensorBase.is_alias_of(TensorBase other)
boolean	VariableHooksInterface.is_leaf(TensorBase arg0)
boolean	TensorBase.is_same(TensorBase other)
boolean	VariableHooksInterface.is_view(TensorBase arg0)
BytePointer	VariableHooksInterface.name(TensorBase arg0)
static TensorIterator	TensorIterator.nullary_op(TensorBase out)
long	VariableHooksInterface.output_nr(TensorBase arg0)
static TensorBaseMaybeOwned	TensorBaseMaybeOwned.owned(TensorBase t)
TensorBase	TensorBase.put(TensorBase x)
Tensor	Tensor.put(TensorBase x)
static TensorIterator	TensorIterator.reduce_op(TensorBase out, TensorBase a)
static TensorIterator	TensorIterator.reduce_op(TensorBase out1, TensorBase out2, TensorBase a)
void	VariableHooksInterface.remove_hook(TensorBase arg0, int pos)
void	VariableHooksInterface.requires_grad_(TensorBase arg0, boolean arg1)
void	VariableHooksInterface.retain_grad(TensorBase arg0)
boolean	VariableHooksInterface.retains_grad(TensorBase arg0)
void	TensorBase.set_data(TensorBase new_data)
void	VariableHooksInterface.set_data(TensorBase arg0, TensorBase arg1)
void	AutogradMetaInterface.set_fw_grad(TensorBase new_grad, TensorBase self, long level, boolean is_inplace_op)
TensorBase	VariableHooksInterface.tensor_data(TensorBase arg0)
static TensorIterator	TensorIterator.unary_float_op(TensorBase out, TensorBase a)
static TensorIterator	TensorIterator.unary_op(TensorBase out, TensorBase a)
TensorBase	VariableHooksInterface.variable_data(TensorBase arg0)

Constructors in org.bytedeco.pytorch with parameters of type TensorBase

Constructor and Description
IValue(TensorBase t)
Tensor(TensorBase base)
TensorBase(TensorBase arg0)
TensorGeometry(TensorBase t)

Uses of TensorBase in org.bytedeco.pytorch.global

Methods in org.bytedeco.pytorch.global that return TensorBase

Modifier and Type	Method and Description
static TensorBase	torch.empty_cpu(long[] size, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_cpu(long[] size, TensorOptions options)
static TensorBase	torch.empty_cpu(long[] size, torch.ScalarType dtype)
static TensorBase	torch.empty_cpu(long[] size, torch.ScalarType dtype, boolean pin_memory, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_cpu(LongArrayRef size, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_cpu(LongArrayRef size, TensorOptions options)
static TensorBase	torch.empty_cpu(LongArrayRef size, torch.ScalarType dtype)
static TensorBase	torch.empty_cpu(LongArrayRef size, torch.ScalarType dtype, boolean pin_memory, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_generic_symint(SymIntArrayRef size, Allocator allocator, DispatchKeySet ks, torch.ScalarType scalar_type, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_generic(long[] size, Allocator allocator, DispatchKeySet ks, torch.ScalarType scalar_type, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_generic(LongArrayRef size, Allocator allocator, DispatchKeySet ks, torch.ScalarType scalar_type, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_meta(long[] size, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_meta(long[] size, TensorOptions options)
static TensorBase	torch.empty_meta(long[] size, torch.ScalarType dtype)
static TensorBase	torch.empty_meta(long[] size, torch.ScalarType dtype, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_meta(LongArrayRef size, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_meta(LongArrayRef size, TensorOptions options)
static TensorBase	torch.empty_meta(LongArrayRef size, torch.ScalarType dtype)
static TensorBase	torch.empty_meta(LongArrayRef size, torch.ScalarType dtype, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.empty_strided_cpu(long[] size, long[] stride, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt)
static TensorBase	torch.empty_strided_cpu(long[] size, long[] stride, TensorOptions options)
static TensorBase	torch.empty_strided_cpu(long[] size, long[] stride, torch.ScalarType dtype)
static TensorBase	torch.empty_strided_cpu(long[] size, long[] stride, torch.ScalarType dtype, boolean pin_memory)
static TensorBase	torch.empty_strided_cpu(LongArrayRef size, LongArrayRef stride, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt)
static TensorBase	torch.empty_strided_cpu(LongArrayRef size, LongArrayRef stride, TensorOptions options)
static TensorBase	torch.empty_strided_cpu(LongArrayRef size, LongArrayRef stride, torch.ScalarType dtype)
static TensorBase	torch.empty_strided_cpu(LongArrayRef size, LongArrayRef stride, torch.ScalarType dtype, boolean pin_memory)
static TensorBase	torch.empty_strided_generic(long[] size, long[] stride, Allocator allocator, DispatchKeySet ks, torch.ScalarType scalar_type)
static TensorBase	torch.empty_strided_generic(LongArrayRef size, LongArrayRef stride, Allocator allocator, DispatchKeySet ks, torch.ScalarType scalar_type)
static TensorBase	torch.empty_strided_meta(long[] size, long[] stride, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt)
static TensorBase	torch.empty_strided_meta(long[] size, long[] stride, TensorOptions options)
static TensorBase	torch.empty_strided_meta(long[] size, long[] stride, torch.ScalarType dtype)
static TensorBase	torch.empty_strided_meta(LongArrayRef size, LongArrayRef stride, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt)
static TensorBase	torch.empty_strided_meta(LongArrayRef size, LongArrayRef stride, TensorOptions options)
static TensorBase	torch.empty_strided_meta(LongArrayRef size, LongArrayRef stride, torch.ScalarType dtype)
static TensorBase	torch.empty_strided_symint_generic(SymIntArrayRef size, SymIntArrayRef stride, Allocator allocator, DispatchKeySet ks, torch.ScalarType scalar_type)
static TensorBase	torch.empty_strided_symint_meta(SymIntArrayRef size, SymIntArrayRef stride, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt)
static TensorBase	torch.empty_strided_symint_meta(SymIntArrayRef size, SymIntArrayRef stride, TensorOptions options)
static TensorBase	torch.empty_strided_symint_meta(SymIntArrayRef size, SymIntArrayRef stride, torch.ScalarType dtype)
static TensorBase	torch.empty_symint_meta(SymIntArrayRef size, ScalarTypeOptional dtype_opt, LayoutOptional layout_opt, DeviceOptional device_opt, BoolOptional pin_memory_opt, MemoryFormatOptional memory_format_opt)
static TensorBase	torch.get_tensor_base(Tensor t)
static TensorBase	torch.internal_set_names_inplace(TensorBase tensor, DimnameListOptional names)
static TensorBase	torch.internal_set_names_inplace(TensorBase tensor, DimnameVector names, boolean validate_names)

Methods in org.bytedeco.pytorch.global with parameters of type TensorBase

Modifier and Type	Method and Description
static void	torch.assert_no_internal_overlap(TensorBase t)
static void	torch.assert_no_overlap(TensorBase a, TensorBase b)
static void	torch.assert_no_partial_overlap(TensorBase a, TensorBase b)
static void	torch.check_variable_result(TensorBase original, TensorBase result, BytePointer hook_name)
static void	torch.check_variable_result(TensorBase original, TensorBase result, String hook_name)
static torch.MemOverlapStatus	torch.get_overlap_status(TensorBase a, TensorBase b)
static torch.MemOverlap	torch.has_internal_overlap(TensorBase t)
static TensorBase	torch.internal_set_names_inplace(TensorBase tensor, DimnameListOptional names)
static TensorBase	torch.internal_set_names_inplace(TensorBase tensor, DimnameVector names, boolean validate_names)
static torch.DispatchKey	torch.legacyExtractDispatchKey(TensorBase t)
static void	torch.propagate_names_if_nonempty(TensorBase result, DimnameArrayRef names)
static void	torch.propagate_names_if_nonempty(TensorBase result, DimnameArrayRef names, boolean validate_names)
static void	torch.propagate_names_if_nonempty(TensorBase result, DimnameVector names)
static void	torch.propagate_names_if_nonempty(TensorBase result, DimnameVector names, boolean validate_names)
static void	torch.propagate_names(TensorBase result, DimnameArrayRef names)
static void	torch.propagate_names(TensorBase result, DimnameArrayRef names, boolean validate_names)
static void	torch.propagate_names(TensorBase result, DimnameVector names)
static void	torch.propagate_names(TensorBase result, DimnameVector names, boolean validate_names)
static void	torch.propagate_names(TensorBase result, TensorBase src)
static void	torch.share_memory_(TensorBase t) In place change the storage to shm based.