Package | Description |
---|---|
org.bytedeco.pytorch | |
org.bytedeco.pytorch.functions | |
org.bytedeco.pytorch.global |
Modifier and Type | Class and Description |
---|---|
class |
Tensor |
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 |
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(int arg) |
TensorBase |
TensorBaseMaybeOwned.multiply() |
TensorBase |
OperandInfo.original_tensor_base() |
TensorBase |
TensorIteratorBase.output_base() |
TensorBase |
TensorIteratorBase.output_base(int 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(int 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(TensorImplPtr tensor_impl) |
TensorBase |
TensorBase.zero_() |
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_input(TensorBase input) |
TensorIteratorConfig |
TensorIteratorConfig.add_borrowed_output(TensorBase output) |
TensorIteratorConfig |
TensorIteratorConfig.add_input(TensorBase input) |
TensorIteratorConfig |
TensorIteratorConfig.add_output(TensorBase output)
Construction
|
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) |
static TensorIterator |
TensorIterator.comparison_op(TensorBase out,
TensorBase a,
TensorBase b) |
TensorBase |
VariableHooksInterface.data(TensorBase arg0) |
Tensor |
AutogradMeta.fw_grad(long level,
TensorBase self) |
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) |
Tensor |
Tensor.put(TensorBase x) |
TensorBase |
TensorBase.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 |
AutogradMeta.set_fw_grad(TensorBase new_grad,
TensorBase self,
long level,
boolean is_inplace_op) |
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) |
Constructor and Description |
---|
IValue(TensorBase t) |
Tensor(TensorBase base) |
TensorBase(TensorBase arg0) |
TensorGeometry(TensorBase t) |
Modifier and Type | Method and Description |
---|---|
TensorBase |
TensorTensorRefHook.call(TensorBase a) |
TensorBase |
TensorTensorHook.call(TensorBase a) |
Modifier and Type | Method and Description |
---|---|
TensorBase |
TensorTensorRefHook.call(TensorBase a) |
void |
VoidTensorHook.call(TensorBase a) |
TensorBase |
TensorTensorHook.call(TensorBase a) |
Modifier and Type | Method and Description |
---|---|
static void |
torch.add_hook(TensorBase arg0,
FunctionPreHook hook) |
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)
Return the next edges of all the given variables, or tuples of variables.
|
static void |
torch.check_variable_result(TensorBase original,
TensorBase result,
String hook_name) |
static void |
torch.clear_hooks(TensorBase arg0) |
static void |
torch.create_cpp_hook(TensorBase arg0) |
static void |
torch.create_cpp_hook(TensorBase arg0,
boolean is_retains_grad_hooks) |
static AutogradMeta |
torch.get_autograd_meta(TensorBase arg0)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Variable
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A
Variable augments a Tensor with the ability to interact in our
autograd machinery. |
static torch.MemOverlapStatus |
torch.get_overlap_status(TensorBase a,
TensorBase b) |
static DifferentiableViewMeta |
torch.get_view_autograd_meta(TensorBase arg0) |
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 AutogradMeta |
torch.materialize_autograd_meta(TensorBase arg0) |
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.set_post_acc_grad_hooks(TensorBase arg0,
PostAccumulateGradHook dict) |
static void |
torch.share_memory_(TensorBase t)
In place change the storage to shm based.
|
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