Package | Description |
---|---|
org.bytedeco.pytorch | |
org.bytedeco.pytorch.global |
Modifier and Type | Method and Description |
---|---|
LongOptional |
LongOptionalArrayRef.at(long Index)
Vector compatibility
|
LongOptional |
LongOptionalVector.back() |
LongOptional |
LongOptionalArrayRef.back()
back - Get the last element.
|
LongOptional |
LongOptionalArrayRef.begin()
\}
\name Simple Operations
\{
|
LongOptional |
LongOptionalArrayRef.cbegin() |
LongOptional |
LongOptionalArrayRef.cend() |
LongOptional |
SymNodeImpl.constant_int() |
LongOptional |
LongOptionalArrayRef.data() |
LongOptional |
AvgPool1dOptions.divisor_override() |
LongOptional |
AvgPool3dOptions.divisor_override() |
LongOptional |
AvgPool2dOptions.divisor_override() |
LongOptional |
LongOptionalArrayRef.end() |
LongOptional |
LongOptionalVector.front() |
LongOptional |
LongOptionalArrayRef.front()
front - Get the first element.
|
LongOptional[] |
LongOptionalVector.get() |
LongOptional |
LongOptionalVector.Iterator.get() |
LongOptional |
LongOptionalVector.get(long i) |
LongOptional |
LongVaryingShape.get(long i) |
LongOptional |
LongOptionalArrayRef.get(long Index)
\}
\name Operator Overloads
\{
|
LongOptional |
LBFGSOptions.max_eval() |
LongOptional |
SymInt.maybe_as_int() |
LongOptional |
SymNodeImpl.maybe_as_int() |
LongOptional |
NestedTensorImpl.opt_size(long d) |
LongOptional |
AdaptiveMaxPool3dOptions.output_size() |
LongOptional |
AdaptiveAvgPool3dOptions.output_size() |
LongOptional |
AdaptiveMaxPool2dOptions.output_size() |
LongOptional |
AdaptiveAvgPool2dOptions.output_size() |
LongOptional |
EmbeddingFuncOptions.padding_idx() |
LongOptional |
EmbeddingOptions.padding_idx() |
LongOptional |
EmbeddingFromPretrainedOptions.padding_idx() |
LongOptional |
EmbeddingBagFromPretrainedOptions.padding_idx() |
LongOptional |
EmbeddingBagFuncOptions.padding_idx() |
LongOptional |
EmbeddingBagOptions.padding_idx() |
LongOptional |
LongOptionalVector.pop_back() |
LongOptional |
LongOptional.put(long value) |
LongOptional |
LongOptional.put(LongOptional x) |
LongOptional |
SymNodeImpl.singleton_int() |
LongOptional |
RangeValue.staticLen() |
LongOptional |
SugaredValue.staticLen() |
LongOptional |
SugaredTupleValue.staticLen() |
Modifier and Type | Method and Description |
---|---|
Tensor |
Tensor._to_sparse_bsc(long[] blocksize,
LongOptional dense_dim) |
Tensor |
Tensor._to_sparse_bsc(LongArrayRef blocksize,
LongOptional dense_dim) |
Tensor |
Tensor._to_sparse_bsr(long[] blocksize,
LongOptional dense_dim) |
Tensor |
Tensor._to_sparse_bsr(LongArrayRef blocksize,
LongOptional dense_dim) |
Tensor |
Tensor._to_sparse_csc(LongOptional dense_dim) |
Tensor |
Tensor._to_sparse_csr(LongOptional dense_dim) |
Tensor |
Tensor._to_sparse(LayoutOptional layout,
long[] blocksize,
LongOptional dense_dim) |
Tensor |
Tensor._to_sparse(LayoutOptional layout,
LongArrayRefOptional blocksize,
LongOptional dense_dim) |
T_TensorTensor_T |
Tensor.aminmax(LongOptional dim,
boolean keepdim) |
Tensor |
Tensor.argmax(LongOptional dim,
boolean keepdim) |
Tensor |
Tensor.argmin(LongOptional dim,
boolean keepdim) |
Tensor |
Tensor.as_strided_(long[] size,
long[] stride,
LongOptional storage_offset) |
Tensor |
Tensor.as_strided_(LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
Tensor |
Tensor.as_strided_scatter(Tensor src,
long[] size,
long[] stride,
LongOptional storage_offset) |
Tensor |
Tensor.as_strided_scatter(Tensor src,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
Tensor |
Tensor.as_strided(long[] size,
long[] stride,
LongOptional storage_offset) |
Tensor |
Tensor.as_strided(LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
Tensor |
Tensor.count_nonzero(LongOptional dim) |
Tensor |
Tensor.cross(Tensor other,
LongOptional dim) |
LongOptionalVector.Iterator |
LongOptionalVector.insert(LongOptionalVector.Iterator pos,
LongOptional value) |
Tensor |
Tensor.istft(long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean center,
boolean normalized,
BoolOptional onesided,
LongOptional length,
boolean return_complex) |
Tensor |
Tensor.nanquantile(double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
Tensor |
Tensor.nanquantile(double q,
LongOptional dim,
boolean keepdim,
String interpolation) |
Tensor |
Tensor.nanquantile(Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
Tensor |
Tensor.nanquantile(Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation) |
LongOptionalVector |
LongOptionalVector.push_back(LongOptional value) |
LongOptionalVector |
LongOptionalVector.put(long i,
LongOptional value) |
LongOptionalVector |
LongOptionalVector.put(LongOptional... array) |
LongOptional |
LongOptional.put(LongOptional x) |
LongOptionalVector |
LongOptionalVector.put(LongOptional value) |
Tensor |
Tensor.quantile(double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
Tensor |
Tensor.quantile(double q,
LongOptional dim,
boolean keepdim,
String interpolation) |
Tensor |
Tensor.quantile(Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
Tensor |
Tensor.quantile(Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation) |
Tensor |
Tensor.random_(long from,
LongOptional to) |
Tensor |
Tensor.random_(long from,
LongOptional to,
GeneratorOptional generator) |
Tensor |
Tensor.repeat_interleave_symint(SymInt repeats,
LongOptional dim,
LongOptional output_size) |
Tensor |
Tensor.repeat_interleave(long repeats,
LongOptional dim,
LongOptional output_size) |
Tensor |
Tensor.repeat_interleave(Tensor repeats,
LongOptional dim,
LongOptional output_size) |
void |
TensorImpl.set_sizes_and_strides(long[] new_size,
long[] new_stride,
LongOptional storage_offset) |
void |
TensorImpl.set_sizes_and_strides(LongArrayRef new_size,
LongArrayRef new_stride,
LongOptional storage_offset)
Set the sizes and strides of a tensor.
|
Tensor |
Tensor.slice_scatter(Tensor src,
long dim,
LongOptional start,
LongOptional end,
long step) |
Tensor |
Tensor.slice(long dim,
LongOptional start,
LongOptional end,
long step) |
Tensor |
Tensor.stft(long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean normalized,
BoolOptional onesided,
BoolOptional return_complex) |
Tensor |
Tensor.stft(long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean center,
BytePointer pad_mode,
boolean normalized,
BoolOptional onesided,
BoolOptional return_complex) |
Tensor |
Tensor.stft(long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean center,
String pad_mode,
boolean normalized,
BoolOptional onesided,
BoolOptional return_complex) |
TensorMaker |
TensorMaker.storage_offset(LongOptional value) |
Tensor |
Tensor.take_along_dim(Tensor indices,
LongOptional dim) |
Tensor |
Tensor.to_sparse_bsc(long[] blocksize,
LongOptional dense_dim) |
Tensor |
Tensor.to_sparse_bsc(LongArrayRef blocksize,
LongOptional dense_dim) |
Tensor |
Tensor.to_sparse_bsr(long[] blocksize,
LongOptional dense_dim) |
Tensor |
Tensor.to_sparse_bsr(LongArrayRef blocksize,
LongOptional dense_dim) |
Tensor |
Tensor.to_sparse_csc(LongOptional dense_dim) |
Tensor |
Tensor.to_sparse_csr(LongOptional dense_dim) |
Tensor |
Tensor.to_sparse(LayoutOptional layout,
long[] blocksize,
LongOptional dense_dim) |
Tensor |
Tensor.to_sparse(LayoutOptional layout,
LongArrayRefOptional blocksize,
LongOptional dense_dim) |
Modifier and Type | Method and Description |
---|---|
static LongOptional |
torch._check_param_device(Tensor param,
LongOptional old_param_device) |
Modifier and Type | Method and Description |
---|---|
static LongOptional |
torch._check_param_device(Tensor param,
LongOptional old_param_device) |
static Tensor |
torch.adaptive_avg_pool2d(Tensor input,
LongOptional output_size) |
static Tensor |
torch.adaptive_avg_pool3d(Tensor input,
LongOptional output_size) |
static T_TensorTensor_T |
torch.adaptive_max_pool2d_with_indices(Tensor input,
LongOptional output_size) |
static Tensor |
torch.adaptive_max_pool2d(Tensor input,
LongOptional output_size) |
static T_TensorTensor_T |
torch.adaptive_max_pool3d_with_indices(Tensor input,
LongOptional output_size) |
static Tensor |
torch.adaptive_max_pool3d(Tensor input,
LongOptional output_size) |
static T_TensorTensor_T |
torch.aminmax_out(Tensor min,
Tensor max,
Tensor self,
LongOptional dim,
boolean keepdim) |
static T_TensorTensor_T |
torch.aminmax_outf(Tensor self,
LongOptional dim,
boolean keepdim,
Tensor min,
Tensor max) |
static T_TensorTensor_T |
torch.aminmax(Tensor self,
LongOptional dim,
boolean keepdim) |
static Tensor |
torch.argmax_out(Tensor out,
Tensor self,
LongOptional dim,
boolean keepdim) |
static Tensor |
torch.argmax_outf(Tensor self,
LongOptional dim,
boolean keepdim,
Tensor out) |
static Tensor |
torch.argmax(Tensor self,
LongOptional dim,
boolean keepdim) |
static Tensor |
torch.argmin_out(Tensor out,
Tensor self,
LongOptional dim,
boolean keepdim) |
static Tensor |
torch.argmin_outf(Tensor self,
LongOptional dim,
boolean keepdim,
Tensor out) |
static Tensor |
torch.argmin(Tensor self,
LongOptional dim,
boolean keepdim) |
static Tensor |
torch.as_strided_(Tensor self,
long[] size,
long[] stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_(Tensor self,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_copy_out(Tensor out,
Tensor self,
long[] size,
long[] stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_copy_out(Tensor out,
Tensor self,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_copy_outf(Tensor self,
long[] size,
long[] stride,
LongOptional storage_offset,
Tensor out) |
static Tensor |
torch.as_strided_copy_outf(Tensor self,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset,
Tensor out) |
static Tensor |
torch.as_strided_copy(Tensor self,
long[] size,
long[] stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_copy(Tensor self,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_scatter_out(Tensor out,
Tensor self,
Tensor src,
long[] size,
long[] stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_scatter_out(Tensor out,
Tensor self,
Tensor src,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_scatter_outf(Tensor self,
Tensor src,
long[] size,
long[] stride,
LongOptional storage_offset,
Tensor out) |
static Tensor |
torch.as_strided_scatter_outf(Tensor self,
Tensor src,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset,
Tensor out) |
static Tensor |
torch.as_strided_scatter(Tensor self,
Tensor src,
long[] size,
long[] stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided_scatter(Tensor self,
Tensor src,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided(Tensor self,
long[] size,
long[] stride,
LongOptional storage_offset) |
static Tensor |
torch.as_strided(Tensor self,
LongArrayRef size,
LongArrayRef stride,
LongOptional storage_offset) |
static Tensor |
torch.avg_pool2d_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d_backward_outf(Tensor grad_output,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor grad_input) |
static Tensor |
torch.avg_pool2d_backward_outf(Tensor grad_output,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor grad_input) |
static Tensor |
torch.avg_pool2d_backward(Tensor grad_output,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d_backward(Tensor grad_output,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d_out(Tensor out,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d_out(Tensor out,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d_outf(Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor out) |
static Tensor |
torch.avg_pool2d_outf(Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor out) |
static Tensor |
torch.avg_pool2d(Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d(Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool2d(Tensor input,
LongPointer kernel_size,
LongPointer stride,
LongPointer padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_backward_outf(Tensor grad_output,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor grad_input) |
static Tensor |
torch.avg_pool3d_backward_outf(Tensor grad_output,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor grad_input) |
static Tensor |
torch.avg_pool3d_backward(Tensor grad_output,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_backward(Tensor grad_output,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_out(Tensor out,
Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_out(Tensor out,
Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d_outf(Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor out) |
static Tensor |
torch.avg_pool3d_outf(Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override,
Tensor out) |
static Tensor |
torch.avg_pool3d(Tensor self,
long[] kernel_size,
long[] stride,
long[] padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d(Tensor self,
LongArrayRef kernel_size,
LongArrayRef stride,
LongArrayRef padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.avg_pool3d(Tensor input,
LongPointer kernel_size,
LongPointer stride,
LongPointer padding,
boolean ceil_mode,
boolean count_include_pad,
LongOptional divisor_override) |
static Tensor |
torch.cdist(Tensor x1,
Tensor x2,
double p,
LongOptional compute_mode) |
static Tensor |
torch.count_nonzero_out(Tensor out,
Tensor self,
LongOptional dim) |
static Tensor |
torch.count_nonzero_outf(Tensor self,
LongOptional dim,
Tensor out) |
static Tensor |
torch.count_nonzero(Tensor self,
LongOptional dim) |
static Tensor |
torch.cross_out(Tensor out,
Tensor self,
Tensor other,
LongOptional dim) |
static Tensor |
torch.cross_outf(Tensor self,
Tensor other,
LongOptional dim,
Tensor out) |
static Tensor |
torch.cross(Tensor self,
Tensor other,
LongOptional dim) |
static T_TensorTensorTensorTensor_T |
torch.embedding_bag(Tensor weight,
Tensor indices,
Tensor offsets,
boolean scale_grad_by_freq,
long mode,
boolean sparse,
TensorOptional per_sample_weights,
boolean include_last_offset,
LongOptional padding_idx) |
static Tensor |
torch.embedding_bag(Tensor input,
Tensor weight,
Tensor offsets,
DoubleOptional max_norm,
double norm_type,
boolean scale_grad_by_freq,
EmbeddingBagMode mode,
boolean sparse,
Tensor per_sample_weights,
boolean include_last_offset,
LongOptional padding_idx) |
static Tensor |
torch.embedding(Tensor input,
Tensor weight,
LongOptional padding_idx,
DoubleOptional max_norm,
double norm_type,
boolean scale_grad_by_freq,
boolean sparse) |
static Tensor |
torch.fft_fft_out(Tensor out,
Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_fft_outf(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm,
Tensor out) |
static Tensor |
torch.fft_fft(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_hfft_out(Tensor out,
Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_hfft_outf(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm,
Tensor out) |
static Tensor |
torch.fft_hfft(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_ifft_out(Tensor out,
Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_ifft_outf(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm,
Tensor out) |
static Tensor |
torch.fft_ifft(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_ihfft_out(Tensor out,
Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_ihfft_outf(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm,
Tensor out) |
static Tensor |
torch.fft_ihfft(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_irfft_out(Tensor out,
Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_irfft_outf(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm,
Tensor out) |
static Tensor |
torch.fft_irfft(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_rfft_out(Tensor out,
Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.fft_rfft_outf(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm,
Tensor out) |
static Tensor |
torch.fft_rfft(Tensor self,
LongOptional n,
long dim,
StringViewOptional norm) |
static Tensor |
torch.from_file_out(Tensor out,
BytePointer filename,
BoolOptional shared,
LongOptional size) |
static Tensor |
torch.from_file_out(Tensor out,
String filename,
BoolOptional shared,
LongOptional size) |
static Tensor |
torch.from_file_outf(BytePointer filename,
BoolOptional shared,
LongOptional size,
Tensor out) |
static Tensor |
torch.from_file_outf(String filename,
BoolOptional shared,
LongOptional size,
Tensor out) |
static Tensor |
torch.from_file(BytePointer filename,
BoolOptional shared,
LongOptional size,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.from_file(BytePointer filename,
BoolOptional shared,
LongOptional size,
TensorOptions options) |
static Tensor |
torch.from_file(String filename,
BoolOptional shared,
LongOptional size,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.from_file(String filename,
BoolOptional shared,
LongOptional size,
TensorOptions options) |
static TensorVector |
torch.gradient(Tensor self,
ScalarArrayRef spacing,
LongOptional dim,
long edge_order) |
static TensorVector |
torch.gradient(Tensor self,
ScalarOptional spacing,
LongOptional dim,
long edge_order) |
static TensorVector |
torch.gradient(Tensor self,
TensorArrayRef spacing,
LongOptional dim,
long edge_order) |
static TensorVector |
torch.gradient(Tensor self,
TensorVector spacing,
LongOptional dim,
long edge_order) |
static Tensor |
torch.istft(Tensor self,
long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean center,
boolean normalized,
BoolOptional onesided,
LongOptional length,
boolean return_complex) |
static Tensor |
torch.linalg_vander(Tensor x,
LongOptional N) |
static Tensor |
torch.nanquantile_out(Tensor out,
Tensor self,
double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.nanquantile_out(Tensor out,
Tensor self,
double q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.nanquantile_out(Tensor out,
Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.nanquantile_out(Tensor out,
Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.nanquantile_outf(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation,
Tensor out) |
static Tensor |
torch.nanquantile_outf(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
String interpolation,
Tensor out) |
static Tensor |
torch.nanquantile_outf(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation,
Tensor out) |
static Tensor |
torch.nanquantile_outf(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation,
Tensor out) |
static Tensor |
torch.nanquantile(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.nanquantile(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.nanquantile(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.nanquantile(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static T_TensorTensor_T |
torch.pad_packed_sequence(PackedSequence sequence,
boolean batch_first,
double padding_value,
LongOptional total_length)
Pads a packed batch of variable length sequences.
|
static Tensor |
torch.quantile_out(Tensor out,
Tensor self,
double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.quantile_out(Tensor out,
Tensor self,
double q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.quantile_out(Tensor out,
Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.quantile_out(Tensor out,
Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.quantile_outf(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation,
Tensor out) |
static Tensor |
torch.quantile_outf(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
String interpolation,
Tensor out) |
static Tensor |
torch.quantile_outf(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation,
Tensor out) |
static Tensor |
torch.quantile_outf(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation,
Tensor out) |
static Tensor |
torch.quantile(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.quantile(Tensor self,
double q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.quantile(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
BytePointer interpolation) |
static Tensor |
torch.quantile(Tensor self,
Tensor q,
LongOptional dim,
boolean keepdim,
String interpolation) |
static Tensor |
torch.random_out(Tensor out,
Tensor self,
long from,
LongOptional to) |
static Tensor |
torch.random_out(Tensor out,
Tensor self,
long from,
LongOptional to,
GeneratorOptional generator) |
static Tensor |
torch.random_outf(Tensor self,
long from,
LongOptional to,
GeneratorOptional generator,
Tensor out) |
static Tensor |
torch.random(Tensor self,
long from,
LongOptional to) |
static Tensor |
torch.random(Tensor self,
long from,
LongOptional to,
GeneratorOptional generator) |
static Tensor |
torch.repeat_interleave_out(Tensor out,
Tensor repeats,
LongOptional output_size) |
static Tensor |
torch.repeat_interleave_outf(Tensor repeats,
LongOptional output_size,
Tensor out) |
static Tensor |
torch.repeat_interleave_symint(Tensor self,
SymInt repeats,
LongOptional dim,
LongOptional output_size) |
static Tensor |
torch.repeat_interleave(Tensor self,
long repeats,
LongOptional dim,
LongOptional output_size) |
static Tensor |
torch.repeat_interleave(Tensor repeats,
LongOptional output_size) |
static Tensor |
torch.repeat_interleave(Tensor self,
Tensor repeats,
LongOptional dim,
LongOptional output_size) |
static Tensor |
torch.slice_copy_out(Tensor out,
Tensor self,
long dim,
LongOptional start,
LongOptional end,
long step) |
static Tensor |
torch.slice_copy_outf(Tensor self,
long dim,
LongOptional start,
LongOptional end,
long step,
Tensor out) |
static Tensor |
torch.slice_copy(Tensor self,
long dim,
LongOptional start,
LongOptional end,
long step) |
static Tensor |
torch.slice_scatter_out(Tensor out,
Tensor self,
Tensor src,
long dim,
LongOptional start,
LongOptional end,
long step) |
static Tensor |
torch.slice_scatter_outf(Tensor self,
Tensor src,
long dim,
LongOptional start,
LongOptional end,
long step,
Tensor out) |
static Tensor |
torch.slice_scatter(Tensor self,
Tensor src,
long dim,
LongOptional start,
LongOptional end,
long step) |
static Tensor |
torch.slice(Tensor self,
long dim,
LongOptional start,
LongOptional end,
long step) |
static Tensor |
torch.stft(Tensor self,
long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean normalized,
BoolOptional onesided,
BoolOptional return_complex) |
static Tensor |
torch.stft(Tensor self,
long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean center,
BytePointer pad_mode,
boolean normalized,
BoolOptional onesided,
BoolOptional return_complex) |
static Tensor |
torch.stft(Tensor self,
long n_fft,
LongOptional hop_length,
LongOptional win_length,
TensorOptional window,
boolean center,
String pad_mode,
boolean normalized,
BoolOptional onesided,
BoolOptional return_complex) |
static void |
torch.sym_constrain_range_for_size(Scalar size,
LongOptional min,
LongOptional max) |
static void |
torch.sym_constrain_range(Scalar size,
LongOptional min,
LongOptional max) |
static Tensor |
torch.take_along_dim_out(Tensor out,
Tensor self,
Tensor indices,
LongOptional dim) |
static Tensor |
torch.take_along_dim_outf(Tensor self,
Tensor indices,
LongOptional dim,
Tensor out) |
static Tensor |
torch.take_along_dim(Tensor self,
Tensor indices,
LongOptional dim) |
static Tensor |
torch.torch_from_file(BytePointer filename,
BoolOptional shared,
LongOptional size,
TensorOptions options) |
static Tensor |
torch.torch_from_file(String filename,
BoolOptional shared,
LongOptional size,
TensorOptions options) |
static T_TensorTensorTensor_T |
torch.unique_consecutive_out(Tensor out0,
Tensor out1,
Tensor out2,
Tensor self,
boolean return_inverse,
boolean return_counts,
LongOptional dim) |
static T_TensorTensorTensor_T |
torch.unique_consecutive_outf(Tensor self,
boolean return_inverse,
boolean return_counts,
LongOptional dim,
Tensor out0,
Tensor out1,
Tensor out2) |
static T_TensorTensorTensor_T |
torch.unique_consecutive(Tensor self,
boolean return_inverse,
boolean return_counts,
LongOptional dim) |
static Tensor |
torch.vander(Tensor x,
LongOptional N,
boolean increasing) |
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