/usr/local/lib64/python3.6/site-packages/torch/include/ATen/
/usr/local/lib64/python3.6/site-packages/torch/include/ATen
NameSizeModeActions
core/-0755rm
cpu/-0755rm
cuda/-0755rm
cudnn/-0755rm
detail/-0755rm
hip/-0755rm
native/-0755rm
quantized/-0755rm
AccumulateType.h44380644editdlrm
ArrayRef.h440644editdlrm
ATen.h9980644editdlrm
autocast_mode.h67160644editdlrm
Backend.h430644editdlrm
Backtrace.h460644editdlrm
BatchedFallback.h9650644editdlrm
BatchedTensorImpl.h53830644editdlrm
CompositeExplicitAutogradFunctions.h16220644editdlrm
CompositeExplicitAutogradFunctions_inl.h540750644editdlrm
CompositeImplicitAutogradFunctions.h16220644editdlrm
CompositeImplicitAutogradFunctions_inl.h1420820644editdlrm
Config.h7340644editdlrm
Context.h127670644editdlrm
cpp_custom_type_hack.h53260644editdlrm
CPUApplyUtils.h125820644editdlrm
CPUFixedAllocator.h8300644editdlrm
CPUFunctions.h16000644editdlrm
CPUFunctions_inl.h1719240644editdlrm
CPUGeneratorImpl.h14310644editdlrm
CUDAFunctions.h16010644editdlrm
CUDAFunctions_inl.h1856960644editdlrm
CUDAGeneratorImpl.h46950644editdlrm
Device.h420644editdlrm
DeviceGuard.h11340644editdlrm
Dimname.h310644editdlrm
DimVector.h460644editdlrm
Dispatch.h521370644editdlrm
div_rtn.h2040644editdlrm
DLConvertor.h5760644editdlrm
dlpack.h52440644editdlrm
DynamicLibrary.h3690644editdlrm
ExpandUtils.h145060644editdlrm
Formatting.h340644editdlrm
Functions.h8463260644editdlrm
Generator.h460644editdlrm
InferSize.h21430644editdlrm
InitialTensorOptions.h4450644editdlrm
Layout.h420644editdlrm
MapAllocator.h29990644editdlrm
MatrixRef.h30160644editdlrm
MemoryOverlap.h11170644editdlrm
MetaFunctions.h16010644editdlrm
MetaFunctions_inl.h840060644editdlrm
NamedTensor.h350644editdlrm
NamedTensorUtils.h57470644editdlrm
NativeFunctions.h3546510644editdlrm
NativeMetaFunctions.h354450644editdlrm
NumericUtils.h27870644editdlrm
OpaqueTensorImpl.h60800644editdlrm
Operators.h17071990644editdlrm
OpMathType.h4600644editdlrm
Parallel.h48750644editdlrm
ParallelNative.h24430644editdlrm
ParallelNativeTBB.h29340644editdlrm
ParallelOpenMP.h30490644editdlrm
PTThreadPool.h3940644editdlrm
record_function.h240440644editdlrm
RedispatchFunctions.h11128860644editdlrm
RegistrationDeclarations.h5457770644editdlrm
SavedTensorHooks.h3280644editdlrm
Scalar.h440644editdlrm
ScalarOps.h22720644editdlrm
ScalarType.h1290644editdlrm
SequenceNumber.h3730644editdlrm
SmallVector.h470644editdlrm
SparseCsrTensorImpl.h20450644editdlrm
SparseCsrTensorUtils.h5230644editdlrm
SparseTensorImpl.h124170644editdlrm
SparseTensorUtils.h42190644editdlrm
Storage.h430644editdlrm
Tensor.h480644editdlrm
TensorAccessor.h510644editdlrm
TensorGeometry.h18550644editdlrm
TensorIndexing.h219230644editdlrm
TensorIterator.h299620644editdlrm
TensorIteratorInternal.h18620644editdlrm
TensorMeta.h29170644editdlrm
TensorNames.h25190644editdlrm
TensorOperators.h32750644editdlrm
TensorOptions.h490644editdlrm
TensorUtils.h56870644editdlrm
ThreadLocalState.h32890644editdlrm
TracerMode.h55760644editdlrm
TypeDefault.h6800644editdlrm
Utils.h59930644editdlrm
Version.h3400644editdlrm
VmapMode.h9520644editdlrm
VmapTransforms.h76540644editdlrm
WrapDimUtils.h34380644editdlrm
WrapDimUtilsMulti.h7680644editdlrm
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/ATen/CUDAFunctions_inl.h (185696B)
// @generated by tools/codegen/gen.py from DispatchKeyFunctions_inl.h // NB: The implementing C++ file is RegisterDispatchKey.cpp // The only #includes we need are for custom classes that have defaults in the C++ API #include #include #include namespace at { namespace cuda { TORCH_API void _assert_async(const at::Tensor & self); TORCH_API bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank); TORCH_API ::std::tuple _cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity); TORCH_API at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional); TORCH_API ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional & weight_buf, const at::Tensor & hx, const c10::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state); TORCH_API ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, at::TensorOptions options); TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API ::std::tuple _fused_dropout(const at::Tensor & self, double p, c10::optional generator=c10::nullopt); TORCH_API at::Tensor _masked_scale(const at::Tensor & self, const at::Tensor & mask, double scale); TORCH_API at::Tensor & abs_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & abs_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor angle(const at::Tensor & self); TORCH_API at::Tensor & angle_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & angle_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor view_as_real(const at::Tensor & self); TORCH_API at::Tensor view_as_complex(const at::Tensor & self); TORCH_API at::Tensor sgn(const at::Tensor & self); TORCH_API at::Tensor & sgn_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sgn_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sgn_(at::Tensor & self); TORCH_API at::Tensor & conj_physical_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & conj_physical_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor acos(const at::Tensor & self); TORCH_API at::Tensor & acos_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & acos_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & acos_(at::Tensor & self); TORCH_API at::Tensor add(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor & add_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor & add_outf(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor & add_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor addmv(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addmv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addmv_outf(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor & addmv_(at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addr_outf(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor all(const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API at::Tensor & all_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); TORCH_API at::Tensor any(const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API at::Tensor & any_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out); TORCH_API at::Tensor & arange_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1); TORCH_API at::Tensor & arange_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); TORCH_API at::Tensor argmax(const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false); TORCH_API at::Tensor & argmax_out(at::Tensor & out, const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false); TORCH_API at::Tensor & argmax_outf(const at::Tensor & self, c10::optional dim, bool keepdim, at::Tensor & out); TORCH_API at::Tensor argmin(const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false); TORCH_API at::Tensor & argmin_out(at::Tensor & out, const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false); TORCH_API at::Tensor & argmin_outf(const at::Tensor & self, c10::optional dim, bool keepdim, at::Tensor & out); TORCH_API at::Tensor acosh(const at::Tensor & self); TORCH_API at::Tensor & acosh_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & acosh_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & acosh_(at::Tensor & self); TORCH_API at::Tensor asinh(const at::Tensor & self); TORCH_API at::Tensor & asinh_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & asinh_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & asinh_(at::Tensor & self); TORCH_API at::Tensor atanh(const at::Tensor & self); TORCH_API at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & atanh_(at::Tensor & self); TORCH_API at::Tensor as_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, c10::optional storage_offset=c10::nullopt); TORCH_API at::Tensor asin(const at::Tensor & self); TORCH_API at::Tensor & asin_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & asin_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & asin_(at::Tensor & self); TORCH_API at::Tensor atan(const at::Tensor & self); TORCH_API at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & atan_(at::Tensor & self); TORCH_API at::Tensor baddbmm(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & baddbmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & baddbmm_outf(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor & baddbmm_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & bernoulli_out(at::Tensor & out, const at::Tensor & self, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & bernoulli_outf(const at::Tensor & self, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor & bernoulli_(at::Tensor & self, const at::Tensor & p, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & bernoulli_(at::Tensor & self, double p=0.5, c10::optional generator=c10::nullopt); TORCH_API at::Tensor binary_cross_entropy(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & binary_cross_entropy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & binary_cross_entropy_outf(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, at::Tensor & out); TORCH_API at::Tensor binary_cross_entropy_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & binary_cross_entropy_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & binary_cross_entropy_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, at::Tensor & grad_input); TORCH_API at::Tensor bincount(const at::Tensor & self, const c10::optional & weights={}, int64_t minlength=0); TORCH_API at::Tensor bitwise_not(const at::Tensor & self); TORCH_API at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & bitwise_not_(at::Tensor & self); TORCH_API at::Tensor copysign(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & copysign_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & copysign_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logical_not_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & logical_not_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & logical_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logical_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & logical_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logical_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor bmm(const at::Tensor & self, const at::Tensor & mat2); TORCH_API at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); TORCH_API at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); TORCH_API at::Tensor ceil(const at::Tensor & self); TORCH_API at::Tensor & ceil_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & ceil_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & ceil_(at::Tensor & self); TORCH_API at::Tensor clamp(const at::Tensor & self, const c10::optional & min, const c10::optional & max=c10::nullopt); TORCH_API at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const c10::optional & min, const c10::optional & max=c10::nullopt); TORCH_API at::Tensor & clamp_outf(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out); TORCH_API at::Tensor & clamp_(at::Tensor & self, const c10::optional & min, const c10::optional & max=c10::nullopt); TORCH_API at::Tensor clamp(const at::Tensor & self, const c10::optional & min={}, const c10::optional & max={}); TORCH_API at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const c10::optional & min={}, const c10::optional & max={}); TORCH_API at::Tensor & clamp_outf(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out); TORCH_API at::Tensor & clamp_max_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & max); TORCH_API at::Tensor & clamp_max_outf(const at::Tensor & self, const at::Scalar & max, at::Tensor & out); TORCH_API at::Tensor & clamp_max_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & max); TORCH_API at::Tensor & clamp_max_outf(const at::Tensor & self, const at::Tensor & max, at::Tensor & out); TORCH_API at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min); TORCH_API at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Scalar & min, at::Tensor & out); TORCH_API at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & min); TORCH_API at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Tensor & min, at::Tensor & out); TORCH_API at::Tensor & complex_out(at::Tensor & out, const at::Tensor & real, const at::Tensor & imag); TORCH_API at::Tensor & complex_outf(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out); TORCH_API at::Tensor & polar_out(at::Tensor & out, const at::Tensor & abs, const at::Tensor & angle); TORCH_API at::Tensor & polar_outf(const at::Tensor & abs, const at::Tensor & angle, at::Tensor & out); TORCH_API at::Tensor cos(const at::Tensor & self); TORCH_API at::Tensor & cos_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & cos_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & cos_(at::Tensor & self); TORCH_API at::Tensor cosh(const at::Tensor & self); TORCH_API at::Tensor & cosh_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & cosh_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & cosh_(at::Tensor & self); TORCH_API at::Tensor count_nonzero(const at::Tensor & self, at::IntArrayRef dim); TORCH_API at::Tensor cudnn_affine_grid_generator(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W); TORCH_API at::Tensor cudnn_affine_grid_generator_backward(const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W); TORCH_API ::std::tuple cudnn_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); TORCH_API ::std::tuple cudnn_batch_norm_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_var, double epsilon, const at::Tensor & reserveSpace); TORCH_API at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); TORCH_API at::Tensor cudnn_convolution_backward_input(at::IntArrayRef self_size, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); TORCH_API ::std::tuple cudnn_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, ::std::array output_mask); TORCH_API at::Tensor cudnn_convolution_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); TORCH_API at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); TORCH_API ::std::tuple cudnn_convolution_transpose_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, ::std::array output_mask); TORCH_API at::Tensor cudnn_convolution_transpose_backward_input(const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); TORCH_API at::Tensor cudnn_convolution_transpose_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); TORCH_API at::Tensor cudnn_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); TORCH_API at::Tensor cudnn_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const c10::optional & alpha, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups); TORCH_API at::Tensor cudnn_grid_sampler(const at::Tensor & self, const at::Tensor & grid); TORCH_API ::std::tuple cudnn_grid_sampler_backward(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output); TORCH_API void _cummax_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); TORCH_API void _cummin_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim); TORCH_API at::Tensor cumprod(const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & cumprod_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & cumprod_outf(const at::Tensor & self, int64_t dim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor & cumprod_(at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor cumsum(const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & cumsum_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & cumsum_outf(const at::Tensor & self, int64_t dim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor & cumsum_(at::Tensor & self, int64_t dim, c10::optional dtype=c10::nullopt); TORCH_API ::std::tuple _ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false); TORCH_API at::Tensor _ctc_loss_backward(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false); TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor div(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); TORCH_API at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); TORCH_API at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, at::Tensor & out); TORCH_API at::Tensor & div_(at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode); TORCH_API at::Tensor dot(const at::Tensor & self, const at::Tensor & tensor); TORCH_API at::Tensor vdot(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor embedding_dense_backward(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq); TORCH_API at::Tensor & embedding_renorm_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type); TORCH_API ::std::tuple _embedding_bag_forward_only(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); TORCH_API ::std::tuple _embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1); TORCH_API at::Tensor _embedding_bag_dense_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional & per_sample_weights, int64_t padding_idx=-1); TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1); TORCH_API at::Tensor empty(at::IntArrayRef size, at::TensorOptions options={}, c10::optional memory_format=c10::nullopt); TORCH_API at::Tensor empty(at::IntArrayRef size, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory, c10::optional memory_format); TORCH_API const at::Tensor & resize_(const at::Tensor & self, at::IntArrayRef size, c10::optional memory_format=c10::nullopt); TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={}); TORCH_API at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor erf(const at::Tensor & self); TORCH_API at::Tensor & erf_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & erf_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & erf_(at::Tensor & self); TORCH_API at::Tensor erfc(const at::Tensor & self); TORCH_API at::Tensor & erfc_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & erfc_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & erfc_(at::Tensor & self); TORCH_API at::Tensor exp(const at::Tensor & self); TORCH_API at::Tensor & exp_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & exp_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & exp_(at::Tensor & self); TORCH_API at::Tensor exp2(const at::Tensor & self); TORCH_API at::Tensor & exp2_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & exp2_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & exp2_(at::Tensor & self); TORCH_API at::Tensor expm1(const at::Tensor & self); TORCH_API at::Tensor & expm1_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & expm1_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & expm1_(at::Tensor & self); TORCH_API at::Tensor & eye_out(at::Tensor & out, int64_t n); TORCH_API at::Tensor & eye_outf(int64_t n, at::Tensor & out); TORCH_API at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m); TORCH_API at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out); TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Scalar & value); TORCH_API at::Tensor & fill_(at::Tensor & self, const at::Tensor & value); TORCH_API at::Tensor floor(const at::Tensor & self); TORCH_API at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & floor_(at::Tensor & self); TORCH_API at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & floor_divide_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor frac(const at::Tensor & self); TORCH_API at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & frac_(at::Tensor & self); TORCH_API at::Tensor gcd(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor lcm(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & lcm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & lcm_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & lcm_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor grid_sampler_2d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); TORCH_API ::std::tuple grid_sampler_2d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); TORCH_API at::Tensor grid_sampler_3d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); TORCH_API ::std::tuple grid_sampler_3d_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners); TORCH_API ::std::tuple native_group_norm(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps); TORCH_API ::std::tuple native_group_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, int64_t N, int64_t C, int64_t HxW, int64_t group, ::std::array output_mask); TORCH_API at::Tensor _fft_r2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); TORCH_API at::Tensor & _fft_r2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided); TORCH_API at::Tensor & _fft_r2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out); TORCH_API at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); TORCH_API at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size); TORCH_API at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out); TORCH_API at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); TORCH_API at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward); TORCH_API at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out); TORCH_API at::Tensor index(const at::Tensor & self, const c10::List> & indices); TORCH_API at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false); TORCH_API at::Tensor _inverse_helper(const at::Tensor & self); TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); TORCH_API at::Tensor & isin_outf(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out); TORCH_API at::Tensor isin(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique=false, bool invert=false); TORCH_API at::Tensor & isin_outf(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert, at::Tensor & out); TORCH_API at::Tensor isin(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); TORCH_API at::Tensor & isin_out(at::Tensor & out, const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique=false, bool invert=false); TORCH_API at::Tensor & isin_outf(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out); TORCH_API at::Tensor isnan(const at::Tensor & self); TORCH_API at::Tensor kl_div_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, bool log_target=false); TORCH_API ::std::tuple kthvalue_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false); TORCH_API ::std::tuple kthvalue_outf(const at::Tensor & self, int64_t k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); TORCH_API ::std::tuple native_layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const c10::optional & weight, const c10::optional & bias, double eps); TORCH_API ::std::tuple native_layer_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, at::IntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional & weight, const c10::optional & bias, ::std::array output_mask); TORCH_API at::Tensor & nan_to_num_out(at::Tensor & out, const at::Tensor & self, c10::optional nan=c10::nullopt, c10::optional posinf=c10::nullopt, c10::optional neginf=c10::nullopt); TORCH_API at::Tensor & nan_to_num_outf(const at::Tensor & self, c10::optional nan, c10::optional posinf, c10::optional neginf, at::Tensor & out); TORCH_API at::Tensor & linspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, c10::optional steps=c10::nullopt); TORCH_API at::Tensor & linspace_outf(const at::Scalar & start, const at::Scalar & end, c10::optional steps, at::Tensor & out); TORCH_API at::Tensor log(const at::Tensor & self); TORCH_API at::Tensor & log_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & log_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & log_(at::Tensor & self); TORCH_API at::Tensor log10(const at::Tensor & self); TORCH_API at::Tensor & log10_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & log10_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & log10_(at::Tensor & self); TORCH_API at::Tensor log1p(const at::Tensor & self); TORCH_API at::Tensor & log1p_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & log1p_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & log1p_(at::Tensor & self); TORCH_API at::Tensor log2(const at::Tensor & self); TORCH_API at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & log2_(at::Tensor & self); TORCH_API at::Tensor logaddexp(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logaddexp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logaddexp_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor logaddexp2(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logaddexp2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logaddexp2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor xlogy(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & xlogy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & xlogy_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & xlogy_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, c10::optional steps=c10::nullopt, double base=10.0); TORCH_API at::Tensor & logspace_outf(const at::Scalar & start, const at::Scalar & end, c10::optional steps, double base, at::Tensor & out); TORCH_API at::Tensor _log_softmax(const at::Tensor & self, int64_t dim, bool half_to_float); TORCH_API at::Tensor & _log_softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); TORCH_API at::Tensor & _log_softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); TORCH_API at::Tensor _log_softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); TORCH_API at::Tensor & _log_softmax_backward_data_out(at::Tensor & out, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); TORCH_API at::Tensor & _log_softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor _logcumsumexp(const at::Tensor & self, int64_t dim); TORCH_API at::Tensor & _logcumsumexp_out(at::Tensor & out, const at::Tensor & self, int64_t dim); TORCH_API at::Tensor & _logcumsumexp_outf(const at::Tensor & self, int64_t dim, at::Tensor & out); TORCH_API at::Tensor matrix_exp(const at::Tensor & self); TORCH_API ::std::tuple _aminmax(const at::Tensor & self); TORCH_API ::std::tuple _aminmax(const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple aminmax(const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false); TORCH_API ::std::tuple aminmax_out(at::Tensor & min, at::Tensor & max, const at::Tensor & self, c10::optional dim=c10::nullopt, bool keepdim=false); TORCH_API ::std::tuple aminmax_outf(const at::Tensor & self, c10::optional dim, bool keepdim, at::Tensor & min, at::Tensor & max); TORCH_API at::Tensor _compute_linear_combination(const at::Tensor & input, const at::Tensor & coefficients); TORCH_API at::Tensor & _compute_linear_combination_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & coefficients); TORCH_API at::Tensor & _compute_linear_combination_outf(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out); TORCH_API ::std::tuple max(const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple max_out(at::Tensor & max, at::Tensor & max_values, const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple max_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values); TORCH_API at::Tensor & amax_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); TORCH_API at::Tensor & amax_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); TORCH_API at::Tensor mean(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & mean_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor median(const at::Tensor & self); TORCH_API ::std::tuple median_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple median_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); TORCH_API at::Tensor nanmedian(const at::Tensor & self); TORCH_API ::std::tuple nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple nanmedian_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices); TORCH_API ::std::tuple min(const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple min_out(at::Tensor & min, at::Tensor & min_indices, const at::Tensor & self, int64_t dim, bool keepdim=false); TORCH_API ::std::tuple min_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices); TORCH_API at::Tensor & amin_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false); TORCH_API at::Tensor & amin_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out); TORCH_API ::std::tuple miopen_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon); TORCH_API ::std::tuple miopen_batch_norm_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_var, double epsilon); TORCH_API at::Tensor miopen_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor miopen_convolution_backward_input(at::IntArrayRef self_size, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API ::std::tuple miopen_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, ::std::array output_mask); TORCH_API at::Tensor miopen_convolution_backward_bias(const at::Tensor & grad_output); TORCH_API at::Tensor miopen_convolution_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API ::std::tuple miopen_convolution_transpose_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, ::std::array output_mask); TORCH_API at::Tensor miopen_convolution_transpose_backward_input(const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor miopen_convolution_transpose_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API at::Tensor miopen_depthwise_convolution_backward_input(at::IntArrayRef self_size, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API ::std::tuple miopen_depthwise_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, ::std::array output_mask); TORCH_API at::Tensor miopen_depthwise_convolution_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); TORCH_API ::std::tuple miopen_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional & cx, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state); TORCH_API ::std::tuple> miopen_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask); TORCH_API at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2); TORCH_API at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2); TORCH_API at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out); TORCH_API ::std::tuple mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false); TORCH_API at::Tensor mul(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & mul_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor mv(const at::Tensor & self, const at::Tensor & vec); TORCH_API at::Tensor & mvlgamma_out(at::Tensor & out, const at::Tensor & self, int64_t p); TORCH_API at::Tensor & mvlgamma_outf(const at::Tensor & self, int64_t p, at::Tensor & out); TORCH_API ::std::tuple native_batch_norm(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps); TORCH_API ::std::tuple native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps); TORCH_API ::std::tuple native_batch_norm_outf(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd); TORCH_API ::std::tuple batch_norm_stats(const at::Tensor & input, double eps); TORCH_API at::Tensor batch_norm_elemt(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps); TORCH_API at::Tensor & batch_norm_elemt_out(at::Tensor & out, const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps); TORCH_API at::Tensor & batch_norm_elemt_outf(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out); TORCH_API ::std::tuple batch_norm_gather_stats(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & running_mean, const c10::optional & running_var, double momentum, double eps, int64_t count); TORCH_API ::std::tuple batch_norm_gather_stats_with_counts(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & running_mean, const c10::optional & running_var, double momentum, double eps, const at::Tensor & counts); TORCH_API ::std::tuple native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const c10::optional & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_invstd, bool train, double eps, ::std::array output_mask); TORCH_API ::std::tuple batch_norm_backward_reduce(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, bool input_g, bool weight_g, bool bias_g); TORCH_API at::Tensor batch_norm_backward_elemt(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional & weight, const at::Tensor & mean_dy, const at::Tensor & mean_dy_xmu, const at::Tensor & count); TORCH_API ::std::tuple batch_norm_update_stats(const at::Tensor & input, const c10::optional & running_mean, const c10::optional & running_var, double momentum); TORCH_API at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional compute_mode); TORCH_API at::Tensor _cdist_backward(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist); TORCH_API at::Tensor _pdist_forward(const at::Tensor & self, double p=2); TORCH_API at::Tensor _pdist_backward(const at::Tensor & grad, const at::Tensor & self, double p, const at::Tensor & pdist); TORCH_API bool is_pinned(const at::Tensor & self, c10::optional device=c10::nullopt); TORCH_API at::Tensor _pin_memory(const at::Tensor & self, c10::optional device=c10::nullopt); TORCH_API at::Tensor & randperm_out(at::Tensor & out, int64_t n, c10::optional generator); TORCH_API at::Tensor & randperm_outf(int64_t n, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1); TORCH_API at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out); TORCH_API at::Tensor reciprocal(const at::Tensor & self); TORCH_API at::Tensor & reciprocal_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & reciprocal_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & reciprocal_(at::Tensor & self); TORCH_API at::Tensor neg(const at::Tensor & self); TORCH_API at::Tensor & neg_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & neg_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & neg_(at::Tensor & self); TORCH_API at::Tensor repeat_interleave(const at::Tensor & repeats, c10::optional output_size=c10::nullopt); TORCH_API at::Tensor _reshape_alias(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride); TORCH_API at::Tensor round(const at::Tensor & self); TORCH_API at::Tensor & round_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & round_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & round_(at::Tensor & self); TORCH_API at::Tensor relu(const at::Tensor & self); TORCH_API at::Tensor & relu_(at::Tensor & self); TORCH_API at::Tensor prelu(const at::Tensor & self, const at::Tensor & weight); TORCH_API ::std::tuple prelu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight); TORCH_API at::Tensor gelu(const at::Tensor & self); TORCH_API at::Tensor & gelu_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & gelu_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor gelu_backward(const at::Tensor & grad, const at::Tensor & self); TORCH_API at::Tensor & gelu_backward_out(at::Tensor & grad_input, const at::Tensor & grad, const at::Tensor & self); TORCH_API at::Tensor & gelu_backward_outf(const at::Tensor & grad, const at::Tensor & self, at::Tensor & grad_input); TORCH_API at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5); TORCH_API at::Tensor & hardshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5); TORCH_API at::Tensor & hardshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out); TORCH_API at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); TORCH_API at::Tensor & hardshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd); TORCH_API at::Tensor & hardshrink_backward_outf(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input); TORCH_API at::Tensor rsqrt(const at::Tensor & self); TORCH_API at::Tensor & rsqrt_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & rsqrt_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & rsqrt_(at::Tensor & self); TORCH_API at::Tensor silu(const at::Tensor & self); TORCH_API at::Tensor & silu_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & silu_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & silu_(at::Tensor & self); TORCH_API at::Tensor silu_backward(const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor & silu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor & silu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); TORCH_API at::Tensor mish(const at::Tensor & self); TORCH_API at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & mish_(at::Tensor & self); TORCH_API at::Tensor mish_backward(const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor sigmoid(const at::Tensor & self); TORCH_API at::Tensor & sigmoid_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sigmoid_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sigmoid_(at::Tensor & self); TORCH_API at::Tensor logit(const at::Tensor & self, c10::optional eps=c10::nullopt); TORCH_API at::Tensor & logit_out(at::Tensor & out, const at::Tensor & self, c10::optional eps=c10::nullopt); TORCH_API at::Tensor & logit_outf(const at::Tensor & self, c10::optional eps, at::Tensor & out); TORCH_API at::Tensor & logit_(at::Tensor & self, c10::optional eps=c10::nullopt); TORCH_API at::Tensor sin(const at::Tensor & self); TORCH_API at::Tensor & sin_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sin_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sin_(at::Tensor & self); TORCH_API at::Tensor sinc(const at::Tensor & self); TORCH_API at::Tensor & sinc_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sinc_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sinc_(at::Tensor & self); TORCH_API at::Tensor sinh(const at::Tensor & self); TORCH_API at::Tensor & sinh_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sinh_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sinh_(at::Tensor & self); TORCH_API at::Tensor _softmax(const at::Tensor & self, int64_t dim, bool half_to_float); TORCH_API at::Tensor & _softmax_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool half_to_float); TORCH_API at::Tensor & _softmax_outf(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out); TORCH_API at::Tensor _softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); TORCH_API at::Tensor & _softmax_backward_data_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self); TORCH_API at::Tensor & _softmax_backward_data_outf(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, const at::Tensor & self, at::Tensor & grad_input); TORCH_API at::Tensor & sspaddmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & sspaddmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor sum(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & sum_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & sum_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor nansum(const at::Tensor & self, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor nansum(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & nansum_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & nansum_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor sqrt(const at::Tensor & self); TORCH_API at::Tensor & sqrt_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sqrt_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sqrt_(at::Tensor & self); TORCH_API at::Tensor & square_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & square_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor std(const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim=false); TORCH_API at::Tensor & std_out(at::Tensor & out, const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim=false); TORCH_API at::Tensor & std_outf(const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim, at::Tensor & out); TORCH_API ::std::tuple std_mean(const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim=false); TORCH_API at::Tensor prod(const at::Tensor & self, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor prod(const at::Tensor & self, int64_t dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & prod_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & prod_outf(const at::Tensor & self, int64_t dim, bool keepdim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor tan(const at::Tensor & self); TORCH_API at::Tensor & tan_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & tan_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & tan_(at::Tensor & self); TORCH_API at::Tensor tanh(const at::Tensor & self); TORCH_API at::Tensor & tanh_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & tanh_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & tanh_(at::Tensor & self); TORCH_API at::Tensor & tensordot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other); TORCH_API at::Tensor & tensordot_outf(const at::Tensor & self, const at::Tensor & other, at::IntArrayRef dims_self, at::IntArrayRef dims_other, at::Tensor & out); TORCH_API at::Tensor threshold(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); TORCH_API at::Tensor & threshold_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); TORCH_API at::Tensor & threshold_outf(const at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value, at::Tensor & out); TORCH_API at::Tensor & threshold_(at::Tensor & self, const at::Scalar & threshold, const at::Scalar & value); TORCH_API at::Tensor threshold_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); TORCH_API at::Tensor & threshold_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold); TORCH_API at::Tensor & threshold_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, at::Tensor & grad_input); TORCH_API at::Tensor flip(const at::Tensor & self, at::IntArrayRef dims); TORCH_API at::Tensor roll(const at::Tensor & self, at::IntArrayRef shifts, at::IntArrayRef dims={}); TORCH_API at::Tensor trunc(const at::Tensor & self); TORCH_API at::Tensor & trunc_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & trunc_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & trunc_(at::Tensor & self); TORCH_API ::std::tuple _unique(const at::Tensor & self, bool sorted=true, bool return_inverse=false); TORCH_API ::std::tuple unique_dim(const at::Tensor & self, int64_t dim, bool sorted=true, bool return_inverse=false, bool return_counts=false); TORCH_API ::std::tuple unique_consecutive(const at::Tensor & self, bool return_inverse=false, bool return_counts=false, c10::optional dim=c10::nullopt); TORCH_API ::std::tuple unique_dim_consecutive(const at::Tensor & self, int64_t dim, bool return_inverse=false, bool return_counts=false); TORCH_API ::std::tuple _unique2(const at::Tensor & self, bool sorted=true, bool return_inverse=false, bool return_counts=false); TORCH_API at::Tensor var(const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim=false); TORCH_API at::Tensor & var_out(at::Tensor & out, const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim=false); TORCH_API at::Tensor & var_outf(const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim, at::Tensor & out); TORCH_API ::std::tuple var_mean(const at::Tensor & self, c10::optional dim, c10::optional correction, bool keepdim=false); TORCH_API at::Tensor _s_where(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other); TORCH_API ::std::tuple _weight_norm_cuda_interface(const at::Tensor & v, const at::Tensor & g, int64_t dim=0); TORCH_API ::std::tuple _weight_norm_cuda_interface_backward(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim); TORCH_API at::Tensor _standard_gamma_grad(const at::Tensor & self, const at::Tensor & output); TORCH_API at::Tensor _standard_gamma(const at::Tensor & self, c10::optional generator=c10::nullopt); TORCH_API at::Tensor _dirichlet_grad(const at::Tensor & x, const at::Tensor & alpha, const at::Tensor & total); TORCH_API at::Tensor _sample_dirichlet(const at::Tensor & self, c10::optional generator=c10::nullopt); TORCH_API at::Tensor poisson(const at::Tensor & self, c10::optional generator=c10::nullopt); TORCH_API at::Tensor binomial(const at::Tensor & count, const at::Tensor & prob, c10::optional generator=c10::nullopt); TORCH_API at::Tensor norm(const at::Tensor & self, const c10::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const c10::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype); TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const c10::optional & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out); TORCH_API at::Tensor norm(const at::Tensor & self, const c10::optional & p, at::IntArrayRef dim, bool keepdim=false); TORCH_API at::Tensor & norm_out(at::Tensor & out, const at::Tensor & self, const c10::optional & p, at::IntArrayRef dim, bool keepdim=false); TORCH_API at::Tensor & norm_outf(const at::Tensor & self, const c10::optional & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out); TORCH_API ::std::tuple frexp_out(at::Tensor & mantissa, at::Tensor & exponent, const at::Tensor & self); TORCH_API ::std::tuple frexp_outf(const at::Tensor & self, at::Tensor & mantissa, at::Tensor & exponent); TORCH_API at::Tensor & zero_(at::Tensor & self); TORCH_API at::Tensor sub(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor & sub_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor & sub_outf(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor & sub_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor rsub(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1); TORCH_API at::Tensor heaviside(const at::Tensor & self, const at::Tensor & values); TORCH_API at::Tensor & heaviside_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & values); TORCH_API at::Tensor & heaviside_outf(const at::Tensor & self, const at::Tensor & values, at::Tensor & out); TORCH_API at::Tensor & heaviside_(at::Tensor & self, const at::Tensor & values); TORCH_API at::Tensor addmm(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addmm_outf(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor & addmm_(at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor to_sparse(const at::Tensor & self, int64_t sparse_dim); TORCH_API at::Tensor to_sparse(const at::Tensor & self); TORCH_API at::Tensor quantize_per_tensor(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype); TORCH_API at::Tensor quantize_per_tensor(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype); TORCH_API at::Tensor quantize_per_channel(const at::Tensor & self, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::ScalarType dtype); TORCH_API at::Tensor _make_per_tensor_quantized_tensor(const at::Tensor & self, double scale, int64_t zero_point); TORCH_API at::Tensor _make_per_channel_quantized_tensor(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis); TORCH_API ::std::tuple fake_quantize_per_tensor_affine_cachemask(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max); TORCH_API ::std::tuple _fake_quantize_per_tensor_affine_cachemask_tensor_qparams(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max); TORCH_API at::Tensor _fake_quantize_learnable_per_tensor_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); TORCH_API ::std::tuple fake_quantize_per_channel_affine_cachemask(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max); TORCH_API at::Tensor _fake_quantize_learnable_per_channel_affine(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, double grad_factor=1.0); TORCH_API ::std::tuple _fused_moving_avg_obs_fq_helper(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant=false, bool symmetric_quant=false); TORCH_API at::Scalar _local_scalar_dense(const at::Tensor & self); TORCH_API ::std::tuple _thnn_fused_lstm_cell(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & cx, const c10::optional & input_bias={}, const c10::optional & hidden_bias={}); TORCH_API ::std::tuple _thnn_fused_lstm_cell_backward(const c10::optional & grad_hy, const c10::optional & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias); TORCH_API ::std::tuple _thnn_fused_gru_cell(const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const c10::optional & input_bias={}, const c10::optional & hidden_bias={}); TORCH_API ::std::tuple _thnn_fused_gru_cell_backward(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias); TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source); TORCH_API at::Tensor & set_(at::Tensor & self, at::Storage source, int64_t storage_offset, at::IntArrayRef size, at::IntArrayRef stride={}); TORCH_API at::Tensor & set_(at::Tensor & self, const at::Tensor & source); TORCH_API at::Tensor & set_(at::Tensor & self); TORCH_API bool is_set_to(const at::Tensor & self, const at::Tensor & tensor); TORCH_API at::Tensor & masked_fill_(at::Tensor & self, const at::Tensor & mask, const at::Scalar & value); TORCH_API at::Tensor & masked_fill_(at::Tensor & self, const at::Tensor & mask, const at::Tensor & value); TORCH_API at::Tensor & masked_scatter_(at::Tensor & self, const at::Tensor & mask, const at::Tensor & source); TORCH_API at::Tensor view(const at::Tensor & self, at::IntArrayRef size); TORCH_API at::Tensor & put_(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate=false); TORCH_API at::Tensor & index_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha); TORCH_API at::Tensor & index_fill_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); TORCH_API at::Tensor & index_fill_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & value); TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out); TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value); TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out); TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce); TORCH_API at::Tensor scatter(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); TORCH_API at::Tensor & scatter_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); TORCH_API at::Tensor & scatter_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce, at::Tensor & out); TORCH_API at::Tensor & scatter_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce); TORCH_API at::Tensor scatter_add(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); TORCH_API at::Tensor & scatter_add_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); TORCH_API at::Tensor & scatter_add_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out); TORCH_API at::Tensor & scatter_add_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src); TORCH_API at::Tensor eq(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & eq_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & eq_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor eq(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & eq_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & eq_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & eq_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_and(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_and_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_or(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_or_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_xor(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_xor_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor __lshift__(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & __ilshift__(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor __lshift__(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & __ilshift__(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_left_shift(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & bitwise_left_shift_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & bitwise_left_shift_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_left_shift_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor bitwise_left_shift(const at::Scalar & self, const at::Tensor & other); TORCH_API at::Tensor __rshift__(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & __irshift__(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor __rshift__(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & __irshift__(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_right_shift_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor bitwise_right_shift(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & bitwise_right_shift_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & bitwise_right_shift_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & bitwise_right_shift_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor bitwise_right_shift(const at::Scalar & self, const at::Tensor & other); TORCH_API at::Tensor & tril_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); TORCH_API at::Tensor & tril_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); TORCH_API at::Tensor & tril_(at::Tensor & self, int64_t diagonal=0); TORCH_API at::Tensor & triu_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); TORCH_API at::Tensor & triu_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); TORCH_API at::Tensor & triu_(at::Tensor & self, int64_t diagonal=0); TORCH_API at::Tensor digamma(const at::Tensor & self); TORCH_API at::Tensor & digamma_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & digamma_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & digamma_(at::Tensor & self); TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); TORCH_API at::Tensor & lerp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); TORCH_API at::Tensor & lerp_outf(const at::Tensor & self, const at::Tensor & end, const at::Scalar & weight, at::Tensor & out); TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Scalar & weight); TORCH_API at::Tensor lerp(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); TORCH_API at::Tensor & lerp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); TORCH_API at::Tensor & lerp_outf(const at::Tensor & self, const at::Tensor & end, const at::Tensor & weight, at::Tensor & out); TORCH_API at::Tensor & lerp_(at::Tensor & self, const at::Tensor & end, const at::Tensor & weight); TORCH_API at::Tensor addbmm(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addbmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & addbmm_outf(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out); TORCH_API at::Tensor & addbmm_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1); TORCH_API at::Tensor & random_(at::Tensor & self, int64_t from, c10::optional to, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & random_(at::Tensor & self, int64_t to, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & random_(at::Tensor & self, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & uniform_(at::Tensor & self, double from=0, double to=1, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & cauchy_(at::Tensor & self, double median=0, double sigma=1, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & log_normal_(at::Tensor & self, double mean=1, double std=2, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & exponential_(at::Tensor & self, double lambd=1, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & geometric_(at::Tensor & self, double p, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & diag_out(at::Tensor & out, const at::Tensor & self, int64_t diagonal=0); TORCH_API at::Tensor & diag_outf(const at::Tensor & self, int64_t diagonal, at::Tensor & out); TORCH_API at::Tensor cross(const at::Tensor & self, const at::Tensor & other, c10::optional dim=c10::nullopt); TORCH_API at::Tensor & cross_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, c10::optional dim=c10::nullopt); TORCH_API at::Tensor & cross_outf(const at::Tensor & self, const at::Tensor & other, c10::optional dim, at::Tensor & out); TORCH_API at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); TORCH_API at::Tensor tril_indices(int64_t row, int64_t col, int64_t offset, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset=0, at::TensorOptions options=at::kLong); TORCH_API at::Tensor triu_indices(int64_t row, int64_t col, int64_t offset, c10::optional dtype, c10::optional layout, c10::optional device, c10::optional pin_memory); TORCH_API at::Tensor trace(const at::Tensor & self); TORCH_API at::Tensor ne(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & ne_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & ne_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & ne_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor ne(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & ne_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & ne_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & ne_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor ge(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor ge(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & ge_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & ge_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & ge_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor le(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & le_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & le_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & le_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor le(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & le_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & le_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & le_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor gt(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor gt(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & gt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & gt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & gt_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor lt(const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & lt_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor & lt_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out); TORCH_API at::Tensor & lt_(at::Tensor & self, const at::Scalar & other); TORCH_API at::Tensor lt(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & lt_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & lt_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & lt_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor take(const at::Tensor & self, const at::Tensor & index); TORCH_API at::Tensor & take_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & index); TORCH_API at::Tensor & take_outf(const at::Tensor & self, const at::Tensor & index, at::Tensor & out); TORCH_API at::Tensor index_select(const at::Tensor & self, int64_t dim, const at::Tensor & index); TORCH_API at::Tensor & index_select_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index); TORCH_API at::Tensor & index_select_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out); TORCH_API at::Tensor masked_select(const at::Tensor & self, const at::Tensor & mask); TORCH_API at::Tensor & masked_select_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mask); TORCH_API at::Tensor & masked_select_outf(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out); TORCH_API at::Tensor nonzero(const at::Tensor & self); TORCH_API at::Tensor & nonzero_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & nonzero_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor gather(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false); TORCH_API at::Tensor & gather_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad=false); TORCH_API at::Tensor & gather_outf(const at::Tensor & self, int64_t dim, const at::Tensor & index, bool sparse_grad, at::Tensor & out); TORCH_API at::Tensor addcmul(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); TORCH_API at::Tensor & addcmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); TORCH_API at::Tensor & addcmul_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); TORCH_API at::Tensor & addcmul_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); TORCH_API at::Tensor addcdiv(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); TORCH_API at::Tensor & addcdiv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); TORCH_API at::Tensor & addcdiv_outf(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out); TORCH_API at::Tensor & addcdiv_(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value=1); TORCH_API ::std::tuple lstsq(const at::Tensor & self, const at::Tensor & A); TORCH_API ::std::tuple lstsq_out(at::Tensor & X, at::Tensor & qr, const at::Tensor & self, const at::Tensor & A); TORCH_API ::std::tuple lstsq_outf(const at::Tensor & self, const at::Tensor & A, at::Tensor & X, at::Tensor & qr); TORCH_API ::std::tuple triangular_solve(const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false); TORCH_API ::std::tuple triangular_solve_out(at::Tensor & X, at::Tensor & M, const at::Tensor & self, const at::Tensor & A, bool upper=true, bool transpose=false, bool unitriangular=false); TORCH_API ::std::tuple triangular_solve_outf(const at::Tensor & self, const at::Tensor & A, bool upper, bool transpose, bool unitriangular, at::Tensor & X, at::Tensor & M); TORCH_API ::std::tuple _symeig_helper(const at::Tensor & self, bool eigenvectors, bool upper); TORCH_API ::std::tuple _svd_helper(const at::Tensor & self, bool some, bool compute_uv); TORCH_API at::Tensor cholesky(const at::Tensor & self, bool upper=false); TORCH_API at::Tensor & cholesky_out(at::Tensor & out, const at::Tensor & self, bool upper=false); TORCH_API at::Tensor & cholesky_outf(const at::Tensor & self, bool upper, at::Tensor & out); TORCH_API at::Tensor _cholesky_solve_helper(const at::Tensor & self, const at::Tensor & A, bool upper); TORCH_API ::std::tuple _solve_helper(const at::Tensor & self, const at::Tensor & A); TORCH_API at::Tensor cholesky_inverse(const at::Tensor & self, bool upper=false); TORCH_API at::Tensor & cholesky_inverse_out(at::Tensor & out, const at::Tensor & self, bool upper=false); TORCH_API at::Tensor & cholesky_inverse_outf(const at::Tensor & self, bool upper, at::Tensor & out); TORCH_API ::std::tuple geqrf(const at::Tensor & self); TORCH_API ::std::tuple geqrf_out(at::Tensor & a, at::Tensor & tau, const at::Tensor & self); TORCH_API ::std::tuple geqrf_outf(const at::Tensor & self, at::Tensor & a, at::Tensor & tau); TORCH_API at::Tensor ormqr(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false); TORCH_API at::Tensor & ormqr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false); TORCH_API at::Tensor & ormqr_outf(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, at::Tensor & out); TORCH_API ::std::tuple _lu_with_info(const at::Tensor & self, bool pivot=true, bool check_errors=true); TORCH_API at::Tensor lu_solve(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots); TORCH_API at::Tensor & lu_solve_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots); TORCH_API at::Tensor & lu_solve_outf(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out); TORCH_API ::std::tuple lu_unpack(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true); TORCH_API ::std::tuple lu_unpack_out(at::Tensor & P, at::Tensor & L, at::Tensor & U, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data=true, bool unpack_pivots=true); TORCH_API ::std::tuple lu_unpack_outf(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U); TORCH_API at::Tensor multinomial(const at::Tensor & self, int64_t num_samples, bool replacement=false, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & multinomial_out(at::Tensor & out, const at::Tensor & self, int64_t num_samples, bool replacement=false, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & multinomial_outf(const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor lgamma(const at::Tensor & self); TORCH_API at::Tensor & lgamma_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & lgamma_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & lgamma_(at::Tensor & self); TORCH_API at::Tensor polygamma(int64_t n, const at::Tensor & self); TORCH_API at::Tensor & polygamma_out(at::Tensor & out, int64_t n, const at::Tensor & self); TORCH_API at::Tensor & polygamma_outf(int64_t n, const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor erfinv(const at::Tensor & self); TORCH_API at::Tensor & erfinv_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & erfinv_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & erfinv_(at::Tensor & self); TORCH_API at::Tensor i0(const at::Tensor & self); TORCH_API at::Tensor & i0_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & i0_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & i0_(at::Tensor & self); TORCH_API at::Tensor sign(const at::Tensor & self); TORCH_API at::Tensor & sign_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & sign_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & sign_(at::Tensor & self); TORCH_API at::Tensor signbit(const at::Tensor & self); TORCH_API at::Tensor & signbit_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & signbit_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor atan2(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & atan2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & atan2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & atan2_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor histc(const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); TORCH_API at::Tensor & histc_out(at::Tensor & out, const at::Tensor & self, int64_t bins=100, const at::Scalar & min=0, const at::Scalar & max=0); TORCH_API at::Tensor & histc_outf(const at::Tensor & self, int64_t bins, const at::Scalar & min, const at::Scalar & max, at::Tensor & out); TORCH_API at::Tensor fmod(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & fmod_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & fmod_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & fmod_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor hypot(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & hypot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & hypot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & hypot_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor igamma(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & igamma_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & igamma_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & igamma_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor igammac(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & igammac_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & igammac_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & igammac_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor nextafter(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & nextafter_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & nextafter_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & nextafter_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor remainder(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & remainder_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & remainder_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor & remainder_(at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor remainder(const at::Scalar & self, const at::Tensor & other); TORCH_API at::Tensor min(const at::Tensor & self); TORCH_API at::Tensor fmin(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & fmin_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & fmin_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor max(const at::Tensor & self); TORCH_API at::Tensor fmax(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & fmax_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & fmax_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor maximum(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & maximum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & maximum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor minimum(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & minimum_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & minimum_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API ::std::tuple sort(const at::Tensor & self, int64_t dim=-1, bool descending=false); TORCH_API ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim=-1, bool descending=false); TORCH_API ::std::tuple sort_outf(const at::Tensor & self, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices); TORCH_API ::std::tuple sort(const at::Tensor & self, c10::optional stable, int64_t dim=-1, bool descending=false); TORCH_API ::std::tuple sort_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, c10::optional stable, int64_t dim=-1, bool descending=false); TORCH_API ::std::tuple sort_outf(const at::Tensor & self, c10::optional stable, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices); TORCH_API ::std::tuple topk(const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true); TORCH_API ::std::tuple topk_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true); TORCH_API ::std::tuple topk_outf(const at::Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted, at::Tensor & values, at::Tensor & indices); TORCH_API at::Tensor all(const at::Tensor & self); TORCH_API at::Tensor & all_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & all_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor any(const at::Tensor & self); TORCH_API at::Tensor & any_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & any_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor renorm(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); TORCH_API at::Tensor & renorm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); TORCH_API at::Tensor & renorm_outf(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, at::Tensor & out); TORCH_API at::Tensor & renorm_(at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm); TORCH_API at::Tensor unfold(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step); TORCH_API at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step); TORCH_API bool equal(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor pow(const at::Tensor & self, const at::Tensor & exponent); TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & exponent); TORCH_API at::Tensor & pow_outf(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out); TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Tensor & exponent); TORCH_API at::Tensor pow(const at::Scalar & self, const at::Tensor & exponent); TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & exponent); TORCH_API at::Tensor & pow_outf(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out); TORCH_API at::Tensor pow(const at::Tensor & self, const at::Scalar & exponent); TORCH_API at::Tensor & pow_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & exponent); TORCH_API at::Tensor & pow_outf(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out); TORCH_API at::Tensor & pow_(at::Tensor & self, const at::Scalar & exponent); TORCH_API at::Tensor & normal_(at::Tensor & self, double mean=0, double std=1, c10::optional generator=c10::nullopt); TORCH_API at::Tensor normal(const at::Tensor & mean, double std=1, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, double std=1, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, double std, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor normal(double mean, const at::Tensor & std, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & normal_out(at::Tensor & out, double mean, const at::Tensor & std, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & normal_outf(double mean, const at::Tensor & std, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor normal(const at::Tensor & mean, const at::Tensor & std, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & normal_out(at::Tensor & out, const at::Tensor & mean, const at::Tensor & std, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & normal_outf(const at::Tensor & mean, const at::Tensor & std, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor & _index_copy_(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source); TORCH_API void _amp_foreach_non_finite_check_and_unscale_(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale); TORCH_API at::Tensor & _amp_update_scale_(at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval); TORCH_API at::Tensor _cat(at::TensorList tensors, int64_t dim=0); TORCH_API at::Tensor & _cat_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0); TORCH_API at::Tensor & _cat_outf(at::TensorList tensors, int64_t dim, at::Tensor & out); TORCH_API ::std::vector _foreach_add(at::TensorList tensors, const at::Scalar & scalar); TORCH_API void _foreach_add_(at::TensorList self, const at::Scalar & scalar); TORCH_API ::std::vector _foreach_sub(at::TensorList tensors, const at::Scalar & scalar); TORCH_API void _foreach_sub_(at::TensorList self, const at::Scalar & scalar); TORCH_API ::std::vector _foreach_mul(at::TensorList tensors, const at::Scalar & scalar); TORCH_API void _foreach_mul_(at::TensorList self, const at::Scalar & scalar); TORCH_API ::std::vector _foreach_div(at::TensorList tensors, const at::Scalar & scalar); TORCH_API void _foreach_div_(at::TensorList self, const at::Scalar & scalar); TORCH_API ::std::vector _foreach_add(at::TensorList tensors1, at::TensorList tensors2, const at::Scalar & alpha=1); TORCH_API void _foreach_add_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); TORCH_API ::std::vector _foreach_sub(at::TensorList tensors1, at::TensorList tensors2, const at::Scalar & alpha=1); TORCH_API void _foreach_sub_(at::TensorList self, at::TensorList other, const at::Scalar & alpha=1); TORCH_API ::std::vector _foreach_mul(at::TensorList tensors1, at::TensorList tensors2); TORCH_API void _foreach_mul_(at::TensorList self, at::TensorList other); TORCH_API ::std::vector _foreach_div(at::TensorList tensors1, at::TensorList tensors2); TORCH_API void _foreach_div_(at::TensorList self, at::TensorList other); TORCH_API ::std::vector _foreach_add(at::TensorList tensors, at::ArrayRef scalars); TORCH_API void _foreach_add_(at::TensorList self, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_sub(at::TensorList tensors, at::ArrayRef scalars); TORCH_API void _foreach_sub_(at::TensorList self, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_div(at::TensorList tensors, at::ArrayRef scalars); TORCH_API void _foreach_div_(at::TensorList self, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_mul(at::TensorList tensors, at::ArrayRef scalars); TORCH_API void _foreach_mul_(at::TensorList self, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_exp(at::TensorList tensors); TORCH_API void _foreach_zero_(at::TensorList self); TORCH_API void _foreach_exp_(at::TensorList self); TORCH_API ::std::vector _foreach_sqrt(at::TensorList tensors); TORCH_API void _foreach_sqrt_(at::TensorList self); TORCH_API ::std::vector _foreach_abs(at::TensorList tensors); TORCH_API void _foreach_abs_(at::TensorList self); TORCH_API ::std::vector _foreach_acos(at::TensorList tensors); TORCH_API void _foreach_acos_(at::TensorList self); TORCH_API ::std::vector _foreach_asin(at::TensorList tensors); TORCH_API void _foreach_asin_(at::TensorList self); TORCH_API ::std::vector _foreach_atan(at::TensorList tensors); TORCH_API void _foreach_atan_(at::TensorList self); TORCH_API ::std::vector _foreach_ceil(at::TensorList tensors); TORCH_API void _foreach_ceil_(at::TensorList self); TORCH_API ::std::vector _foreach_cos(at::TensorList tensors); TORCH_API void _foreach_cos_(at::TensorList self); TORCH_API ::std::vector _foreach_cosh(at::TensorList tensors); TORCH_API void _foreach_cosh_(at::TensorList self); TORCH_API ::std::vector _foreach_erf(at::TensorList tensors); TORCH_API void _foreach_erf_(at::TensorList self); TORCH_API ::std::vector _foreach_erfc(at::TensorList tensors); TORCH_API void _foreach_erfc_(at::TensorList self); TORCH_API ::std::vector _foreach_expm1(at::TensorList tensors); TORCH_API void _foreach_expm1_(at::TensorList self); TORCH_API ::std::vector _foreach_floor(at::TensorList tensors); TORCH_API void _foreach_floor_(at::TensorList self); TORCH_API ::std::vector _foreach_log(at::TensorList tensors); TORCH_API void _foreach_log_(at::TensorList self); TORCH_API ::std::vector _foreach_log10(at::TensorList tensors); TORCH_API void _foreach_log10_(at::TensorList self); TORCH_API ::std::vector _foreach_log1p(at::TensorList tensors); TORCH_API void _foreach_log1p_(at::TensorList self); TORCH_API ::std::vector _foreach_log2(at::TensorList tensors); TORCH_API void _foreach_log2_(at::TensorList self); TORCH_API ::std::vector _foreach_neg(at::TensorList tensors); TORCH_API void _foreach_neg_(at::TensorList self); TORCH_API ::std::vector _foreach_tan(at::TensorList tensors); TORCH_API void _foreach_tan_(at::TensorList self); TORCH_API ::std::vector _foreach_tanh(at::TensorList tensors); TORCH_API void _foreach_tanh_(at::TensorList self); TORCH_API ::std::vector _foreach_sin(at::TensorList tensors); TORCH_API void _foreach_sin_(at::TensorList self); TORCH_API ::std::vector _foreach_sinh(at::TensorList tensors); TORCH_API void _foreach_sinh_(at::TensorList self); TORCH_API ::std::vector _foreach_round(at::TensorList tensors); TORCH_API void _foreach_round_(at::TensorList self); TORCH_API ::std::vector _foreach_lgamma(at::TensorList tensors); TORCH_API void _foreach_lgamma_(at::TensorList self); TORCH_API ::std::vector _foreach_frac(at::TensorList tensors); TORCH_API void _foreach_frac_(at::TensorList self); TORCH_API ::std::vector _foreach_reciprocal(at::TensorList tensors); TORCH_API void _foreach_reciprocal_(at::TensorList self); TORCH_API ::std::vector _foreach_sigmoid(at::TensorList tensors); TORCH_API void _foreach_sigmoid_(at::TensorList self); TORCH_API ::std::vector _foreach_trunc(at::TensorList tensors); TORCH_API void _foreach_trunc_(at::TensorList self); TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); TORCH_API void _foreach_addcdiv_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); TORCH_API void _foreach_addcmul_(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_addcdiv(at::TensorList input, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); TORCH_API ::std::vector _foreach_addcmul(at::TensorList input, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value=1); TORCH_API ::std::vector _foreach_addcdiv(at::TensorList input, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_addcmul(at::TensorList input, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef scalars); TORCH_API ::std::vector _foreach_maximum(at::TensorList tensors1, at::TensorList tensors2); TORCH_API ::std::vector _foreach_minimum(at::TensorList tensors1, at::TensorList tensors2); TORCH_API at::Tensor bucketize(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); TORCH_API at::Tensor & bucketize_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); TORCH_API at::Tensor & bucketize_outf(const at::Tensor & self, const at::Tensor & boundaries, bool out_int32, bool right, at::Tensor & out); TORCH_API at::Tensor bucketize(const at::Scalar & self, const at::Tensor & boundaries, bool out_int32=false, bool right=false); TORCH_API at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false); TORCH_API at::Tensor & searchsorted_out(at::Tensor & out, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32=false, bool right=false); TORCH_API at::Tensor & searchsorted_outf(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, at::Tensor & out); TORCH_API at::Tensor searchsorted(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32=false, bool right=false); TORCH_API at::Tensor _convert_indices_from_coo_to_csr(const at::Tensor & self, int64_t size, bool out_int32=false); TORCH_API at::Tensor & _convert_indices_from_coo_to_csr_out(at::Tensor & out, const at::Tensor & self, int64_t size, bool out_int32=false); TORCH_API at::Tensor & _convert_indices_from_coo_to_csr_outf(const at::Tensor & self, int64_t size, bool out_int32, at::Tensor & out); TORCH_API at::Tensor mse_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & mse_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & mse_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out); TORCH_API at::Tensor mse_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); TORCH_API at::Tensor & mse_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); TORCH_API at::Tensor & mse_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); TORCH_API at::Tensor & l1_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction); TORCH_API at::Tensor & l1_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input); TORCH_API at::Tensor multi_margin_loss(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & multi_margin_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p=1, const at::Scalar & margin=1, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & multi_margin_loss_outf(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight, int64_t reduction, at::Tensor & out); TORCH_API at::Tensor multi_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & multi_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean); TORCH_API at::Tensor & multi_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional & weight, int64_t reduction, at::Tensor & grad_input); TORCH_API ::std::tuple multilabel_margin_loss_forward(const at::Tensor & self, const at::Tensor & target, int64_t reduction); TORCH_API ::std::tuple multilabel_margin_loss_forward_out(at::Tensor & output, at::Tensor & is_target, const at::Tensor & self, const at::Tensor & target, int64_t reduction); TORCH_API ::std::tuple multilabel_margin_loss_forward_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target); TORCH_API at::Tensor multilabel_margin_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); TORCH_API at::Tensor & multilabel_margin_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target); TORCH_API at::Tensor & multilabel_margin_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input); TORCH_API ::std::tuple nll_loss_forward(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index); TORCH_API ::std::tuple nll_loss_forward_out(at::Tensor & output, at::Tensor & total_weight, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index); TORCH_API ::std::tuple nll_loss_forward_outf(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, at::Tensor & output, at::Tensor & total_weight); TORCH_API at::Tensor nll_loss_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); TORCH_API at::Tensor & nll_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); TORCH_API at::Tensor & nll_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); TORCH_API ::std::tuple nll_loss2d_forward(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index); TORCH_API ::std::tuple nll_loss2d_forward_out(at::Tensor & output, at::Tensor & total_weight, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index); TORCH_API ::std::tuple nll_loss2d_forward_outf(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, at::Tensor & output, at::Tensor & total_weight); TORCH_API at::Tensor nll_loss2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); TORCH_API at::Tensor & nll_loss2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight); TORCH_API at::Tensor & nll_loss2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, int64_t ignore_index, const at::Tensor & total_weight, at::Tensor & grad_input); TORCH_API at::Tensor smooth_l1_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double beta=1.0); TORCH_API at::Tensor & smooth_l1_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double beta=1.0); TORCH_API at::Tensor & smooth_l1_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out); TORCH_API at::Tensor & smooth_l1_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta); TORCH_API at::Tensor & smooth_l1_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & grad_input); TORCH_API at::Tensor huber_loss(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0); TORCH_API at::Tensor & huber_loss_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, double delta=1.0); TORCH_API at::Tensor & huber_loss_outf(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & out); TORCH_API at::Tensor & huber_loss_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta); TORCH_API at::Tensor & huber_loss_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double delta, at::Tensor & grad_input); TORCH_API at::Tensor elu(const at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); TORCH_API at::Tensor & elu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); TORCH_API at::Tensor & elu_outf(const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, at::Tensor & out); TORCH_API at::Tensor & elu_(at::Tensor & self, const at::Scalar & alpha=1, const at::Scalar & scale=1, const at::Scalar & input_scale=1); TORCH_API at::Tensor elu_backward(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); TORCH_API at::Tensor & elu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result); TORCH_API at::Tensor & elu_backward_outf(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result, at::Tensor & grad_input); TORCH_API at::Tensor glu(const at::Tensor & self, int64_t dim=-1); TORCH_API at::Tensor & glu_out(at::Tensor & out, const at::Tensor & self, int64_t dim=-1); TORCH_API at::Tensor & glu_outf(const at::Tensor & self, int64_t dim, at::Tensor & out); TORCH_API at::Tensor glu_backward(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim); TORCH_API at::Tensor & glu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim); TORCH_API at::Tensor & glu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input); TORCH_API at::Tensor hardsigmoid(const at::Tensor & self); TORCH_API at::Tensor & hardsigmoid_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & hardsigmoid_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & hardsigmoid_(at::Tensor & self); TORCH_API at::Tensor hardsigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor & hardsigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor & hardsigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); TORCH_API at::Tensor hardtanh(const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1); TORCH_API at::Tensor & hardtanh_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1); TORCH_API at::Tensor & hardtanh_outf(const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & out); TORCH_API at::Tensor & hardtanh_(at::Tensor & self, const at::Scalar & min_val=-1, const at::Scalar & max_val=1); TORCH_API at::Tensor hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val); TORCH_API at::Tensor & hardtanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val); TORCH_API at::Tensor & hardtanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input); TORCH_API at::Tensor hardswish(const at::Tensor & self); TORCH_API at::Tensor & hardswish_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & hardswish_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor & hardswish_(at::Tensor & self); TORCH_API at::Tensor hardswish_backward(const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor leaky_relu(const at::Tensor & self, const at::Scalar & negative_slope=0.01); TORCH_API at::Tensor & leaky_relu_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & negative_slope=0.01); TORCH_API at::Tensor & leaky_relu_outf(const at::Tensor & self, const at::Scalar & negative_slope, at::Tensor & out); TORCH_API at::Tensor & leaky_relu_(at::Tensor & self, const at::Scalar & negative_slope=0.01); TORCH_API at::Tensor leaky_relu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); TORCH_API at::Tensor & leaky_relu_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result); TORCH_API at::Tensor & leaky_relu_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input); TORCH_API ::std::tuple log_sigmoid_forward(const at::Tensor & self); TORCH_API ::std::tuple log_sigmoid_forward_out(at::Tensor & output, at::Tensor & buffer, const at::Tensor & self); TORCH_API ::std::tuple log_sigmoid_forward_outf(const at::Tensor & self, at::Tensor & output, at::Tensor & buffer); TORCH_API at::Tensor log_sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & buffer); TORCH_API at::Tensor & log_sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & buffer); TORCH_API at::Tensor & log_sigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & buffer, at::Tensor & grad_input); TORCH_API at::Tensor rrelu_with_noise(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & rrelu_with_noise_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional generator=c10::nullopt); TORCH_API at::Tensor & rrelu_with_noise_outf(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional generator, at::Tensor & out); TORCH_API at::Tensor & rrelu_with_noise_(at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional generator=c10::nullopt); TORCH_API at::Tensor softplus(const at::Tensor & self, const at::Scalar & beta=1, const at::Scalar & threshold=20); TORCH_API at::Tensor & softplus_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & beta=1, const at::Scalar & threshold=20); TORCH_API at::Tensor & softplus_outf(const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & out); TORCH_API at::Tensor softplus_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, const at::Tensor & output); TORCH_API at::Tensor & softplus_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, const at::Tensor & output); TORCH_API at::Tensor & softplus_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, const at::Tensor & output, at::Tensor & grad_input); TORCH_API at::Tensor softshrink(const at::Tensor & self, const at::Scalar & lambd=0.5); TORCH_API at::Tensor & softshrink_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & lambd=0.5); TORCH_API at::Tensor & softshrink_outf(const at::Tensor & self, const at::Scalar & lambd, at::Tensor & out); TORCH_API at::Tensor softshrink_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); TORCH_API at::Tensor & softshrink_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd); TORCH_API at::Tensor & softshrink_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input); TORCH_API at::Tensor & adaptive_avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size); TORCH_API at::Tensor & adaptive_avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); TORCH_API at::Tensor _adaptive_avg_pool2d(const at::Tensor & self, at::IntArrayRef output_size); TORCH_API at::Tensor _adaptive_avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor & adaptive_avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size); TORCH_API at::Tensor & adaptive_avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out); TORCH_API at::Tensor _adaptive_avg_pool3d(const at::Tensor & self, at::IntArrayRef output_size); TORCH_API at::Tensor & adaptive_avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self); TORCH_API at::Tensor & adaptive_avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input); TORCH_API at::Tensor _adaptive_avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self); TORCH_API ::std::tuple adaptive_max_pool2d(const at::Tensor & self, at::IntArrayRef output_size); TORCH_API ::std::tuple adaptive_max_pool2d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); TORCH_API ::std::tuple adaptive_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); TORCH_API at::Tensor adaptive_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); TORCH_API at::Tensor & adaptive_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); TORCH_API at::Tensor & adaptive_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); TORCH_API ::std::tuple adaptive_max_pool3d(const at::Tensor & self, at::IntArrayRef output_size); TORCH_API ::std::tuple adaptive_max_pool3d_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef output_size); TORCH_API ::std::tuple adaptive_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out, at::Tensor & indices); TORCH_API at::Tensor adaptive_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); TORCH_API at::Tensor & adaptive_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices); TORCH_API at::Tensor & adaptive_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::Tensor & grad_input); TORCH_API at::Tensor avg_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt); TORCH_API at::Tensor & avg_pool2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt); TORCH_API at::Tensor & avg_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & out); TORCH_API at::Tensor avg_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override); TORCH_API at::Tensor & avg_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override); TORCH_API at::Tensor & avg_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & grad_input); TORCH_API at::Tensor avg_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt); TORCH_API at::Tensor & avg_pool3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true, c10::optional divisor_override=c10::nullopt); TORCH_API at::Tensor & avg_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & out); TORCH_API at::Tensor avg_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override); TORCH_API at::Tensor & avg_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override); TORCH_API at::Tensor & avg_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional divisor_override, at::Tensor & grad_input); TORCH_API ::std::tuple fractional_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); TORCH_API ::std::tuple fractional_max_pool2d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); TORCH_API ::std::tuple fractional_max_pool2d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices); TORCH_API at::Tensor fractional_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); TORCH_API at::Tensor & fractional_max_pool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); TORCH_API at::Tensor & fractional_max_pool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input); TORCH_API ::std::tuple fractional_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); TORCH_API ::std::tuple fractional_max_pool3d_out(at::Tensor & output, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples); TORCH_API ::std::tuple fractional_max_pool3d_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & random_samples, at::Tensor & output, at::Tensor & indices); TORCH_API at::Tensor fractional_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); TORCH_API at::Tensor & fractional_max_pool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices); TORCH_API at::Tensor & fractional_max_pool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input); TORCH_API ::std::tuple max_pool2d_with_indices(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); TORCH_API ::std::tuple max_pool2d_with_indices_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); TORCH_API ::std::tuple max_pool2d_with_indices_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); TORCH_API at::Tensor max_pool2d_with_indices_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); TORCH_API at::Tensor & max_pool2d_with_indices_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); TORCH_API at::Tensor & max_pool2d_with_indices_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input); TORCH_API ::std::tuple max_pool3d_with_indices(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); TORCH_API ::std::tuple max_pool3d_with_indices_out(at::Tensor & out, at::Tensor & indices, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false); TORCH_API ::std::tuple max_pool3d_with_indices_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices); TORCH_API at::Tensor max_pool3d_with_indices_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); TORCH_API at::Tensor & max_pool3d_with_indices_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices); TORCH_API at::Tensor & max_pool3d_with_indices_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input); TORCH_API at::Tensor max_unpool2d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size); TORCH_API at::Tensor & max_unpool2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size); TORCH_API at::Tensor & max_unpool2d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & out); TORCH_API at::Tensor max_unpool2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size); TORCH_API at::Tensor & max_unpool2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size); TORCH_API at::Tensor & max_unpool2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::Tensor & grad_input); TORCH_API at::Tensor max_unpool3d(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); TORCH_API at::Tensor & max_unpool3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); TORCH_API at::Tensor & max_unpool3d_outf(const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor max_unpool3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); TORCH_API at::Tensor & max_unpool3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding); TORCH_API at::Tensor & max_unpool3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & indices, at::IntArrayRef output_size, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor reflection_pad1d(const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor reflection_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor reflection_pad2d(const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor reflection_pad2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor reflection_pad3d(const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor reflection_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & reflection_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor replication_pad1d(const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad1d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor replication_pad1d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad1d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor replication_pad2d(const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad2d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor replication_pad2d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor replication_pad3d(const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad3d_outf(const at::Tensor & self, at::IntArrayRef padding, at::Tensor & out); TORCH_API at::Tensor replication_pad3d_backward(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding); TORCH_API at::Tensor & replication_pad3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::Tensor & grad_input); TORCH_API at::Tensor upsample_nearest3d(const at::Tensor & input, c10::optional output_size, c10::optional> scale_factors); TORCH_API at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, c10::optional output_size, at::IntArrayRef input_size, c10::optional> scale_factors); TORCH_API at::Tensor upsample_linear1d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_linear1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_linear1d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales, at::Tensor & out); TORCH_API at::Tensor upsample_linear1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_linear1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_linear1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales, at::Tensor & grad_input); TORCH_API at::Tensor upsample_bilinear2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bilinear2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bilinear2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); TORCH_API at::Tensor upsample_bilinear2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bilinear2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bilinear2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); TORCH_API at::Tensor upsample_bicubic2d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bicubic2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bicubic2d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); TORCH_API at::Tensor upsample_bicubic2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bicubic2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_bicubic2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); TORCH_API at::Tensor upsample_trilinear3d(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_trilinear3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_trilinear3d_outf(const at::Tensor & self, at::IntArrayRef output_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); TORCH_API at::Tensor upsample_trilinear3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_trilinear3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_trilinear3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, bool align_corners, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); TORCH_API at::Tensor upsample_nearest1d(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_nearest1d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_nearest1d_outf(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales, at::Tensor & out); TORCH_API at::Tensor upsample_nearest1d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_nearest1d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales=c10::nullopt); TORCH_API at::Tensor & upsample_nearest1d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales, at::Tensor & grad_input); TORCH_API at::Tensor upsample_nearest2d(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest2d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest2d_outf(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); TORCH_API at::Tensor upsample_nearest2d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest2d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest2d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); TORCH_API at::Tensor upsample_nearest3d(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest3d_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest3d_outf(const at::Tensor & self, at::IntArrayRef output_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & out); TORCH_API at::Tensor upsample_nearest3d_backward(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest3d_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d=c10::nullopt, c10::optional scales_h=c10::nullopt, c10::optional scales_w=c10::nullopt); TORCH_API at::Tensor & upsample_nearest3d_backward_outf(const at::Tensor & grad_output, at::IntArrayRef output_size, at::IntArrayRef input_size, c10::optional scales_d, c10::optional scales_h, c10::optional scales_w, at::Tensor & grad_input); TORCH_API at::Tensor sigmoid_backward(const at::Tensor & grad_output, const at::Tensor & output); TORCH_API at::Tensor & sigmoid_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); TORCH_API at::Tensor & sigmoid_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); TORCH_API at::Tensor logit_backward(const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps=c10::nullopt); TORCH_API at::Tensor & logit_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps=c10::nullopt); TORCH_API at::Tensor & logit_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, c10::optional eps, at::Tensor & grad_input); TORCH_API at::Tensor tanh_backward(const at::Tensor & grad_output, const at::Tensor & output); TORCH_API at::Tensor & tanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & output); TORCH_API at::Tensor & tanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input); TORCH_API at::Tensor slow_conv_transpose2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); TORCH_API at::Tensor & slow_conv_transpose2d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); TORCH_API at::Tensor & slow_conv_transpose2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out); TORCH_API ::std::tuple slow_conv_transpose2d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, const at::Tensor & columns, const at::Tensor & ones); TORCH_API ::std::tuple slow_conv_transpose2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, const at::Tensor & columns, const at::Tensor & ones, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); TORCH_API ::std::tuple slow_conv_transpose2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, const at::Tensor & columns, const at::Tensor & ones, ::std::array output_mask); TORCH_API at::Tensor slow_conv_transpose3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); TORCH_API at::Tensor & slow_conv_transpose3d_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, at::IntArrayRef dilation=1); TORCH_API at::Tensor & slow_conv_transpose3d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out); TORCH_API ::std::tuple slow_conv_transpose3d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, const at::Tensor & finput, const at::Tensor & fgrad_input); TORCH_API ::std::tuple slow_conv_transpose3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, const at::Tensor & finput, const at::Tensor & fgrad_input, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); TORCH_API ::std::tuple slow_conv_transpose3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef dilation, const at::Tensor & finput, const at::Tensor & fgrad_input, ::std::array output_mask); TORCH_API ::std::tuple _slow_conv2d_forward(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding); TORCH_API ::std::tuple _slow_conv2d_forward_out(at::Tensor & output, at::Tensor & finput, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding); TORCH_API ::std::tuple _slow_conv2d_forward_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & output, at::Tensor & finput); TORCH_API ::std::tuple _slow_conv2d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, const at::Tensor & finput); TORCH_API ::std::tuple _slow_conv2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, const at::Tensor & finput, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); TORCH_API ::std::tuple _slow_conv2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, const at::Tensor & finput, ::std::array output_mask); TORCH_API at::Tensor _conv_depthwise2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); TORCH_API const at::Tensor & _conv_depthwise2d_out(const at::Tensor & out, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); TORCH_API const at::Tensor & _conv_depthwise2d_outf(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, const at::Tensor & out); TORCH_API ::std::tuple _conv_depthwise2d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); TORCH_API ::std::tuple _conv_depthwise2d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, at::Tensor & grad_input, at::Tensor & grad_weight); TORCH_API ::std::tuple _conv_depthwise2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, ::std::array output_mask); TORCH_API at::Tensor conv_depthwise3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); TORCH_API ::std::tuple conv_depthwise3d_backward_out(at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation); TORCH_API ::std::tuple conv_depthwise3d_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, at::Tensor & grad_input, at::Tensor & grad_weight, at::Tensor & grad_bias); TORCH_API ::std::tuple conv_depthwise3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, ::std::array output_mask); TORCH_API at::Tensor slow_conv_dilated2d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); TORCH_API ::std::tuple slow_conv_dilated2d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, ::std::array output_mask); TORCH_API at::Tensor slow_conv_dilated3d(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1); TORCH_API ::std::tuple slow_conv_dilated3d_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, ::std::array output_mask); TORCH_API at::Tensor col2im(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & col2im_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & col2im_outf(const at::Tensor & self, at::IntArrayRef output_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); TORCH_API at::Tensor col2im_backward(const at::Tensor & grad_output, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & col2im_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & col2im_backward_outf(const at::Tensor & grad_output, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & grad_input); TORCH_API at::Tensor im2col(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & im2col_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & im2col_outf(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out); TORCH_API at::Tensor im2col_backward(const at::Tensor & grad_output, at::IntArrayRef input_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & im2col_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, at::IntArrayRef input_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride); TORCH_API at::Tensor & im2col_backward_outf(const at::Tensor & grad_output, at::IntArrayRef input_size, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & grad_input); TORCH_API void record_stream(at::Tensor & self, at::Stream s); TORCH_API at::Tensor isposinf(const at::Tensor & self); TORCH_API at::Tensor & isposinf_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & isposinf_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor isneginf(const at::Tensor & self); TORCH_API at::Tensor & isneginf_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & isneginf_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor special_entr(const at::Tensor & self); TORCH_API at::Tensor & special_entr_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & special_entr_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor special_ndtri(const at::Tensor & self); TORCH_API at::Tensor & special_ndtri_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & special_ndtri_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor special_erfcx(const at::Tensor & self); TORCH_API at::Tensor & special_erfcx_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & special_erfcx_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor special_xlog1py(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & special_xlog1py_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & special_xlog1py_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor special_zeta(const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & special_zeta_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other); TORCH_API at::Tensor & special_zeta_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out); TORCH_API at::Tensor special_i0e(const at::Tensor & self); TORCH_API at::Tensor & special_i0e_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & special_i0e_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor special_i1(const at::Tensor & self); TORCH_API at::Tensor & special_i1_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & special_i1_outf(const at::Tensor & self, at::Tensor & out); TORCH_API at::Tensor special_i1e(const at::Tensor & self); TORCH_API at::Tensor & special_i1e_out(at::Tensor & out, const at::Tensor & self); TORCH_API at::Tensor & special_i1e_outf(const at::Tensor & self, at::Tensor & out); TORCH_API ::std::tuple linalg_cholesky_ex(const at::Tensor & self, bool upper=false, bool check_errors=false); TORCH_API ::std::tuple linalg_cholesky_ex_out(at::Tensor & L, at::Tensor & info, const at::Tensor & self, bool upper=false, bool check_errors=false); TORCH_API ::std::tuple linalg_cholesky_ex_outf(const at::Tensor & self, bool upper, bool check_errors, at::Tensor & L, at::Tensor & info); TORCH_API ::std::tuple _det_lu_based_helper(const at::Tensor & self); TORCH_API at::Tensor _det_lu_based_helper_backward_helper(const at::Tensor & det_grad, const at::Tensor & det, const at::Tensor & self, const at::Tensor & lu, const at::Tensor & pivs); TORCH_API ::std::tuple linalg_lstsq_out(at::Tensor & solution, at::Tensor & residuals, at::Tensor & rank, at::Tensor & singular_values, const at::Tensor & self, const at::Tensor & b, c10::optional rcond=c10::nullopt, c10::optional driver=c10::nullopt); TORCH_API ::std::tuple linalg_lstsq_outf(const at::Tensor & self, const at::Tensor & b, c10::optional rcond, c10::optional driver, at::Tensor & solution, at::Tensor & residuals, at::Tensor & rank, at::Tensor & singular_values); TORCH_API ::std::tuple linalg_slogdet(const at::Tensor & self); TORCH_API ::std::tuple linalg_slogdet_out(at::Tensor & sign, at::Tensor & logabsdet, const at::Tensor & self); TORCH_API ::std::tuple linalg_slogdet_outf(const at::Tensor & self, at::Tensor & sign, at::Tensor & logabsdet); TORCH_API ::std::tuple linalg_eig(const at::Tensor & self); TORCH_API ::std::tuple linalg_eig_out(at::Tensor & eigenvalues, at::Tensor & eigenvectors, const at::Tensor & self); TORCH_API ::std::tuple linalg_eig_outf(const at::Tensor & self, at::Tensor & eigenvalues, at::Tensor & eigenvectors); TORCH_API ::std::tuple linalg_eigh(const at::Tensor & self, c10::string_view UPLO="L"); TORCH_API ::std::tuple linalg_eigh_out(at::Tensor & eigvals, at::Tensor & eigvecs, const at::Tensor & self, c10::string_view UPLO="L"); TORCH_API ::std::tuple linalg_eigh_outf(const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs); TORCH_API at::Tensor & linalg_eigvalsh_out(at::Tensor & out, const at::Tensor & self, c10::string_view UPLO="L"); TORCH_API at::Tensor & linalg_eigvalsh_outf(const at::Tensor & self, c10::string_view UPLO, at::Tensor & out); TORCH_API at::Tensor linalg_householder_product(const at::Tensor & input, const at::Tensor & tau); TORCH_API at::Tensor & linalg_householder_product_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & tau); TORCH_API at::Tensor & linalg_householder_product_outf(const at::Tensor & input, const at::Tensor & tau, at::Tensor & out); TORCH_API at::Tensor & _linalg_inv_out_helper_(at::Tensor & self, at::Tensor & infos_lu, at::Tensor & infos_getri); TORCH_API at::Tensor linalg_vector_norm(const at::Tensor & self, const at::Scalar & ord=2, c10::optional dim=c10::nullopt, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & linalg_vector_norm_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & ord=2, c10::optional dim=c10::nullopt, bool keepdim=false, c10::optional dtype=c10::nullopt); TORCH_API at::Tensor & linalg_vector_norm_outf(const at::Tensor & self, const at::Scalar & ord, c10::optional dim, bool keepdim, c10::optional dtype, at::Tensor & out); TORCH_API at::Tensor linalg_solve(const at::Tensor & input, const at::Tensor & other); TORCH_API at::Tensor & linalg_solve_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & other); TORCH_API at::Tensor & linalg_solve_outf(const at::Tensor & input, const at::Tensor & other, at::Tensor & out); TORCH_API ::std::tuple _linalg_qr_helper(const at::Tensor & self, c10::string_view mode); TORCH_API at::Tensor segment_reduce(const at::Tensor & data, c10::string_view reduce, const c10::optional & lengths={}, const c10::optional & indices={}, int64_t axis=0, bool unsafe=false, const c10::optional & initial=c10::nullopt); TORCH_API at::Tensor _segment_reduce_backward(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const c10::optional & lengths={}, int64_t axis=0); } // namespace cuda } // namespace at