// This file contains all native_functions that can be registered to
// and the schema string that they should be registered with

Tensor _cast_Byte(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Char(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Char(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Double(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Double(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Float(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Float(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Int(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Int(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Long(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Long(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Short(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Short(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _cast_Half(const Tensor & self, bool non_blocking); // {"schema": "aten::_cast_Half(Tensor self, bool non_blocking=False) -> Tensor", "dispatch": "False", "default": "True"}
void _backward(const Tensor & self, TensorList inputs, const c10::optional<Tensor> & gradient, c10::optional<bool> retain_graph, bool create_graph); // {"schema": "aten::_backward(Tensor self, Tensor[] inputs, Tensor? gradient=None, bool? retain_graph=None, bool create_graph=False) -> ()", "dispatch": "False", "default": "True"}
void set_data(Tensor & self, const Tensor & new_data); // {"schema": "aten::set_data(Tensor(a!) self, Tensor new_data) -> ()", "dispatch": "False", "default": "True"}
Tensor data(const Tensor & self); // {"schema": "aten::data(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
bool is_leaf(const Tensor & self); // {"schema": "aten::is_leaf(Tensor self) -> bool", "dispatch": "False", "default": "True"}
int64_t output_nr(const Tensor & self); // {"schema": "aten::output_nr(Tensor self) -> int", "dispatch": "False", "default": "True"}
int64_t _version(const Tensor & self); // {"schema": "aten::_version(Tensor self) -> int", "dispatch": "False", "default": "True"}
Tensor & requires_grad_(Tensor & self, bool requires_grad); // {"schema": "aten::requires_grad_(Tensor(a!) self, bool requires_grad=True) -> Tensor(a!)", "dispatch": "False", "default": "True"}
void retain_grad(Tensor & self); // {"schema": "aten::retain_grad(Tensor(a!) self) -> ()", "dispatch": "False", "default": "True"}
Tensor _fw_primal(const Tensor & self, int64_t level); // {"schema": "aten::_fw_primal(Tensor(a) self, int level) -> Tensor(a)", "dispatch": "True", "default": "True"}
Tensor _make_dual(const Tensor & primal, const Tensor & tangent, int64_t level); // {"schema": "aten::_make_dual(Tensor(a) primal, Tensor tangent, int level) -> Tensor(a)", "dispatch": "False", "default": "True"}
std::tuple<Tensor,Tensor> _unpack_dual(const Tensor & dual, int64_t level); // {"schema": "aten::_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent)", "dispatch": "False", "default": "True"}
Tensor & rename_(Tensor & self, c10::optional<DimnameList> names); // {"schema": "aten::rename_(Tensor(a!) self, Dimname[]? names) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor rename(const Tensor & self, c10::optional<DimnameList> names); // {"schema": "aten::rename(Tensor(a) self, Dimname[]? names) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor align_to(const Tensor & self, DimnameList names); // {"schema": "aten::align_to(Tensor(a) self, Dimname[] names) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor align_to(const Tensor & self, DimnameList order, int64_t ellipsis_idx); // {"schema": "aten::align_to.ellipsis_idx(Tensor(a) self, Dimname[] order, int ellipsis_idx) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor align_as(const Tensor & self, const Tensor & other); // {"schema": "aten::align_as(Tensor self, Tensor other) -> Tensor", "dispatch": "False", "default": "True"}
std::vector<Tensor> align_tensors(TensorList tensors); // {"schema": "aten::align_tensors(Tensor[] tensors) -> Tensor[]", "dispatch": "False", "default": "True"}
Tensor refine_names(const Tensor & self, DimnameList names); // {"schema": "aten::refine_names(Tensor(a) self, Dimname[] names) -> Tensor(a)", "dispatch": "False", "default": "True"}
bool _use_cudnn_ctc_loss(const Tensor & log_probs, const Tensor & targets, IntArrayRef input_lengths, IntArrayRef target_lengths, int64_t blank); // {"schema": "aten::_use_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank) -> bool", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> _cudnn_ctc_loss(const Tensor & log_probs, const Tensor & targets, IntArrayRef input_lengths, IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity); // {"schema": "aten::_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor)", "dispatch": "True", "default": "False"}
bool _use_cudnn_rnn_flatten_weight(); // {"schema": "aten::_use_cudnn_rnn_flatten_weight() -> bool", "dispatch": "False", "default": "True"}
Tensor _cudnn_rnn_flatten_weight(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); // {"schema": "aten::_cudnn_rnn_flatten_weight(Tensor[] weight_arr, int weight_stride0, int input_size, int mode, int hidden_size, int proj_size, int num_layers, bool batch_first, bool bidirectional) -> Tensor", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor,Tensor,Tensor,Tensor> _cudnn_rnn(const Tensor & input, TensorList weight, int64_t weight_stride0, const c10::optional<Tensor> & weight_buf, const Tensor & hx, const c10::optional<Tensor> & 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, IntArrayRef batch_sizes, const c10::optional<Tensor> & dropout_state); // {"schema": "aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, int hidden_size, int proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor,Tensor,std::vector<Tensor>> _cudnn_rnn_backward(const Tensor & input, TensorList weight, int64_t weight_stride0, const Tensor & weight_buf, const Tensor & hx, const c10::optional<Tensor> & cx, const Tensor & output, const c10::optional<Tensor> & grad_output, const c10::optional<Tensor> & grad_hy, const c10::optional<Tensor> & 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, IntArrayRef batch_sizes, const c10::optional<Tensor> & dropout_state, const Tensor & reserve, std::array<bool,4> output_mask); // {"schema": "aten::_cudnn_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[])", "dispatch": "True", "default": "False"}
Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor", "dispatch": "True", "default": "False"}
int64_t _debug_has_internal_overlap(const Tensor & self); // {"schema": "aten::_debug_has_internal_overlap(Tensor self) -> int", "dispatch": "False", "default": "True"}
std::tuple<Tensor,Tensor> _fused_dropout(const Tensor & self, double p, c10::optional<Generator> generator); // {"schema": "aten::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor)", "dispatch": "True", "default": "False"}
Tensor _masked_scale(const Tensor & self, const Tensor & mask, double scale); // {"schema": "aten::_masked_scale(Tensor self, Tensor mask, float scale) -> Tensor", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> _sobol_engine_draw(const Tensor & quasi, int64_t n, const Tensor & sobolstate, int64_t dimension, int64_t num_generated, c10::optional<ScalarType> dtype); // {"schema": "aten::_sobol_engine_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor)", "dispatch": "False", "default": "True"}
Tensor & _sobol_engine_ff_(Tensor & self, int64_t n, const Tensor & sobolstate, int64_t dimension, int64_t num_generated); // {"schema": "aten::_sobol_engine_ff_(Tensor(a!) self, int n, Tensor sobolstate, int dimension, int num_generated) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & _sobol_engine_scramble_(Tensor & self, const Tensor & ltm, int64_t dimension); // {"schema": "aten::_sobol_engine_scramble_(Tensor(a!) self, Tensor ltm, int dimension) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & _sobol_engine_initialize_state_(Tensor & self, int64_t dimension); // {"schema": "aten::_sobol_engine_initialize_state_(Tensor(a!) self, int dimension) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor _reshape_from_tensor(const Tensor & self, const Tensor & shape); // {"schema": "aten::_reshape_from_tensor(Tensor self, Tensor shape) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _shape_as_tensor(const Tensor & self); // {"schema": "aten::_shape_as_tensor(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor dropout(const Tensor & input, double p, bool train); // {"schema": "aten::dropout(Tensor input, float p, bool train) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & dropout_(Tensor & self, double p, bool train); // {"schema": "aten::dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor feature_dropout(const Tensor & input, double p, bool train); // {"schema": "aten::feature_dropout(Tensor input, float p, bool train) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & feature_dropout_(Tensor & self, double p, bool train); // {"schema": "aten::feature_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor alpha_dropout(const Tensor & input, double p, bool train); // {"schema": "aten::alpha_dropout(Tensor input, float p, bool train) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & alpha_dropout_(Tensor & self, double p, bool train); // {"schema": "aten::alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor feature_alpha_dropout(const Tensor & input, double p, bool train); // {"schema": "aten::feature_alpha_dropout(Tensor input, float p, bool train) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & feature_alpha_dropout_(Tensor & self, double p, bool train); // {"schema": "aten::feature_alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor abs(const Tensor & self); // {"schema": "aten::abs(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & abs_(Tensor & self); // {"schema": "aten::abs_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & abs_out(const Tensor & self, Tensor & out); // {"schema": "aten::abs.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor absolute(const Tensor & self); // {"schema": "aten::absolute(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & absolute_(Tensor & self); // {"schema": "aten::absolute_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & absolute_out(const Tensor & self, Tensor & out); // {"schema": "aten::absolute.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor angle(const Tensor & self); // {"schema": "aten::angle(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & angle_out(const Tensor & self, Tensor & out); // {"schema": "aten::angle.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor view_as_real(const Tensor & self); // {"schema": "aten::view_as_real(Tensor(a) self) -> Tensor(a)", "dispatch": "True", "default": "False"}
Tensor view_as_complex(const Tensor & self); // {"schema": "aten::view_as_complex(Tensor(a) self) -> Tensor(a)", "dispatch": "True", "default": "False"}
Tensor sgn(const Tensor & self); // {"schema": "aten::sgn(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & sgn_(Tensor & self); // {"schema": "aten::sgn_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & sgn_out(const Tensor & self, Tensor & out); // {"schema": "aten::sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor real(const Tensor & self); // {"schema": "aten::real(Tensor(a) self) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor imag(const Tensor & self); // {"schema": "aten::imag(Tensor(a) self) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor conj(const Tensor & self); // {"schema": "aten::conj(Tensor(a) self) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor & conj_out(const Tensor & self, Tensor & out); // {"schema": "aten::conj.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor _conj(const Tensor & self); // {"schema": "aten::_conj(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor acos(const Tensor & self); // {"schema": "aten::acos(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & acos_(Tensor & self); // {"schema": "aten::acos_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & acos_out(const Tensor & self, Tensor & out); // {"schema": "aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor arccos(const Tensor & self); // {"schema": "aten::arccos(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arccos_(Tensor & self); // {"schema": "aten::arccos_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arccos_out(const Tensor & self, Tensor & out); // {"schema": "aten::arccos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor avg_pool1d(const Tensor & self, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, bool ceil_mode, bool count_include_pad); // {"schema": "aten::avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor", "dispatch": "False", "default": "True"}
Tensor adaptive_avg_pool1d(const Tensor & self, IntArrayRef output_size); // {"schema": "aten::adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor", "dispatch": "False", "default": "True"}
std::tuple<Tensor,Tensor> adaptive_max_pool1d(const Tensor & self, IntArrayRef output_size); // {"schema": "aten::adaptive_max_pool1d(Tensor self, int[1] output_size) -> (Tensor, Tensor)", "dispatch": "False", "default": "True"}
Tensor add(const Tensor & self, const Tensor & other, Scalar alpha); // {"schema": "aten::add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & add_(Tensor & self, const Tensor & other, Scalar alpha); // {"schema": "aten::add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & add_out(const Tensor & self, const Tensor & other, Scalar alpha, Tensor & out); // {"schema": "aten::add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor _add_relu(const Tensor & self, const Tensor & other, Scalar alpha); // {"schema": "aten::_add_relu.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & _add_relu_(Tensor & self, const Tensor & other, Scalar alpha); // {"schema": "aten::_add_relu_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & _add_relu_out(const Tensor & self, const Tensor & other, Scalar alpha, Tensor & out); // {"schema": "aten::_add_relu.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor add(const Tensor & self, Scalar other, Scalar alpha); // {"schema": "aten::add.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & add_(Tensor & self, Scalar other, Scalar alpha); // {"schema": "aten::add_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor addmv(const Tensor & self, const Tensor & mat, const Tensor & vec, Scalar beta, Scalar alpha); // {"schema": "aten::addmv(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & addmv_(Tensor & self, const Tensor & mat, const Tensor & vec, Scalar beta, Scalar alpha); // {"schema": "aten::addmv_(Tensor(a!) self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & addmv_out(const Tensor & self, const Tensor & mat, const Tensor & vec, Scalar beta, Scalar alpha, Tensor & out); // {"schema": "aten::addmv.out(Tensor self, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & _addmv_impl_(Tensor & self, const Tensor & self2, const Tensor & mat, const Tensor & vec, Scalar beta, Scalar alpha); // {"schema": "aten::_addmv_impl_(Tensor(a!) self, Tensor self2, Tensor mat, Tensor vec, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor addr(const Tensor & self, const Tensor & vec1, const Tensor & vec2, Scalar beta, Scalar alpha); // {"schema": "aten::addr(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & addr_(Tensor & self, const Tensor & vec1, const Tensor & vec2, Scalar beta, Scalar alpha); // {"schema": "aten::addr_(Tensor(a!) self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & addr_out(const Tensor & self, const Tensor & vec1, const Tensor & vec2, Scalar beta, Scalar alpha, Tensor & out); // {"schema": "aten::addr.out(Tensor self, Tensor vec1, Tensor vec2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor affine_grid_generator(const Tensor & theta, IntArrayRef size, bool align_corners); // {"schema": "aten::affine_grid_generator(Tensor theta, int[] size, bool align_corners) -> Tensor", "dispatch": "True", "default": "True"}
Tensor affine_grid_generator_backward(const Tensor & grad, IntArrayRef size, bool align_corners); // {"schema": "aten::affine_grid_generator_backward(Tensor grad, int[] size, bool align_corners) -> Tensor", "dispatch": "False", "default": "True"}
Tensor all(const Tensor & self, int64_t dim, bool keepdim); // {"schema": "aten::all.dim(Tensor self, int dim, bool keepdim=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & all_out(const Tensor & self, int64_t dim, bool keepdim, Tensor & out); // {"schema": "aten::all.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor all(const Tensor & self, Dimname dim, bool keepdim); // {"schema": "aten::all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & all_out(const Tensor & self, Dimname dim, bool keepdim, Tensor & out); // {"schema": "aten::all.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
bool allclose(const Tensor & self, const Tensor & other, double rtol, double atol, bool equal_nan); // {"schema": "aten::allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool", "dispatch": "False", "default": "True"}
Tensor any(const Tensor & self, int64_t dim, bool keepdim); // {"schema": "aten::any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & any_out(const Tensor & self, int64_t dim, bool keepdim, Tensor & out); // {"schema": "aten::any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor any(const Tensor & self, Dimname dim, bool keepdim); // {"schema": "aten::any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & any_out(const Tensor & self, Dimname dim, bool keepdim, Tensor & out); // {"schema": "aten::any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor arange(Scalar end, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::arange(Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor arange(Scalar start, Scalar end, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor arange(Scalar start, Scalar end, Scalar step, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::arange.start_step(Scalar start, Scalar end, Scalar step, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arange_out(Scalar end, Tensor & out); // {"schema": "aten::arange.out(Scalar end, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arange_out(Scalar start, Scalar end, Scalar step, Tensor & out); // {"schema": "aten::arange.start_out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor _dim_arange(const Tensor & like, int64_t dim); // {"schema": "aten::_dim_arange(Tensor like, int dim) -> Tensor", "dispatch": "False", "default": "True"}
Tensor argmax(const Tensor & self, c10::optional<int64_t> dim, bool keepdim); // {"schema": "aten::argmax(Tensor self, int? dim=None, bool keepdim=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & argmax_out(const Tensor & self, c10::optional<int64_t> dim, bool keepdim, Tensor & out); // {"schema": "aten::argmax.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor argmin(const Tensor & self, c10::optional<int64_t> dim, bool keepdim); // {"schema": "aten::argmin(Tensor self, int? dim=None, bool keepdim=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & argmin_out(const Tensor & self, c10::optional<int64_t> dim, bool keepdim, Tensor & out); // {"schema": "aten::argmin.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor acosh(const Tensor & self); // {"schema": "aten::acosh(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & acosh_(Tensor & self); // {"schema": "aten::acosh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & acosh_out(const Tensor & self, Tensor & out); // {"schema": "aten::acosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor arccosh(const Tensor & self); // {"schema": "aten::arccosh(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arccosh_(Tensor & self); // {"schema": "aten::arccosh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arccosh_out(const Tensor & self, Tensor & out); // {"schema": "aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor asinh(const Tensor & self); // {"schema": "aten::asinh(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & asinh_(Tensor & self); // {"schema": "aten::asinh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & asinh_out(const Tensor & self, Tensor & out); // {"schema": "aten::asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor arcsinh(const Tensor & self); // {"schema": "aten::arcsinh(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arcsinh_(Tensor & self); // {"schema": "aten::arcsinh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arcsinh_out(const Tensor & self, Tensor & out); // {"schema": "aten::arcsinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor atanh(const Tensor & self); // {"schema": "aten::atanh(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & atanh_(Tensor & self); // {"schema": "aten::atanh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & atanh_out(const Tensor & self, Tensor & out); // {"schema": "aten::atanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor arctanh(const Tensor & self); // {"schema": "aten::arctanh(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arctanh_(Tensor & self); // {"schema": "aten::arctanh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arctanh_out(const Tensor & self, Tensor & out); // {"schema": "aten::arctanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor as_strided(const Tensor & self, IntArrayRef size, IntArrayRef stride, c10::optional<int64_t> storage_offset); // {"schema": "aten::as_strided(Tensor(a) self, int[] size, int[] stride, int? storage_offset=None) -> Tensor(a)", "dispatch": "True", "default": "False"}
Tensor & as_strided_(Tensor & self, IntArrayRef size, IntArrayRef stride, c10::optional<int64_t> storage_offset); // {"schema": "aten::as_strided_(Tensor(a!) self, int[] size, int[] stride, int? storage_offset=None) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor asin(const Tensor & self); // {"schema": "aten::asin(Tensor self) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & asin_(Tensor & self); // {"schema": "aten::asin_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & asin_out(const Tensor & self, Tensor & out); // {"schema": "aten::asin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor arcsin(const Tensor & self); // {"schema": "aten::arcsin(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arcsin_(Tensor & self); // {"schema": "aten::arcsin_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arcsin_out(const Tensor & self, Tensor & out); // {"schema": "aten::arcsin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor atan(const Tensor & self); // {"schema": "aten::atan(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & atan_(Tensor & self); // {"schema": "aten::atan_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & atan_out(const Tensor & self, Tensor & out); // {"schema": "aten::atan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor arctan(const Tensor & self); // {"schema": "aten::arctan(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & arctan_(Tensor & self); // {"schema": "aten::arctan_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & arctan_out(const Tensor & self, Tensor & out); // {"schema": "aten::arctan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor atleast_1d(const Tensor & self); // {"schema": "aten::atleast_1d(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
std::vector<Tensor> atleast_1d(TensorList tensors); // {"schema": "aten::atleast_1d.Sequence(Tensor[] tensors) -> Tensor[]", "dispatch": "False", "default": "True"}
Tensor atleast_2d(const Tensor & self); // {"schema": "aten::atleast_2d(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
std::vector<Tensor> atleast_2d(TensorList tensors); // {"schema": "aten::atleast_2d.Sequence(Tensor[] tensors) -> Tensor[]", "dispatch": "False", "default": "True"}
Tensor atleast_3d(const Tensor & self); // {"schema": "aten::atleast_3d(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
std::vector<Tensor> atleast_3d(TensorList tensors); // {"schema": "aten::atleast_3d.Sequence(Tensor[] tensors) -> Tensor[]", "dispatch": "False", "default": "True"}
Tensor baddbmm(const Tensor & self, const Tensor & batch1, const Tensor & batch2, Scalar beta, Scalar alpha); // {"schema": "aten::baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & baddbmm_(Tensor & self, const Tensor & batch1, const Tensor & batch2, Scalar beta, Scalar alpha); // {"schema": "aten::baddbmm_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & _baddbmm_mkl_(Tensor & self, const Tensor & batch1, const Tensor & batch2, Scalar beta, Scalar alpha); // {"schema": "aten::_baddbmm_mkl_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & baddbmm_out(const Tensor & self, const Tensor & batch1, const Tensor & batch2, Scalar beta, Scalar alpha, Tensor & out); // {"schema": "aten::baddbmm.out(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor bartlett_window(int64_t window_length, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::bartlett_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor bartlett_window(int64_t window_length, bool periodic, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::bartlett_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor batch_norm(const Tensor & input, const c10::optional<Tensor> & weight, const c10::optional<Tensor> & bias, const c10::optional<Tensor> & running_mean, const c10::optional<Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled); // {"schema": "aten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor", "dispatch": "False", "default": "True"}
Tensor quantized_batch_norm(const Tensor & input, const c10::optional<Tensor> & weight, const c10::optional<Tensor> & bias, const Tensor & mean, const Tensor & var, double eps, double output_scale, int64_t output_zero_point); // {"schema": "aten::quantized_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor var, float eps, float output_scale, int output_zero_point) -> Tensor", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor,Tensor,Tensor,int64_t> _batch_norm_impl_index(const Tensor & input, const c10::optional<Tensor> & weight, const c10::optional<Tensor> & bias, const c10::optional<Tensor> & running_mean, const c10::optional<Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled); // {"schema": "aten::_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int)", "dispatch": "False", "default": "True"}
std::tuple<Tensor,Tensor,Tensor> _batch_norm_impl_index_backward(int64_t impl_index, const Tensor & input, const Tensor & grad_output, const c10::optional<Tensor> & weight, const c10::optional<Tensor> & running_mean, const c10::optional<Tensor> & running_var, const c10::optional<Tensor> & save_mean, const c10::optional<Tensor> & save_var_transform, bool train, double eps, std::array<bool,3> output_mask, const Tensor & reservedSpace); // {"schema": "aten::_batch_norm_impl_index_backward(int impl_index, Tensor input, Tensor grad_output, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var_transform, bool train, float eps, bool[3] output_mask, Tensor reservedSpace) -> (Tensor, Tensor, Tensor)", "dispatch": "False", "default": "True"}
Tensor bernoulli(const Tensor & self, c10::optional<Generator> generator); // {"schema": "aten::bernoulli(Tensor self, *, Generator? generator=None) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & bernoulli_out(const Tensor & self, c10::optional<Generator> generator, Tensor & out); // {"schema": "aten::bernoulli.out(Tensor self, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & bernoulli_(Tensor & self, const Tensor & p, c10::optional<Generator> generator); // {"schema": "aten::bernoulli_.Tensor(Tensor(a!) self, Tensor p, *, Generator? generator=None) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & bernoulli_(Tensor & self, double p, c10::optional<Generator> generator); // {"schema": "aten::bernoulli_.float(Tensor(a!) self, float p=0.5, *, Generator? generator=None) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor bernoulli(const Tensor & self, double p, c10::optional<Generator> generator); // {"schema": "aten::bernoulli.p(Tensor self, float p, *, Generator? generator=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor bilinear(const Tensor & input1, const Tensor & input2, const Tensor & weight, const c10::optional<Tensor> & bias); // {"schema": "aten::bilinear(Tensor input1, Tensor input2, Tensor weight, Tensor? bias) -> Tensor", "dispatch": "False", "default": "True"}
Tensor binary_cross_entropy(const Tensor & self, const Tensor & target, const c10::optional<Tensor> & weight, int64_t reduction); // {"schema": "aten::binary_cross_entropy(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & binary_cross_entropy_out(const Tensor & self, const Tensor & target, const c10::optional<Tensor> & weight, int64_t reduction, Tensor & out); // {"schema": "aten::binary_cross_entropy.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor binary_cross_entropy_backward(const Tensor & grad_output, const Tensor & self, const Tensor & target, const c10::optional<Tensor> & weight, int64_t reduction); // {"schema": "aten::binary_cross_entropy_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & binary_cross_entropy_backward_out(const Tensor & grad_output, const Tensor & self, const Tensor & target, const c10::optional<Tensor> & weight, int64_t reduction, Tensor & grad_input); // {"schema": "aten::binary_cross_entropy_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor binary_cross_entropy_with_logits(const Tensor & self, const Tensor & target, const c10::optional<Tensor> & weight, const c10::optional<Tensor> & pos_weight, int64_t reduction); // {"schema": "aten::binary_cross_entropy_with_logits(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean) -> Tensor", "dispatch": "True", "default": "True"}
Tensor binary_cross_entropy_with_logits_backward(const Tensor & grad_output, const Tensor & self, const Tensor & target, const c10::optional<Tensor> & weight, const c10::optional<Tensor> & pos_weight, int64_t reduction); // {"schema": "aten::binary_cross_entropy_with_logits_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean) -> Tensor", "dispatch": "False", "default": "True"}
Tensor bincount(const Tensor & self, const c10::optional<Tensor> & weights, int64_t minlength); // {"schema": "aten::bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor", "dispatch": "True", "default": "False"}
Tensor bitwise_not(const Tensor & self); // {"schema": "aten::bitwise_not(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & bitwise_not_(Tensor & self); // {"schema": "aten::bitwise_not_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & bitwise_not_out(const Tensor & self, Tensor & out); // {"schema": "aten::bitwise_not.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor copysign(const Tensor & self, const Tensor & other); // {"schema": "aten::copysign.Tensor(Tensor self, Tensor other) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & copysign_(Tensor & self, const Tensor & other); // {"schema": "aten::copysign_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & copysign_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor copysign(const Tensor & self, Scalar other); // {"schema": "aten::copysign.Scalar(Tensor self, Scalar other) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & copysign_(Tensor & self, Scalar other); // {"schema": "aten::copysign_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor logical_not(const Tensor & self); // {"schema": "aten::logical_not(Tensor self) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & logical_not_(Tensor & self); // {"schema": "aten::logical_not_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & logical_not_out(const Tensor & self, Tensor & out); // {"schema": "aten::logical_not.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor logical_xor(const Tensor & self, const Tensor & other); // {"schema": "aten::logical_xor(Tensor self, Tensor other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & logical_xor_(Tensor & self, const Tensor & other); // {"schema": "aten::logical_xor_(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & logical_xor_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor logical_and(const Tensor & self, const Tensor & other); // {"schema": "aten::logical_and(Tensor self, Tensor other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & logical_and_(Tensor & self, const Tensor & other); // {"schema": "aten::logical_and_(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & logical_and_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor logical_or(const Tensor & self, const Tensor & other); // {"schema": "aten::logical_or(Tensor self, Tensor other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & logical_or_(Tensor & self, const Tensor & other); // {"schema": "aten::logical_or_(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & logical_or_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor blackman_window(int64_t window_length, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::blackman_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor blackman_window(int64_t window_length, bool periodic, c10::optional<ScalarType> dtype, c10::optional<Layout> layout, c10::optional<Device> device, c10::optional<bool> pin_memory); // {"schema": "aten::blackman_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor bmm(const Tensor & self, const Tensor & mat2); // {"schema": "aten::bmm(Tensor self, Tensor mat2) -> Tensor", "dispatch": "True", "default": "False"}
Tensor _bmm(const Tensor & self, const Tensor & mat2, bool deterministic); // {"schema": "aten::_bmm(Tensor self, Tensor mat2, *, bool deterministic=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & bmm_out(const Tensor & self, const Tensor & mat2, Tensor & out); // {"schema": "aten::bmm.out(Tensor self, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & _bmm_out(const Tensor & self, const Tensor & mat2, bool deterministic, Tensor & out); // {"schema": "aten::_bmm.out(Tensor self, Tensor mat2, *, bool deterministic=False, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
std::vector<Tensor> broadcast_tensors(TensorList tensors); // {"schema": "aten::broadcast_tensors(Tensor[] tensors) -> Tensor[]", "dispatch": "False", "default": "True"}
Tensor broadcast_to(const Tensor & self, IntArrayRef size); // {"schema": "aten::broadcast_to(Tensor(a) self, int[] size) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor cat(TensorList tensors, int64_t dim); // {"schema": "aten::cat(Tensor[] tensors, int dim=0) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & cat_out(TensorList tensors, int64_t dim, Tensor & out); // {"schema": "aten::cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor cat(TensorList tensors, Dimname dim); // {"schema": "aten::cat.names(Tensor[] tensors, Dimname dim) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & cat_out(TensorList tensors, Dimname dim, Tensor & out); // {"schema": "aten::cat.names_out(Tensor[] tensors, Dimname dim, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor block_diag(TensorList tensors); // {"schema": "aten::block_diag(Tensor[] tensors) -> Tensor", "dispatch": "False", "default": "True"}
Tensor ceil(const Tensor & self); // {"schema": "aten::ceil(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & ceil_(Tensor & self); // {"schema": "aten::ceil_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & ceil_out(const Tensor & self, Tensor & out); // {"schema": "aten::ceil.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor chain_matmul(TensorList matrices); // {"schema": "aten::chain_matmul(Tensor[] matrices) -> Tensor", "dispatch": "False", "default": "True"}
std::vector<Tensor> unsafe_chunk(const Tensor & self, int64_t chunks, int64_t dim); // {"schema": "aten::unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[]", "dispatch": "False", "default": "True"}
std::vector<Tensor> chunk(const Tensor & self, int64_t chunks, int64_t dim); // {"schema": "aten::chunk(Tensor(a) self, int chunks, int dim=0) -> Tensor(a)[]", "dispatch": "False", "default": "True"}
std::vector<Tensor> tensor_split(const Tensor & self, int64_t sections, int64_t dim); // {"schema": "aten::tensor_split.sections(Tensor(a) self, int sections, int dim=0) -> Tensor(a)[]", "dispatch": "False", "default": "True"}
std::vector<Tensor> tensor_split(const Tensor & self, IntArrayRef indices, int64_t dim); // {"schema": "aten::tensor_split.indices(Tensor(a) self, int[] indices, int dim=0) -> Tensor(a)[]", "dispatch": "False", "default": "True"}
std::vector<Tensor> tensor_split(const Tensor & self, const Tensor & tensor_indices_or_sections, int64_t dim); // {"schema": "aten::tensor_split.tensor_indices_or_sections(Tensor(a) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[]", "dispatch": "False", "default": "True"}
Tensor clamp(const Tensor & self, c10::optional<Scalar> min, c10::optional<Scalar> max); // {"schema": "aten::clamp(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & clamp_(Tensor & self, c10::optional<Scalar> min, c10::optional<Scalar> max); // {"schema": "aten::clamp_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & clamp_out(const Tensor & self, c10::optional<Scalar> min, c10::optional<Scalar> max, Tensor & out); // {"schema": "aten::clamp.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor clamp_max(const Tensor & self, Scalar max); // {"schema": "aten::clamp_max(Tensor self, Scalar max) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & clamp_max_(Tensor & self, Scalar max); // {"schema": "aten::clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & clamp_max_out(const Tensor & self, Scalar max, Tensor & out); // {"schema": "aten::clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor clamp_min(const Tensor & self, Scalar min); // {"schema": "aten::clamp_min(Tensor self, Scalar min) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & clamp_min_(Tensor & self, Scalar min); // {"schema": "aten::clamp_min_(Tensor(a!) self, Scalar min) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & clamp_min_out(const Tensor & self, Scalar min, Tensor & out); // {"schema": "aten::clamp_min.out(Tensor self, Scalar min, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor clip(const Tensor & self, c10::optional<Scalar> min, c10::optional<Scalar> max); // {"schema": "aten::clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & clip_(Tensor & self, c10::optional<Scalar> min, c10::optional<Scalar> max); // {"schema": "aten::clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & clip_out(const Tensor & self, c10::optional<Scalar> min, c10::optional<Scalar> max, Tensor & out); // {"schema": "aten::clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
bool cudnn_is_acceptable(const Tensor & self); // {"schema": "aten::cudnn_is_acceptable(Tensor self) -> bool", "dispatch": "False", "default": "True"}
Tensor complex(const Tensor & real, const Tensor & imag); // {"schema": "aten::complex(Tensor real, Tensor imag) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & complex_out(const Tensor & real, const Tensor & imag, Tensor & out); // {"schema": "aten::complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor polar(const Tensor & abs, const Tensor & angle); // {"schema": "aten::polar(Tensor abs, Tensor angle) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & polar_out(const Tensor & abs, const Tensor & angle, Tensor & out); // {"schema": "aten::polar.out(Tensor abs, Tensor angle, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor constant_pad_nd(const Tensor & self, IntArrayRef pad, Scalar value); // {"schema": "aten::constant_pad_nd(Tensor self, int[] pad, Scalar value=0) -> Tensor", "dispatch": "True", "default": "True"}
Tensor contiguous(const Tensor & self, MemoryFormat memory_format); // {"schema": "aten::contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor convolution(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding, int64_t groups); // {"schema": "aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor", "dispatch": "False", "default": "True"}
Tensor convolution_overrideable(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding, int64_t groups); // {"schema": "aten::convolution_overrideable(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor", "dispatch": "True", "default": "True"}
std::tuple<Tensor,Tensor,Tensor> convolution_backward_overrideable(const Tensor & grad_output, const Tensor & input, const Tensor & weight, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding, int64_t groups, std::array<bool,3> output_mask); // {"schema": "aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias)", "dispatch": "True", "default": "True"}
Tensor _convolution(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32); // {"schema": "aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _convolution(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled); // {"schema": "aten::_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor", "dispatch": "False", "default": "True"}
Tensor _convolution_nogroup(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding); // {"schema": "aten::_convolution_nogroup(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding) -> Tensor", "dispatch": "False", "default": "True"}
std::tuple<Tensor,Tensor,Tensor> _convolution_double_backward(const c10::optional<Tensor> & ggI, const c10::optional<Tensor> & ggW, const c10::optional<Tensor> & ggb, const Tensor & gO, const Tensor & weight, const Tensor & self, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool transposed, IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, std::array<bool,3> output_mask); // {"schema": "aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, bool[3] output_mask) -> (Tensor, Tensor, Tensor)", "dispatch": "False", "default": "True"}
Tensor conv1d(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, int64_t groups); // {"schema": "aten::conv1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] dilation=1, int groups=1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor conv2d(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, int64_t groups); // {"schema": "aten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, int groups=1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor conv3d(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, int64_t groups); // {"schema": "aten::conv3d(Tensor input, Tensor weight, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1, int groups=1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor conv_tbc(const Tensor & self, const Tensor & weight, const Tensor & bias, int64_t pad); // {"schema": "aten::conv_tbc(Tensor self, Tensor weight, Tensor bias, int pad=0) -> Tensor", "dispatch": "True", "default": "True"}
std::tuple<Tensor,Tensor,Tensor> conv_tbc_backward(const Tensor & self, const Tensor & input, const Tensor & weight, const Tensor & bias, int64_t pad); // {"schema": "aten::conv_tbc_backward(Tensor self, Tensor input, Tensor weight, Tensor bias, int pad) -> (Tensor, Tensor, Tensor)", "dispatch": "False", "default": "True"}
Tensor conv_transpose1d(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef output_padding, int64_t groups, IntArrayRef dilation); // {"schema": "aten::conv_transpose1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] output_padding=0, int groups=1, int[1] dilation=1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor conv_transpose2d(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef output_padding, int64_t groups, IntArrayRef dilation); // {"schema": "aten::conv_transpose2d.input(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int groups=1, int[2] dilation=1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor conv_transpose3d(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef output_padding, int64_t groups, IntArrayRef dilation); // {"schema": "aten::conv_transpose3d.input(Tensor input, Tensor weight, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int groups=1, int[3] dilation=1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & copy_(Tensor & self, const Tensor & src, bool non_blocking); // {"schema": "aten::copy_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor _copy_from(const Tensor & self, const Tensor & dst, bool non_blocking); // {"schema": "aten::_copy_from(Tensor self, Tensor dst, bool non_blocking=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cos(const Tensor & self); // {"schema": "aten::cos(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & cos_(Tensor & self); // {"schema": "aten::cos_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & cos_out(const Tensor & self, Tensor & out); // {"schema": "aten::cos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor cosh(const Tensor & self); // {"schema": "aten::cosh(Tensor self) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & cosh_(Tensor & self); // {"schema": "aten::cosh_(Tensor(a!) self) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & cosh_out(const Tensor & self, Tensor & out); // {"schema": "aten::cosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor cosine_embedding_loss(const Tensor & input1, const Tensor & input2, const Tensor & target, double margin, int64_t reduction); // {"schema": "aten::cosine_embedding_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor", "dispatch": "False", "default": "True"}
Tensor count_nonzero(const Tensor & self, IntArrayRef dim); // {"schema": "aten::count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor", "dispatch": "True", "default": "False"}
Tensor count_nonzero(const Tensor & self, c10::optional<int64_t> dim); // {"schema": "aten::count_nonzero(Tensor self, int? dim=None) -> Tensor", "dispatch": "True", "default": "True"}
Tensor cudnn_affine_grid_generator(const Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W); // {"schema": "aten::cudnn_affine_grid_generator(Tensor theta, int N, int C, int H, int W) -> Tensor grid", "dispatch": "True", "default": "False"}
Tensor cudnn_affine_grid_generator_backward(const Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W); // {"schema": "aten::cudnn_affine_grid_generator_backward(Tensor grad, int N, int C, int H, int W) -> Tensor grad_theta", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor,Tensor,Tensor> cudnn_batch_norm(const Tensor & input, const Tensor & weight, const c10::optional<Tensor> & bias, const c10::optional<Tensor> & running_mean, const c10::optional<Tensor> & running_var, bool training, double exponential_average_factor, double epsilon); // {"schema": "aten::cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor)", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor,Tensor> cudnn_batch_norm_backward(const Tensor & input, const Tensor & grad_output, const Tensor & weight, const c10::optional<Tensor> & running_mean, const c10::optional<Tensor> & running_var, const c10::optional<Tensor> & save_mean, const c10::optional<Tensor> & save_var, double epsilon, const Tensor & reserveSpace); // {"schema": "aten::cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor)", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution(const Tensor & self, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); // {"schema": "aten::cudnn_convolution.deprecated(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution(const Tensor & self, const Tensor & weight, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); // {"schema": "aten::cudnn_convolution.deprecated2(Tensor self, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution(const Tensor & self, const Tensor & weight, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); // {"schema": "aten::cudnn_convolution(Tensor self, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_backward_input(IntArrayRef self_size, const Tensor & grad_output, const Tensor & weight, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); // {"schema": "aten::cudnn_convolution_backward_input(int[] self_size, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> cudnn_convolution_backward(const Tensor & self, const Tensor & grad_output, const Tensor & weight, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, std::array<bool,2> output_mask); // {"schema": "aten::cudnn_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32, bool[2] output_mask) -> (Tensor, Tensor)", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_backward_weight(IntArrayRef weight_size, const Tensor & grad_output, const Tensor & self, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); // {"schema": "aten::cudnn_convolution_backward_weight(int[] weight_size, Tensor grad_output, Tensor self, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_transpose(const Tensor & self, const Tensor & weight, const c10::optional<Tensor> & bias, IntArrayRef padding, IntArrayRef output_padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); // {"schema": "aten::cudnn_convolution_transpose.deprecated(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_transpose(const Tensor & self, const Tensor & weight, IntArrayRef padding, IntArrayRef output_padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic); // {"schema": "aten::cudnn_convolution_transpose.deprecated2(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_transpose(const Tensor & self, const Tensor & weight, IntArrayRef padding, IntArrayRef output_padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); // {"schema": "aten::cudnn_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> cudnn_convolution_transpose_backward(const Tensor & self, const Tensor & grad_output, const Tensor & weight, IntArrayRef padding, IntArrayRef output_padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, std::array<bool,2> output_mask); // {"schema": "aten::cudnn_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32, bool[2] output_mask) -> (Tensor, Tensor)", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_transpose_backward_input(const Tensor & grad_output, const Tensor & weight, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); // {"schema": "aten::cudnn_convolution_transpose_backward_input(Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_convolution_transpose_backward_weight(IntArrayRef weight_size, const Tensor & grad_output, const Tensor & self, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32); // {"schema": "aten::cudnn_convolution_transpose_backward_weight(int[] weight_size, Tensor grad_output, Tensor self, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor", "dispatch": "True", "default": "False"}
Tensor cudnn_grid_sampler(const Tensor & self, const Tensor & grid); // {"schema": "aten::cudnn_grid_sampler(Tensor self, Tensor grid) -> Tensor output", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> cudnn_grid_sampler_backward(const Tensor & self, const Tensor & grid, const Tensor & grad_output); // {"schema": "aten::cudnn_grid_sampler_backward(Tensor self, Tensor grid, Tensor grad_output) -> (Tensor grad_self, Tensor grad_grid)", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> cummax(const Tensor & self, int64_t dim); // {"schema": "aten::cummax(Tensor self, int dim) -> (Tensor values, Tensor indices)", "dispatch": "True", "default": "True"}
std::tuple<Tensor &,Tensor &> cummax_out(const Tensor & self, int64_t dim, Tensor & values, Tensor & indices); // {"schema": "aten::cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)", "dispatch": "True", "default": "True"}
std::tuple<Tensor,Tensor> cummax(const Tensor & self, Dimname dim); // {"schema": "aten::cummax.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices)", "dispatch": "False", "default": "True"}
std::tuple<Tensor &,Tensor &> cummax_out(const Tensor & self, Dimname dim, Tensor & values, Tensor & indices); // {"schema": "aten::cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)", "dispatch": "False", "default": "True"}
void _cummax_helper(const Tensor & self, Tensor & values, Tensor & indices, int64_t dim); // {"schema": "aten::_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> ()", "dispatch": "True", "default": "False"}
std::tuple<Tensor,Tensor> cummin(const Tensor & self, int64_t dim); // {"schema": "aten::cummin(Tensor self, int dim) -> (Tensor values, Tensor indices)", "dispatch": "True", "default": "True"}
std::tuple<Tensor &,Tensor &> cummin_out(const Tensor & self, int64_t dim, Tensor & values, Tensor & indices); // {"schema": "aten::cummin.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)", "dispatch": "True", "default": "True"}
std::tuple<Tensor,Tensor> cummin(const Tensor & self, Dimname dim); // {"schema": "aten::cummin.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices)", "dispatch": "False", "default": "True"}
std::tuple<Tensor &,Tensor &> cummin_out(const Tensor & self, Dimname dim, Tensor & values, Tensor & indices); // {"schema": "aten::cummin.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)", "dispatch": "False", "default": "True"}
void _cummin_helper(const Tensor & self, Tensor & values, Tensor & indices, int64_t dim); // {"schema": "aten::_cummin_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> ()", "dispatch": "True", "default": "False"}
Tensor cummaxmin_backward(const Tensor & grad, const Tensor & input, const Tensor & indices, int64_t dim); // {"schema": "aten::cummaxmin_backward(Tensor grad, Tensor input, Tensor indices, int dim) -> Tensor", "dispatch": "False", "default": "True"}
Tensor cumprod(const Tensor & self, int64_t dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumprod(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & cumprod_(Tensor & self, int64_t dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumprod_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & cumprod_out(const Tensor & self, int64_t dim, c10::optional<ScalarType> dtype, Tensor & out); // {"schema": "aten::cumprod.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor cumprod(const Tensor & self, Dimname dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumprod.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & cumprod_(Tensor & self, Dimname dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumprod_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & cumprod_out(const Tensor & self, Dimname dim, c10::optional<ScalarType> dtype, Tensor & out); // {"schema": "aten::cumprod.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor cumprod_backward(const Tensor & grad, const Tensor & input, int64_t dim); // {"schema": "aten::cumprod_backward(Tensor grad, Tensor input, int dim) -> Tensor", "dispatch": "False", "default": "True"}
Tensor cumsum(const Tensor & self, int64_t dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumsum(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & cumsum_(Tensor & self, int64_t dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumsum_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor & cumsum_out(const Tensor & self, int64_t dim, c10::optional<ScalarType> dtype, Tensor & out); // {"schema": "aten::cumsum.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor cumsum(const Tensor & self, Dimname dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & cumsum_(Tensor & self, Dimname dim, c10::optional<ScalarType> dtype); // {"schema": "aten::cumsum_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & cumsum_out(const Tensor & self, Dimname dim, c10::optional<ScalarType> dtype, Tensor & out); // {"schema": "aten::cumsum.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor ctc_loss(const Tensor & log_probs, const Tensor & targets, IntArrayRef input_lengths, IntArrayRef target_lengths, int64_t blank, int64_t reduction, bool zero_infinity); // {"schema": "aten::ctc_loss.IntList(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, int reduction=Mean, bool zero_infinity=False) -> Tensor", "dispatch": "False", "default": "True"}
Tensor ctc_loss(const Tensor & log_probs, const Tensor & targets, const Tensor & input_lengths, const Tensor & target_lengths, int64_t blank, int64_t reduction, bool zero_infinity); // {"schema": "aten::ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, int reduction=Mean, bool zero_infinity=False) -> Tensor", "dispatch": "False", "default": "True"}
std::tuple<Tensor,Tensor> _ctc_loss(const Tensor & log_probs, const Tensor & targets, IntArrayRef input_lengths, IntArrayRef target_lengths, int64_t blank, bool zero_infinity); // {"schema": "aten::_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)", "dispatch": "True", "default": "False"}
Tensor _ctc_loss_backward(const Tensor & grad, const Tensor & log_probs, const Tensor & targets, IntArrayRef input_lengths, IntArrayRef target_lengths, const Tensor & neg_log_likelihood, const Tensor & log_alpha, int64_t blank, bool zero_infinity); // {"schema": "aten::_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor", "dispatch": "True", "default": "False"}
Tensor diag_embed(const Tensor & self, int64_t offset, int64_t dim1, int64_t dim2); // {"schema": "aten::diag_embed(Tensor self, int offset=0, int dim1=-2, int dim2=-1) -> Tensor", "dispatch": "False", "default": "True"}
Tensor diagflat(const Tensor & self, int64_t offset); // {"schema": "aten::diagflat(Tensor self, int offset=0) -> Tensor", "dispatch": "False", "default": "True"}
Tensor diagonal(const Tensor & self, int64_t offset, int64_t dim1, int64_t dim2); // {"schema": "aten::diagonal(Tensor(a) self, int offset=0, int dim1=0, int dim2=1) -> Tensor(a)", "dispatch": "True", "default": "True"}
Tensor diagonal(const Tensor & self, Dimname outdim, Dimname dim1, Dimname dim2, int64_t offset); // {"schema": "aten::diagonal.Dimname(Tensor(a) self, *, Dimname outdim, Dimname dim1, Dimname dim2, int offset=0) -> Tensor(a)", "dispatch": "False", "default": "True"}
Tensor diagonal_backward(const Tensor & grad, IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2); // {"schema": "aten::diagonal_backward(Tensor grad, int[] input_sizes, int offset, int dim1, int dim2) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & fill_diagonal_(Tensor & self, Scalar fill_value, bool wrap); // {"schema": "aten::fill_diagonal_(Tensor(a!) self, Scalar fill_value, bool wrap=False) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor diff(const Tensor & self, int64_t n, int64_t dim, const c10::optional<Tensor> & prepend, const c10::optional<Tensor> & append); // {"schema": "aten::diff(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & diff_out(const Tensor & self, int64_t n, int64_t dim, const c10::optional<Tensor> & prepend, const c10::optional<Tensor> & append, Tensor & out); // {"schema": "aten::diff.out(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor div(const Tensor & self, const Tensor & other); // {"schema": "aten::div.Tensor(Tensor self, Tensor other) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & div_(Tensor & self, const Tensor & other); // {"schema": "aten::div_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & div_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::div.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor div(const Tensor & self, const Tensor & other, std::string rounding_mode); // {"schema": "aten::div.Tensor_mode(Tensor self, Tensor other, *, str rounding_mode) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & div_(Tensor & self, const Tensor & other, std::string rounding_mode); // {"schema": "aten::div_.Tensor_mode(Tensor(a!) self, Tensor other, *, str rounding_mode) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor & div_out(const Tensor & self, const Tensor & other, std::string rounding_mode, Tensor & out); // {"schema": "aten::div.out_mode(Tensor self, Tensor other, *, str rounding_mode, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "False"}
Tensor div(const Tensor & self, Scalar other); // {"schema": "aten::div.Scalar(Tensor self, Scalar other) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & div_(Tensor & self, Scalar other); // {"schema": "aten::div_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor div(const Tensor & self, Scalar other, std::string rounding_mode); // {"schema": "aten::div.Scalar_mode(Tensor self, Scalar other, *, str rounding_mode) -> Tensor", "dispatch": "True", "default": "True"}
Tensor & div_(Tensor & self, Scalar other, std::string rounding_mode); // {"schema": "aten::div_.Scalar_mode(Tensor(a!) self, Scalar other, *, str rounding_mode) -> Tensor(a!)", "dispatch": "True", "default": "True"}
Tensor divide(const Tensor & self, const Tensor & other); // {"schema": "aten::divide.Tensor(Tensor self, Tensor other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & divide_(Tensor & self, const Tensor & other); // {"schema": "aten::divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & divide_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor divide(const Tensor & self, Scalar other); // {"schema": "aten::divide.Scalar(Tensor self, Scalar other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & divide_(Tensor & self, Scalar other); // {"schema": "aten::divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor divide(const Tensor & self, const Tensor & other, std::string rounding_mode); // {"schema": "aten::divide.Tensor_mode(Tensor self, Tensor other, *, str rounding_mode) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & divide_(Tensor & self, const Tensor & other, std::string rounding_mode); // {"schema": "aten::divide_.Tensor_mode(Tensor(a!) self, Tensor other, *, str rounding_mode) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & divide_out(const Tensor & self, const Tensor & other, std::string rounding_mode, Tensor & out); // {"schema": "aten::divide.out_mode(Tensor self, Tensor other, *, str rounding_mode, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor divide(const Tensor & self, Scalar other, std::string rounding_mode); // {"schema": "aten::divide.Scalar_mode(Tensor self, Scalar other, *, str rounding_mode) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & divide_(Tensor & self, Scalar other, std::string rounding_mode); // {"schema": "aten::divide_.Scalar_mode(Tensor(a!) self, Scalar other, *, str rounding_mode) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor true_divide(const Tensor & self, const Tensor & other); // {"schema": "aten::true_divide.Tensor(Tensor self, Tensor other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & true_divide_(Tensor & self, const Tensor & other); // {"schema": "aten::true_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor & true_divide_out(const Tensor & self, const Tensor & other, Tensor & out); // {"schema": "aten::true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor true_divide(const Tensor & self, Scalar other); // {"schema": "aten::true_divide.Scalar(Tensor self, Scalar other) -> Tensor", "dispatch": "False", "default": "True"}
Tensor & true_divide_(Tensor & self, Scalar other); // {"schema": "aten::true_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)", "dispatch": "False", "default": "True"}
Tensor dot(const Tensor & self, const Tensor & tensor); // {"schema": "aten::dot(Tensor self, Tensor tensor) -> Tensor", "dispatch": "True", "default": "False"}
Tensor & dot_out(const Tensor & self, const Tensor & tensor, Tensor & out); // {"schema": "aten::dot.out(Tensor self, Tensor tensor, *, Tensor(a!) out) -> Tensor(a!)", "dispatch": "True", "default": "True"}