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parseable.h
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parseable.h
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#pragma once
// @generated by aten/src/ATen/gen.py from Functions.h
#include <c10/core/Scalar.h>
#include <ATen/Tensor.h>
#include <c10/core/Storage.h>
#include <ATen/core/Generator.h>
#include <c10/util/Deprecated.h>
#include <ATen/NativeFunctions.h>
#include <ATen/DeviceGuard.h>
#include <c10/core/TensorOptions.h>
#include <ATen/core/Reduction.h>
#include <c10/util/Optional.h>
#include <ATen/TensorUtils.h>
#include <ATen/Context.h>
namespace at {
using native::tensor;
static inline std::tuple<at::Tensor,at::Tensor> _efficient_attention_forward(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const c10::optional<at::Tensor> & cu_seqlens_q, const c10::optional<at::Tensor> & cu_seqlens_k, c10::optional<int64_t> max_seqlen_q, bool compute_log_sumexp=false, bool causal=false)
// aten::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor)
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> _efficient_attention_backward(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, bool is_causal=false, bool chunk_grad_outputs=false);
// aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value)
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, int64_t philox_seed, int64_t philox_offset);
// aten::_scaled_dot_product_flash_attention(Tensor query, Tensor key, Tensor value, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False) -> (Tensor ouput, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, int philox_seed, int philox_offset, Tensor debug_attn_mask)
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t,int64_t,int64_t,int64_t,at::Tensor> _scaled_dot_product_flash_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, double dropout_p=0.0, bool is_causal=false, bool return_debug_mask=false)
static inline std::tuple<at::Tensor,at::Tensor> _scaled_dot_product_efficient_attention(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, bool compute_log_sumexp, bool is_causal=false);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_efficient_attention_backward(const at::Tensor & grad_out_, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, bool is_causal=false, bool chunk_grad_outputs=false);
static inline at::Tensor _cast_Byte(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Char(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Double(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Float(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Int(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Long(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Short(const at::Tensor & self, bool non_blocking=false);
static inline at::Tensor _cast_Half(const at::Tensor & self, bool non_blocking=false);
// static inline at::Tensor _make_dual(const at::Tensor & primal, const at::Tensor & tangent, int64_t level);
// static inline std::tuple<at::Tensor,at::Tensor> _unpack_dual(const at::Tensor & dual, int64_t level);
static inline std::vector<at::Tensor> align_tensors(at::TensorList tensors);
// static inline void _assert_async(const at::Tensor & self);
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor> _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);
// static inline bool _use_cudnn_rnn_flatten_weight();
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional<at::Tensor> & weight_buf, const at::Tensor & hx, const c10::optional<at::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, at::IntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,std::vector<at::Tensor>> _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<at::Tensor> & cx, const at::Tensor & output, const c10::optional<at::Tensor> & grad_output, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::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, at::IntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, const at::Tensor & reserve, std::array<bool,4> output_mask);
// static inline at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, at::TensorOptions options);
// static inline at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline int64_t _debug_has_internal_overlap(const at::Tensor & self);
static inline std::tuple<at::Tensor,at::Tensor> _fused_dropout(const at::Tensor & self, double p, c10::optional<at::Generator> generator=c10::nullopt);
static inline at::Tensor _masked_scale(const at::Tensor & self, const at::Tensor & mask, double scale);
static inline std::tuple<at::Tensor,at::Tensor> _sobol_engine_draw(const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, c10::optional<at::ScalarType> dtype);
static inline at::Tensor & _sobol_engine_ff_(at::Tensor & self, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated);
static inline at::Tensor & _sobol_engine_scramble_(at::Tensor & self, const at::Tensor & ltm, int64_t dimension);
static inline at::Tensor & _sobol_engine_initialize_state_(at::Tensor & self, int64_t dimension);
static inline at::Tensor _reshape_from_tensor(const at::Tensor & self, const at::Tensor & shape);
static inline at::Tensor _shape_as_tensor(const at::Tensor & self);
static inline at::Tensor dropout(const at::Tensor & input, double p, bool train);
static inline at::Tensor & dropout_(at::Tensor & self, double p, bool train);
static inline at::Tensor feature_dropout(const at::Tensor & input, double p, bool train);
static inline at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train);
static inline at::Tensor alpha_dropout(const at::Tensor & input, double p, bool train);
static inline at::Tensor & alpha_dropout_(at::Tensor & self, double p, bool train);
static inline at::Tensor feature_alpha_dropout(const at::Tensor & input, double p, bool train);
static inline at::Tensor & feature_alpha_dropout_(at::Tensor & self, double p, bool train);
static inline at::Tensor abs(const at::Tensor & self);
static inline at::Tensor & abs_(at::Tensor & self);
static inline at::Tensor & abs_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & abs_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor absolute(const at::Tensor & self);
static inline at::Tensor & absolute_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & absolute_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor angle(const at::Tensor & self);
static inline at::Tensor & angle_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & angle_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor view_as_real(const at::Tensor & self);
static inline at::Tensor view_as_complex(const at::Tensor & self);
static inline at::Tensor sgn(const at::Tensor & self);
static inline at::Tensor & sgn_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & sgn_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor real(const at::Tensor & self);
static inline at::Tensor imag(const at::Tensor & self);
static inline at::Tensor conj(const at::Tensor & self);
// static inline at::Tensor & conj_out(at::Tensor & out, const at::Tensor & self);
// static inline at::Tensor & conj_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor _conj(const at::Tensor & self);
static inline at::Tensor acos(const at::Tensor & self);
static inline at::Tensor & acos_(at::Tensor & self);
static inline at::Tensor & acos_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & acos_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor arccos(const at::Tensor & self);
static inline at::Tensor & arccos_(at::Tensor & self);
static inline at::Tensor & arccos_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & arccos_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor avg_pool1d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, bool ceil_mode=false, bool count_include_pad=true);
static inline at::Tensor adaptive_avg_pool1d(const at::Tensor & self, at::IntArrayRef output_size);
static inline std::tuple<at::Tensor,at::Tensor> adaptive_max_pool1d(const at::Tensor & self, at::IntArrayRef output_size);
static inline at::Tensor add(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
static inline at::Tensor & add_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
static inline at::Tensor & add_outf(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
static inline at::Tensor _add_relu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
static inline at::Tensor & _add_relu_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
static inline at::Tensor & _add_relu_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
static inline at::Tensor & _add_relu_outf(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
static inline at::Tensor add(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1);
static inline 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);
static inline at::Tensor & addmv_(at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta=1, const at::Scalar & alpha=1);
static inline 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);
static inline 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);
static inline 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);
static inline 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);
static inline 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);
static inline at::Tensor affine_grid_generator(const at::Tensor & theta, at::IntArrayRef size, bool align_corners);
static inline at::Tensor affine_grid_generator_backward(const at::Tensor & grad, at::IntArrayRef size, bool align_corners);
static inline at::Tensor all(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline at::Tensor & all_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out);
// static inline at::Tensor all(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline at::Tensor & all_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline at::Tensor & all_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out);
static inline bool allclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false);
static inline at::Tensor any(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline at::Tensor & any_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out);
// static inline at::Tensor any(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline at::Tensor & any_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline at::Tensor & any_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out);
static inline at::Tensor arange(const at::Scalar & end, at::TensorOptions options={});
// static inline at::Tensor arange(const at::Scalar & end, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, at::TensorOptions options={});
// static inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::TensorOptions options={});
// static inline at::Tensor arange(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & arange_out(at::Tensor & out, const at::Scalar & end);
static inline at::Tensor & arange_outf(const at::Scalar & end, at::Tensor & out);
static inline at::Tensor & arange_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1);
static inline at::Tensor & arange_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out);
static inline at::Tensor _dim_arange(const at::Tensor & like, int64_t dim);
static inline at::Tensor argmax(const at::Tensor & self, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false);
static inline at::Tensor & argmax_out(at::Tensor & out, const at::Tensor & self, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false);
static inline at::Tensor & argmax_outf(const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim, at::Tensor & out);
static inline at::Tensor argmin(const at::Tensor & self, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false);
static inline at::Tensor & argmin_out(at::Tensor & out, const at::Tensor & self, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false);
static inline at::Tensor & argmin_outf(const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim, at::Tensor & out);
static inline at::Tensor acosh(const at::Tensor & self);
static inline at::Tensor & acosh_(at::Tensor & self);
static inline at::Tensor & acosh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & acosh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor arccosh(const at::Tensor & self);
static inline at::Tensor & arccosh_(at::Tensor & self);
static inline at::Tensor & arccosh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & arccosh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor asinh(const at::Tensor & self);
static inline at::Tensor & asinh_(at::Tensor & self);
static inline at::Tensor & asinh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & asinh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor arcsinh(const at::Tensor & self);
static inline at::Tensor & arcsinh_(at::Tensor & self);
static inline at::Tensor & arcsinh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & arcsinh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor atanh(const at::Tensor & self);
static inline at::Tensor & atanh_(at::Tensor & self);
static inline at::Tensor & atanh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & atanh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor arctanh(const at::Tensor & self);
static inline at::Tensor & arctanh_(at::Tensor & self);
static inline at::Tensor & arctanh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & arctanh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor as_strided(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, c10::optional<int64_t> storage_offset=c10::nullopt);
static inline const at::Tensor & as_strided_(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, c10::optional<int64_t> storage_offset=c10::nullopt);
static inline at::Tensor asin(const at::Tensor & self);
static inline at::Tensor & asin_(at::Tensor & self);
static inline at::Tensor & asin_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & asin_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor arcsin(const at::Tensor & self);
static inline at::Tensor & arcsin_(at::Tensor & self);
static inline at::Tensor & arcsin_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & arcsin_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor atan(const at::Tensor & self);
static inline at::Tensor & atan_(at::Tensor & self);
static inline at::Tensor & atan_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & atan_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor arctan(const at::Tensor & self);
static inline at::Tensor & arctan_(at::Tensor & self);
static inline at::Tensor & arctan_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & arctan_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor atleast_1d(const at::Tensor & self);
static inline std::vector<at::Tensor> atleast_1d(at::TensorList tensors);
static inline at::Tensor atleast_2d(const at::Tensor & self);
static inline std::vector<at::Tensor> atleast_2d(at::TensorList tensors);
static inline at::Tensor atleast_3d(const at::Tensor & self);
static inline std::vector<at::Tensor> atleast_3d(at::TensorList tensors);
static inline 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);
// static inline at::Tensor & _baddbmm_mkl_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
static inline 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);
static inline 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);
static inline at::Tensor bartlett_window(int64_t window_length, at::TensorOptions options={});
// static inline at::Tensor bartlett_window(int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor bartlett_window(int64_t window_length, bool periodic, at::TensorOptions options={});
// static inline at::Tensor bartlett_window(int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor batch_norm(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled);
static inline at::Tensor quantized_batch_norm(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & var, double eps, double output_scale, int64_t output_zero_point);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t> _batch_norm_impl_index(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> _batch_norm_impl_index_backward(int64_t impl_index, const at::Tensor & input, const at::Tensor & grad_output, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var_transform, bool train, double eps, std::array<bool,3> output_mask, const at::Tensor & reservedSpace);
static inline at::Tensor bernoulli(const at::Tensor & self, c10::optional<at::Generator> generator=c10::nullopt);
static inline at::Tensor & bernoulli_out(at::Tensor & out, const at::Tensor & self, c10::optional<at::Generator> generator=c10::nullopt);
static inline at::Tensor & bernoulli_outf(const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out);
static inline at::Tensor bernoulli(const at::Tensor & self, double p, c10::optional<at::Generator> generator=c10::nullopt);
static inline at::Tensor bilinear(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const c10::optional<at::Tensor> & bias);
static inline at::Tensor binary_cross_entropy(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor & binary_cross_entropy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor & binary_cross_entropy_outf(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & out);
static inline at::Tensor binary_cross_entropy_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean);
static inline 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<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor & binary_cross_entropy_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & grad_input);
static inline at::Tensor binary_cross_entropy_with_logits(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, const c10::optional<at::Tensor> & pos_weight={}, int64_t reduction=at::Reduction::Mean);
// static inline at::Tensor binary_cross_entropy_with_logits_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, const c10::optional<at::Tensor> & pos_weight={}, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor bincount(const at::Tensor & self, const c10::optional<at::Tensor> & weights={}, int64_t minlength=0);
static inline at::Tensor bitwise_not(const at::Tensor & self);
static inline at::Tensor & bitwise_not_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & bitwise_not_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & copysign_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor copysign(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor copysign(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor & copysign_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor & copysign_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
static inline at::Tensor logical_not(const at::Tensor & self);
static inline at::Tensor & logical_not_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & logical_not_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor logical_xor(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logical_xor_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logical_xor_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor logical_and(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logical_and_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logical_and_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor logical_or(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logical_or_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logical_or_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor blackman_window(int64_t window_length, at::TensorOptions options={});
// static inline at::Tensor blackman_window(int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor blackman_window(int64_t window_length, bool periodic, at::TensorOptions options={});
// static inline at::Tensor blackman_window(int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor bmm(const at::Tensor & self, const at::Tensor & mat2);
// static inline at::Tensor _bmm(const at::Tensor & self, const at::Tensor & mat2, bool deterministic=false);
static inline at::Tensor & bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2);
static inline at::Tensor & bmm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out);
// static inline at::Tensor & _bmm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2, bool deterministic=false);
// static inline at::Tensor & _bmm_outf(const at::Tensor & self, const at::Tensor & mat2, bool deterministic, at::Tensor & out);
static inline std::vector<at::Tensor> broadcast_tensors(at::TensorList tensors);
static inline at::Tensor broadcast_to(const at::Tensor & self, at::IntArrayRef size);
static inline at::Tensor cat(at::TensorList tensors, int64_t dim=0);
static inline at::Tensor & cat_out(at::Tensor & out, at::TensorList tensors, int64_t dim=0);
static inline at::Tensor & cat_outf(at::TensorList tensors, int64_t dim, at::Tensor & out);
// static inline at::Tensor cat(at::TensorList tensors, at::Dimname dim);
// static inline at::Tensor & cat_out(at::Tensor & out, at::TensorList tensors, at::Dimname dim);
// static inline at::Tensor & cat_outf(at::TensorList tensors, at::Dimname dim, at::Tensor & out);
static inline at::Tensor block_diag(at::TensorList tensors);
static inline at::Tensor ceil(const at::Tensor & self);
static inline at::Tensor & ceil_(at::Tensor & self);
static inline at::Tensor & ceil_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & ceil_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor chain_matmul(at::TensorList matrices);
static inline at::Tensor & chain_matmul_out(at::Tensor & out, at::TensorList matrices);
static inline at::Tensor & chain_matmul_outf(at::TensorList matrices, at::Tensor & out);
static inline std::vector<at::Tensor> unsafe_chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0);
static inline std::vector<at::Tensor> chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0);
static inline std::vector<at::Tensor> tensor_split(const at::Tensor & self, int64_t sections, int64_t dim=0);
static inline std::vector<at::Tensor> tensor_split(const at::Tensor & self, at::IntArrayRef indices, int64_t dim=0);
static inline std::vector<at::Tensor> tensor_split(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim=0);
static inline at::Tensor clamp(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max=c10::nullopt);
static inline at::Tensor clamp(const at::Tensor & self, const c10::optional<at::Tensor> & min={}, const c10::optional<at::Tensor> & max={});
static inline at::Tensor & clamp_(at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max=c10::nullopt);
static inline at::Tensor & clamp_(at::Tensor & self, const c10::optional<at::Tensor> & min={}, const c10::optional<at::Tensor> & max={});
static inline at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max=c10::nullopt);
static inline at::Tensor & clamp_outf(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max, at::Tensor & out);
static inline at::Tensor & clamp_out(at::Tensor & out, const at::Tensor & self, const c10::optional<at::Tensor> & min={}, const c10::optional<at::Tensor> & max={});
static inline at::Tensor & clamp_outf(const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max, at::Tensor & out);
static inline at::Tensor clamp_max(const at::Tensor & self, const at::Scalar & max);
static inline at::Tensor clamp_max(const at::Tensor & self, const at::Tensor & max);
static inline at::Tensor & clamp_max_(at::Tensor & self, const at::Scalar & max);
static inline at::Tensor & clamp_max_(at::Tensor & self, const at::Tensor & max);
static inline at::Tensor & clamp_max_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & max);
static inline at::Tensor & clamp_max_outf(const at::Tensor & self, const at::Scalar & max, at::Tensor & out);
static inline at::Tensor & clamp_max_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & max);
static inline at::Tensor & clamp_max_outf(const at::Tensor & self, const at::Tensor & max, at::Tensor & out);
static inline at::Tensor clamp_min(const at::Tensor & self, const at::Scalar & min);
static inline at::Tensor clamp_min(const at::Tensor & self, const at::Tensor & min);
static inline at::Tensor & clamp_min_(at::Tensor & self, const at::Scalar & min);
static inline at::Tensor & clamp_min_(at::Tensor & self, const at::Tensor & min);
static inline at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & min);
static inline at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Scalar & min, at::Tensor & out);
static inline at::Tensor & clamp_min_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & min);
static inline at::Tensor & clamp_min_outf(const at::Tensor & self, const at::Tensor & min, at::Tensor & out);
static inline at::Tensor clip(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max=c10::nullopt);
static inline at::Tensor clip(const at::Tensor & self, const c10::optional<at::Tensor> & min={}, const c10::optional<at::Tensor> & max={});
static inline at::Tensor & clip_(at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max=c10::nullopt);
static inline at::Tensor & clip_(at::Tensor & self, const c10::optional<at::Tensor> & min={}, const c10::optional<at::Tensor> & max={});
static inline at::Tensor & clip_out(at::Tensor & out, const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max=c10::nullopt);
static inline at::Tensor & clip_outf(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max, at::Tensor & out);
static inline at::Tensor & clip_out(at::Tensor & out, const at::Tensor & self, const c10::optional<at::Tensor> & min={}, const c10::optional<at::Tensor> & max={});
static inline at::Tensor & clip_outf(const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max, at::Tensor & out);
static inline bool cudnn_is_acceptable(const at::Tensor & self);
static inline at::Tensor complex(const at::Tensor & real, const at::Tensor & imag);
static inline at::Tensor & complex_out(at::Tensor & out, const at::Tensor & real, const at::Tensor & imag);
static inline at::Tensor & complex_outf(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out);
static inline at::Tensor polar(const at::Tensor & abs, const at::Tensor & angle);
static inline at::Tensor & polar_out(at::Tensor & out, const at::Tensor & abs, const at::Tensor & angle);
static inline at::Tensor & polar_outf(const at::Tensor & abs, const at::Tensor & angle, at::Tensor & out);
static inline at::Tensor constant_pad_nd(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0);
static inline at::Tensor convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups)
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> convolution_backward(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalIntArrayRef bias_sizes, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, std::array<bool,3> output_mask);
// static inline at::Tensor convolution_overrideable(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> convolution_backward_overrideable(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, std::array<bool,3> output_mask);
// static inline at::Tensor _convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32);
// static inline at::Tensor _convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled);
// static inline at::Tensor _convolution_mode(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, std::string padding, at::IntArrayRef dilation, int64_t groups);
// static inline at::Tensor _convolution_nogroup(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> _convolution_double_backward(const c10::optional<at::Tensor> & ggI, const c10::optional<at::Tensor> & ggW, const c10::optional<at::Tensor> & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, std::array<bool,3> output_mask);
static inline at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1);
static inline at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1);
static inline at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1);
static inline at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, std::string padding, at::IntArrayRef dilation=1, int64_t groups=1);
static inline at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, std::string padding, at::IntArrayRef dilation=1, int64_t groups=1);
static inline at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, std::string padding, at::IntArrayRef dilation=1, int64_t groups=1);
static inline at::Tensor conv_tbc(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad=0);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> conv_tbc_backward(const at::Tensor & self, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & bias, int64_t pad);
static inline at::Tensor conv_transpose1d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1);
static inline at::Tensor conv_transpose2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1);
static inline at::Tensor conv_transpose3d(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1);
static inline at::Tensor _copy_from(const at::Tensor & self, const at::Tensor & dst, bool non_blocking=false);
static inline at::Tensor cos(const at::Tensor & self);
static inline at::Tensor & cos_(at::Tensor & self);
static inline at::Tensor & cos_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & cos_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor cosh(const at::Tensor & self);
static inline at::Tensor & cosh_(at::Tensor & self);
static inline at::Tensor & cosh_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & cosh_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor cosine_embedding_loss(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin=0.0, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor count_nonzero(const at::Tensor & self, at::IntArrayRef dim);
static inline at::Tensor count_nonzero(const at::Tensor & self, c10::optional<int64_t> dim=c10::nullopt);
static inline at::Tensor cudnn_affine_grid_generator(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W);
static inline at::Tensor cudnn_affine_grid_generator_backward(const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> cudnn_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double exponential_average_factor, double epsilon);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> cudnn_batch_norm_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, const at::Tensor & reserveSpace);
// static inline at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
// static inline 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);
// static inline 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);
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor> 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<bool,2> output_mask);
// static inline 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);
// static inline at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
// static inline 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);
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor> 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<bool,2> output_mask);
// static inline 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);
// static inline 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);
// static inline at::Tensor cudnn_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups);
// static inline at::Tensor cudnn_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const c10::optional<at::Scalar> & alpha, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups);
static inline at::Tensor cudnn_grid_sampler(const at::Tensor & self, const at::Tensor & grid);
static inline std::tuple<at::Tensor,at::Tensor> cudnn_grid_sampler_backward(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output);
static inline std::tuple<at::Tensor,at::Tensor> cummax(const at::Tensor & self, int64_t dim);
static inline std::tuple<at::Tensor &,at::Tensor &> cummax_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim);
static inline std::tuple<at::Tensor &,at::Tensor &> cummax_outf(const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices);
// static inline std::tuple<at::Tensor,at::Tensor> cummax(const at::Tensor & self, at::Dimname dim);
// static inline std::tuple<at::Tensor &,at::Tensor &> cummax_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim);
// static inline std::tuple<at::Tensor &,at::Tensor &> cummax_outf(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices);
static inline void _cummax_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim);
static inline std::tuple<at::Tensor,at::Tensor> cummin(const at::Tensor & self, int64_t dim);
static inline std::tuple<at::Tensor &,at::Tensor &> cummin_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim);
static inline std::tuple<at::Tensor &,at::Tensor &> cummin_outf(const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices);
// static inline std::tuple<at::Tensor,at::Tensor> cummin(const at::Tensor & self, at::Dimname dim);
// static inline std::tuple<at::Tensor &,at::Tensor &> cummin_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim);
// static inline std::tuple<at::Tensor &,at::Tensor &> cummin_outf(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices);
static inline void _cummin_helper(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim);
static inline at::Tensor cummaxmin_backward(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t dim);
static inline at::Tensor cumprod(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor & cumprod_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor & cumprod_outf(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype, at::Tensor & out);
// static inline at::Tensor cumprod(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor & cumprod_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor & cumprod_outf(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype, at::Tensor & out);
static inline at::Tensor cumprod_backward(const at::Tensor & grad, const at::Tensor & input, int64_t dim, const at::Tensor & output);
static inline at::Tensor cumsum(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor & cumsum_out(at::Tensor & out, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor & cumsum_outf(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype, at::Tensor & out);
// static inline at::Tensor cumsum(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor & cumsum_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor & cumsum_outf(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype, at::Tensor & out);
static inline at::Tensor ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, int64_t reduction=at::Reduction::Mean, bool zero_infinity=false);
static inline at::Tensor ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank=0, int64_t reduction=at::Reduction::Mean, bool zero_infinity=false);
static inline std::tuple<at::Tensor,at::Tensor> _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);
static inline 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);
static inline at::Tensor diag_embed(const at::Tensor & self, int64_t offset=0, int64_t dim1=-2, int64_t dim2=-1);
static inline at::Tensor diagflat(const at::Tensor & self, int64_t offset=0);
static inline at::Tensor diagonal(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1);
// static inline at::Tensor diagonal(const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset=0);
static inline at::Tensor diagonal_backward(const at::Tensor & grad, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2);
static inline at::Tensor diff(const at::Tensor & self, int64_t n=1, int64_t dim=-1, const c10::optional<at::Tensor> & prepend={}, const c10::optional<at::Tensor> & append={});
static inline at::Tensor & diff_out(at::Tensor & out, const at::Tensor & self, int64_t n=1, int64_t dim=-1, const c10::optional<at::Tensor> & prepend={}, const c10::optional<at::Tensor> & append={});
static inline at::Tensor & diff_outf(const at::Tensor & self, int64_t n, int64_t dim, const c10::optional<at::Tensor> & prepend, const c10::optional<at::Tensor> & append, at::Tensor & out);
static inline std::vector<at::Tensor> gradient(const at::Tensor & self, const c10::optional<at::Scalar> & spacing=c10::nullopt, c10::optional<int64_t> dim=c10::nullopt, int64_t edge_order=1);
static inline std::vector<at::Tensor> gradient(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order=1);
static inline std::vector<at::Tensor> gradient(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order=1);
// static inline std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, c10::optional<int64_t> dim=c10::nullopt, int64_t edge_order=1);
// static inline std::vector<at::Tensor> gradient(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order=1);
static inline std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, c10::optional<int64_t> dim=c10::nullopt, int64_t edge_order=1);
static inline std::vector<at::Tensor> gradient(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order=1);
static inline at::Tensor div(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
// static inline at::Tensor div(const at::Tensor & self, const at::Tensor & other, c10::optional<c10::string_view> rounding_mode);
// static inline at::Tensor & div_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, c10::optional<c10::string_view> rounding_mode);
static inline at::Tensor & div_outf(const at::Tensor & self, const at::Tensor & other, c10::optional<c10::string_view> rounding_mode, at::Tensor & out);
static inline at::Tensor div(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor div(const at::Tensor & self, const at::Scalar & other, c10::optional<c10::string_view> rounding_mode);
static inline at::Tensor divide(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor divide(const at::Tensor & self, const at::Scalar & other);
// static inline at::Tensor divide(const at::Tensor & self, const at::Tensor & other, c10::optional<c10::string_view> rounding_mode);
// static inline at::Tensor & divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other, c10::optional<c10::string_view> rounding_mode);
// static inline at::Tensor & divide_outf(const at::Tensor & self, const at::Tensor & other, c10::optional<c10::string_view> rounding_mode, at::Tensor & out);
// static inline at::Tensor divide(const at::Tensor & self, const at::Scalar & other, c10::optional<c10::string_view> rounding_mode);
static inline at::Tensor true_divide(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & true_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & true_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor true_divide(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor dot(const at::Tensor & self, const at::Tensor & tensor);
static inline at::Tensor & dot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & tensor);
static inline at::Tensor & dot_outf(const at::Tensor & self, const at::Tensor & tensor, at::Tensor & out);
static inline at::Tensor vdot(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & vdot_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & vdot_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor einsum(std::string equation, at::TensorList tensors);
static inline at::Tensor embedding(const at::Tensor & weight, const at::Tensor & indices, int64_t padding_idx=-1, bool scale_grad_by_freq=false, bool sparse=false);
static inline at::Tensor embedding_backward(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq, bool sparse);
static inline 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);
static inline at::Tensor & embedding_renorm_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type);
static inline at::Tensor embedding_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _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<at::Tensor> & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
static inline std::tuple<at::Tensor,at::Tensor> _rowwise_prune(const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype);
static inline at::Tensor row_stack(at::TensorList tensors);
static inline at::Tensor & row_stack_out(at::Tensor & out, at::TensorList tensors);
static inline at::Tensor & row_stack_outf(at::TensorList tensors, at::Tensor & out);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> 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<at::Tensor> & per_sample_weights={}, bool include_last_offset=false);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, bool include_last_offset, c10::optional<int64_t> padding_idx);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _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<at::Tensor> & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
static inline at::Tensor _embedding_bag_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, 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, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx=-1);
static inline at::Tensor _embedding_bag_sparse_backward(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx=-1);
static inline 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<at::Tensor> & per_sample_weights, int64_t padding_idx=-1);
static inline 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);
// static inline at::Tensor empty(at::IntArrayRef size, c10::optional<at::DimnameList> names, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor empty(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor empty(at::IntArrayRef size, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor empty(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, at::TensorOptions options={}, double scale=1, int64_t zero_point=0, c10::optional<at::MemoryFormat> memory_format=MemoryFormat::Contiguous);
// static inline at::Tensor _empty_affine_quantized(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, double scale, int64_t zero_point, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=MemoryFormat::Contiguous);
// static inline at::Tensor _empty_per_channel_affine_quantized(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor empty_quantized(at::IntArrayRef size, const at::Tensor & qtensor);
static inline at::Tensor & empty_out(at::Tensor & out, at::IntArrayRef size, c10::optional<at::DimnameList> names=c10::nullopt, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
static inline at::Tensor & empty_outf(at::IntArrayRef size, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out);
static inline at::Tensor empty_like(const at::Tensor & self, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor empty_like(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, at::TensorOptions options={});
// static inline at::Tensor empty_strided(at::IntArrayRef size, at::IntArrayRef stride, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor erf(const at::Tensor & self);
static inline at::Tensor & erf_(at::Tensor & self);
static inline at::Tensor & erf_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & erf_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor erfc(const at::Tensor & self);
static inline at::Tensor & erfc_(at::Tensor & self);
static inline at::Tensor & erfc_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & erfc_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor exp(const at::Tensor & self);
static inline at::Tensor & exp_(at::Tensor & self);
static inline at::Tensor & exp_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & exp_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor exp2(const at::Tensor & self);
static inline at::Tensor & exp2_(at::Tensor & self);
static inline at::Tensor & exp2_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & exp2_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor expm1(const at::Tensor & self);
static inline at::Tensor & expm1_(at::Tensor & self);
static inline at::Tensor & expm1_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & expm1_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor eye(int64_t n, at::TensorOptions options={});
// static inline at::Tensor eye(int64_t n, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor eye(int64_t n, int64_t m, at::TensorOptions options={});
// static inline at::Tensor eye(int64_t n, int64_t m, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & eye_out(at::Tensor & out, int64_t n);
static inline at::Tensor & eye_outf(int64_t n, at::Tensor & out);
static inline at::Tensor & eye_out(at::Tensor & out, int64_t n, int64_t m);
static inline at::Tensor & eye_outf(int64_t n, int64_t m, at::Tensor & out);
static inline at::Tensor flatten(const at::Tensor & self, int64_t start_dim=0, int64_t end_dim=-1);
// static inline at::Tensor flatten(const at::Tensor & self, int64_t start_dim, int64_t end_dim, at::Dimname out_dim);
// static inline at::Tensor flatten(const at::Tensor & self, at::Dimname start_dim, at::Dimname end_dim, at::Dimname out_dim);
// static inline at::Tensor flatten(const at::Tensor & self, at::DimnameList dims, at::Dimname out_dim);
static inline at::Tensor & fill_(at::Tensor & self, const at::Scalar & value);
static inline at::Tensor & fill_(at::Tensor & self, const at::Tensor & value);
static inline at::Tensor floor(const at::Tensor & self);
static inline at::Tensor & floor_(at::Tensor & self);
static inline at::Tensor & floor_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & floor_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor floor_divide(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & floor_divide_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & floor_divide_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor floor_divide(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor frac(const at::Tensor & self);
static inline at::Tensor & frac_(at::Tensor & self);
static inline at::Tensor & frac_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & frac_outf(const at::Tensor & self, at::Tensor & out);
// static inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional<at::DimnameList> names, at::TensorOptions options={});
// static inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, at::TensorOptions options={});
// static inline at::Tensor full(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & full_out(at::Tensor & out, at::IntArrayRef size, const at::Scalar & fill_value);
static inline at::Tensor & full_outf(at::IntArrayRef size, const at::Scalar & fill_value, at::Tensor & out);
static inline at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor full_like(const at::Tensor & self, const at::Scalar & fill_value, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor from_file(std::string filename, c10::optional<bool> shared=c10::nullopt, c10::optional<int64_t> size=0, at::TensorOptions options={});
// static inline at::Tensor from_file(std::string filename, c10::optional<bool> shared, c10::optional<int64_t> size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & gcd_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & gcd_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor gcd(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & gcd_(at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & lcm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & lcm_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor lcm(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & lcm_(at::Tensor & self, const at::Tensor & other);
// static inline at::Tensor grid_sampler(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
// static inline at::Tensor grid_sampler_2d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
// static inline std::tuple<at::Tensor,at::Tensor> 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);
// static inline at::Tensor _grid_sampler_2d_cpu_fallback(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
// static inline std::tuple<at::Tensor,at::Tensor> _grid_sampler_2d_cpu_fallback_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);
// static inline at::Tensor grid_sampler_3d(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners);
// static inline std::tuple<at::Tensor,at::Tensor> 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);
static inline at::Tensor hann_window(int64_t window_length, at::TensorOptions options={});
// static inline at::Tensor hann_window(int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor hann_window(int64_t window_length, bool periodic, at::TensorOptions options={});
// static inline at::Tensor hann_window(int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor hamming_window(int64_t window_length, at::TensorOptions options={});
// static inline at::Tensor hamming_window(int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor hamming_window(int64_t window_length, bool periodic, at::TensorOptions options={});
// static inline at::Tensor hamming_window(int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, at::TensorOptions options={});
// static inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, at::TensorOptions options={});
// static inline at::Tensor hamming_window(int64_t window_length, bool periodic, double alpha, double beta, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor kaiser_window(int64_t window_length, at::TensorOptions options={});
// static inline at::Tensor kaiser_window(int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor kaiser_window(int64_t window_length, bool periodic, at::TensorOptions options={});
// static inline at::Tensor kaiser_window(int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, at::TensorOptions options={});
// static inline at::Tensor kaiser_window(int64_t window_length, bool periodic, double beta, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor hinge_embedding_loss(const at::Tensor & self, const at::Tensor & target, double margin=1.0, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor group_norm(const at::Tensor & input, int64_t num_groups, const c10::optional<at::Tensor> & weight={}, const c10::optional<at::Tensor> & bias={}, double eps=1e-05, bool cudnn_enabled=true);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> native_group_norm(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, int64_t N, int64_t C, int64_t HxW, int64_t group, double eps);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> native_group_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional<at::Tensor> & weight, int64_t N, int64_t C, int64_t HxW, int64_t group, std::array<bool,3> output_mask);
// static inline at::Tensor _fft_r2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided);
// static inline at::Tensor & _fft_r2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided);
// static inline at::Tensor & _fft_r2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool onesided, at::Tensor & out);
static inline at::Tensor _fft_c2r(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size);
static inline at::Tensor & _fft_c2r_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size);
static inline at::Tensor & _fft_c2r_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out);
static inline at::Tensor _fft_c2c(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward);
static inline at::Tensor & _fft_c2c_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward);
static inline at::Tensor & _fft_c2c_outf(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, bool forward, at::Tensor & out);
static inline int64_t _cufft_get_plan_cache_size(int64_t device_index);
static inline int64_t _cufft_get_plan_cache_max_size(int64_t device_index);
static inline void _cufft_set_plan_cache_max_size(int64_t device_index, int64_t max_size);
static inline void _cufft_clear_plan_cache(int64_t device_index);
static inline at::Tensor index(const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices);
static inline at::Tensor index_copy(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source);
static inline at::Tensor & index_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source);
// static inline at::Tensor index_copy(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source);
static inline at::Tensor & index_put_(at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate=false);
static inline at::Tensor index_put(const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate=false);
static inline at::Tensor & _index_put_impl_(at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate=false, bool unsafe=false);
static inline at::Tensor instance_norm(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool use_input_stats, double momentum, double eps, bool cudnn_enabled);
static inline at::Tensor inverse(const at::Tensor & self);
static inline at::Tensor & inverse_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & inverse_outf(const at::Tensor & self, at::Tensor & out);
// static inline at::Tensor _inverse_helper(const at::Tensor & self);
static inline at::Tensor isclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false);
static inline at::Tensor isnan(const at::Tensor & self);
static inline bool is_distributed(const at::Tensor & self);
static inline bool __dispatch_is_floating_point(const at::Tensor & self);
static inline bool __dispatch_is_complex(const at::Tensor & self);
static inline at::Tensor isreal(const at::Tensor & self);
static inline bool is_nonzero(const at::Tensor & self);
static inline bool is_same_size(const at::Tensor & self, const at::Tensor & other);
static inline bool __dispatch_is_signed(const at::Tensor & self);
static inline at::Tensor kl_div(const at::Tensor & self, const at::Tensor & target, int64_t reduction=at::Reduction::Mean, bool log_target=false);
// static inline 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);
static inline at::Tensor kron(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & kron_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & kron_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline std::tuple<at::Tensor,at::Tensor> kthvalue(const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> kthvalue_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, int64_t dim=-1, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> kthvalue_outf(const at::Tensor & self, int64_t k, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
// static inline std::tuple<at::Tensor,at::Tensor> kthvalue(const at::Tensor & self, int64_t k, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> kthvalue_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t k, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> kthvalue_outf(const at::Tensor & self, int64_t k, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
static inline at::Tensor layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const c10::optional<at::Tensor> & weight={}, const c10::optional<at::Tensor> & bias={}, double eps=1e-05, bool cudnn_enable=true);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> native_layer_norm(const at::Tensor & input, at::IntArrayRef normalized_shape, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, double eps);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> 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<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, std::array<bool,3> output_mask);
static inline at::Tensor nan_to_num(const at::Tensor & self, c10::optional<double> nan=c10::nullopt, c10::optional<double> posinf=c10::nullopt, c10::optional<double> neginf=c10::nullopt);
static inline at::Tensor & nan_to_num_(at::Tensor & self, c10::optional<double> nan=c10::nullopt, c10::optional<double> posinf=c10::nullopt, c10::optional<double> neginf=c10::nullopt);
static inline at::Tensor & nan_to_num_out(at::Tensor & out, const at::Tensor & self, c10::optional<double> nan=c10::nullopt, c10::optional<double> posinf=c10::nullopt, c10::optional<double> neginf=c10::nullopt);
static inline at::Tensor & nan_to_num_outf(const at::Tensor & self, c10::optional<double> nan, c10::optional<double> posinf, c10::optional<double> neginf, at::Tensor & out);
static inline at::Tensor linear(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={});
// static inline at::Tensor mkldnn_linear(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias={});
// static inline at::Tensor mkldnn_linear_backward_input(at::IntArrayRef input_size, const at::Tensor & grad_output, const at::Tensor & weight);
// static inline std::tuple<at::Tensor,at::Tensor> mkldnn_linear_backward_weights(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> mkldnn_linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, std::array<bool,3> output_mask);
static inline at::Tensor fbgemm_linear_int8_weight_fp32_activation(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
static inline at::Tensor fbgemm_linear_int8_weight(const at::Tensor & input, const at::Tensor & weight, const at::Tensor & packed, const at::Tensor & col_offsets, const at::Scalar & weight_scale, const at::Scalar & weight_zero_point, const at::Tensor & bias);
static inline std::tuple<at::Tensor,at::Tensor,double,int64_t> fbgemm_linear_quantize_weight(const at::Tensor & input);
static inline at::Tensor fbgemm_pack_gemm_matrix_fp16(const at::Tensor & input);
static inline at::Tensor fbgemm_linear_fp16_weight_fp32_activation(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
static inline at::Tensor fbgemm_linear_fp16_weight(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias);
static inline at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input);
static inline at::Tensor fbgemm_pack_quantized_matrix(const at::Tensor & input, int64_t K, int64_t N);
static inline at::Tensor ldexp(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & ldexp_(at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & ldexp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & ldexp_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor linspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, at::TensorOptions options={});
static inline at::Tensor linspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor linspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, c10::optional<at::ScalarType> dtype={}, c10::optional<at::Layout> layout={}, c10::optional<at::Device> device={}, c10::optional<bool> pin_memory={});
static inline at::Tensor & linspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps);
static inline at::Tensor & linspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, at::Tensor & out);
static inline at::Tensor log(const at::Tensor & self);
static inline at::Tensor & log_(at::Tensor & self);
static inline at::Tensor & log_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & log_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor log10(const at::Tensor & self);
static inline at::Tensor & log10_(at::Tensor & self);
static inline at::Tensor & log10_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & log10_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor log1p(const at::Tensor & self);
static inline at::Tensor & log1p_(at::Tensor & self);
static inline at::Tensor & log1p_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & log1p_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor log2(const at::Tensor & self);
static inline at::Tensor & log2_(at::Tensor & self);
static inline at::Tensor & log2_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & log2_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor & logaddexp_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logaddexp_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor logaddexp(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logaddexp2_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & logaddexp2_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor logaddexp2(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor xlogy(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor xlogy(const at::Scalar & self, const at::Tensor & other);
static inline at::Tensor xlogy(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor & xlogy_(at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & xlogy_(at::Tensor & self, const at::Scalar & other);
static inline at::Tensor & xlogy_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & xlogy_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor & xlogy_out(at::Tensor & out, const at::Scalar & self, const at::Tensor & other);
static inline at::Tensor & xlogy_outf(const at::Scalar & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor & xlogy_out(at::Tensor & out, const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor & xlogy_outf(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
static inline at::Tensor logdet(const at::Tensor & self);
static inline at::Tensor logspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0, c10::optional<at::ScalarType> dtype={}, c10::optional<at::Layout> layout={}, c10::optional<at::Device> device={}, c10::optional<bool> pin_memory={});
// static inline at::Tensor logspace(const at::Scalar & start, const at::Scalar & end, c10::optional<int64_t> steps, double base, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0);
static inline at::Tensor & logspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out);
static inline at::Tensor log_softmax(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor log_softmax(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor _log_softmax(const at::Tensor & self, int64_t dim, bool half_to_float);
static inline at::Tensor _log_softmax_backward_data(const at::Tensor & grad_output, const at::Tensor & output, int64_t dim, at::ScalarType input_dtype);
static inline at::Tensor _logcumsumexp(const at::Tensor & self, int64_t dim);
static inline at::Tensor & _logcumsumexp_out(at::Tensor & out, const at::Tensor & self, int64_t dim);
static inline at::Tensor & _logcumsumexp_outf(const at::Tensor & self, int64_t dim, at::Tensor & out);
static inline at::Tensor logcumsumexp(const at::Tensor & self, int64_t dim);
static inline at::Tensor & logcumsumexp_out(at::Tensor & out, const at::Tensor & self, int64_t dim);
static inline at::Tensor & logcumsumexp_outf(const at::Tensor & self, int64_t dim, at::Tensor & out);
// static inline at::Tensor logcumsumexp(const at::Tensor & self, at::Dimname dim);
// static inline at::Tensor & logcumsumexp_out(at::Tensor & out, const at::Tensor & self, at::Dimname dim);
// static inline at::Tensor & logcumsumexp_outf(const at::Tensor & self, at::Dimname dim, at::Tensor & out);
static inline at::Tensor logsumexp(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false);
static inline at::Tensor & logsumexp_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false);
static inline at::Tensor & logsumexp_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
// static inline at::Tensor logsumexp(const at::Tensor & self, at::DimnameList dim, bool keepdim=false);
// static inline at::Tensor & logsumexp_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool keepdim=false);
// static inline at::Tensor & logsumexp_outf(const at::Tensor & self, at::DimnameList dim, bool keepdim, at::Tensor & out);
static inline at::Tensor margin_ranking_loss(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin=0.0, int64_t reduction=at::Reduction::Mean);
static inline at::Tensor matmul(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & matmul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & matmul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
// static inline at::Tensor matrix_rank(const at::Tensor & self, double tol, bool symmetric=false);
// static inline at::Tensor matrix_rank(const at::Tensor & self, bool symmetric=false);
static inline at::Tensor matrix_power(const at::Tensor & self, int64_t n);
static inline at::Tensor & matrix_power_out(at::Tensor & out, const at::Tensor & self, int64_t n);
static inline at::Tensor & matrix_power_outf(const at::Tensor & self, int64_t n, at::Tensor & out);
static inline at::Tensor matrix_exp(const at::Tensor & self);
static inline at::Tensor matrix_exp_backward(const at::Tensor & self, const at::Tensor & grad);
static inline std::tuple<at::Tensor,at::Tensor> _aminmax(const at::Tensor & self);
static inline std::tuple<at::Tensor,at::Tensor> _aminmax(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline at::Tensor _compute_linear_combination(const at::Tensor & input, const at::Tensor & coefficients);
static inline at::Tensor & _compute_linear_combination_out(at::Tensor & out, const at::Tensor & input, const at::Tensor & coefficients);
static inline at::Tensor & _compute_linear_combination_outf(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out);
static inline std::tuple<at::Tensor,at::Tensor> max(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> max_out(at::Tensor & max, at::Tensor & max_values, const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> max_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values);
// static inline std::tuple<at::Tensor,at::Tensor> max(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> max_out(at::Tensor & max, at::Tensor & max_values, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> max_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & max, at::Tensor & max_values);
static inline at::Tensor value_selecting_reduction_backward(const at::Tensor & grad, int64_t dim, const at::Tensor & indices, at::IntArrayRef sizes, bool keepdim);
static inline at::Tensor amax(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false);
static inline at::Tensor & amax_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false);
static inline at::Tensor & amax_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
static inline std::tuple<at::Tensor,at::Tensor> max_pool1d_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);
static inline at::Tensor max_pool1d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
static inline at::Tensor max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
// static inline at::Tensor mkldnn_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
// static inline at::Tensor mkldnn_max_pool2d_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
// static inline at::Tensor mkldnn_max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
// static inline at::Tensor mkldnn_max_pool3d_backward(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
static inline at::Tensor quantized_max_pool1d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
static inline at::Tensor quantized_max_pool2d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
static inline at::Tensor max_pool3d(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride={}, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, bool ceil_mode=false);
static inline at::Tensor mean(const at::Tensor & self, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor mean(const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim, bool keepdim=false, c10::optional<at::ScalarType> dtype=c10::nullopt);
static inline at::Tensor & mean_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out);
// static inline at::Tensor mean(const at::Tensor & self, at::DimnameList dim, bool keepdim=false, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor & mean_out(at::Tensor & out, const at::Tensor & self, at::DimnameList dim, bool keepdim=false, c10::optional<at::ScalarType> dtype=c10::nullopt);
// static inline at::Tensor & mean_outf(const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out);
static inline at::Tensor median(const at::Tensor & self);
static inline std::tuple<at::Tensor,at::Tensor> median(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> median_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> median_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
// static inline std::tuple<at::Tensor,at::Tensor> median(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> median_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> median_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
static inline at::Tensor nanmedian(const at::Tensor & self);
static inline std::tuple<at::Tensor,at::Tensor> nanmedian(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> nanmedian_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
// static inline std::tuple<at::Tensor,at::Tensor> nanmedian(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> nanmedian_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> nanmedian_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
static inline std::tuple<at::Tensor,at::Tensor> min(const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> min_out(at::Tensor & min, at::Tensor & min_indices, const at::Tensor & self, int64_t dim, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> min_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices);
// static inline std::tuple<at::Tensor,at::Tensor> min(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> min_out(at::Tensor & min, at::Tensor & min_indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> min_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & min, at::Tensor & min_indices);
static inline at::Tensor amin(const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false);
static inline at::Tensor & amin_out(at::Tensor & out, const at::Tensor & self, at::IntArrayRef dim={}, bool keepdim=false);
static inline at::Tensor & amin_outf(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out);
// static inline at::Tensor mkldnn_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups);
// static inline at::Tensor mkldnn_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 bias_defined);
// static inline std::tuple<at::Tensor,at::Tensor> mkldnn_convolution_backward_weights(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 bias_defined);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> mkldnn_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, std::array<bool,3> output_mask);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double exponential_average_factor, double epsilon);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_batch_norm_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon);
// static inline at::Tensor miopen_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> 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<bool,3> output_mask);
// static inline at::Tensor miopen_convolution_backward_bias(const at::Tensor & grad_output);
// static inline 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);
// static inline at::Tensor miopen_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> 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<bool,3> output_mask);
// static inline 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);
// static inline 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);
// static inline at::Tensor miopen_depthwise_convolution(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> 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<bool,3> output_mask);
// static inline 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);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> miopen_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional<at::Tensor> & 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<at::Tensor> & dropout_state);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,std::vector<at::Tensor>> 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<at::Tensor> & cx, const at::Tensor & output, const c10::optional<at::Tensor> & grad_output, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & 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<at::Tensor> & dropout_state, const at::Tensor & reserve, std::array<bool,4> output_mask);
static inline at::Tensor mm(const at::Tensor & self, const at::Tensor & mat2);
static inline at::Tensor & mm_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & mat2);
static inline at::Tensor & mm_outf(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out);
static inline at::Tensor _sparse_mm(const at::Tensor & sparse, const at::Tensor & dense);
static inline at::Tensor _sparse_sparse_matmul(const at::Tensor & self, const at::Tensor & other);
// static inline at::Tensor _sparse_mask_helper(const at::Tensor & t, const at::Tensor & mask_indices);
static inline std::tuple<at::Tensor,at::Tensor> mode(const at::Tensor & self, int64_t dim=-1, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, int64_t dim=-1, bool keepdim=false);
static inline std::tuple<at::Tensor &,at::Tensor &> mode_outf(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
// static inline std::tuple<at::Tensor,at::Tensor> mode(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> mode_out(at::Tensor & values, at::Tensor & indices, const at::Tensor & self, at::Dimname dim, bool keepdim=false);
// static inline std::tuple<at::Tensor &,at::Tensor &> mode_outf(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices);
static inline at::Tensor mul(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & mul_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & mul_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor mul(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor multiply(const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & multiply_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & other);
static inline at::Tensor & multiply_outf(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
static inline at::Tensor multiply(const at::Tensor & self, const at::Scalar & other);
static inline at::Tensor mv(const at::Tensor & self, const at::Tensor & vec);
static inline at::Tensor & mv_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & vec);
static inline at::Tensor & mv_outf(const at::Tensor & self, const at::Tensor & vec, at::Tensor & out);
static inline at::Tensor mvlgamma(const at::Tensor & self, int64_t p);
static inline at::Tensor narrow_copy(const at::Tensor & self, int64_t dim, int64_t start, int64_t length);
static inline at::Tensor & narrow_copy_out(at::Tensor & out, const at::Tensor & self, int64_t dim, int64_t start, int64_t length);
static inline at::Tensor & narrow_copy_outf(const at::Tensor & self, int64_t dim, int64_t start, int64_t length, at::Tensor & out);
static inline at::Tensor narrow(const at::Tensor & self, int64_t dim, int64_t start, int64_t length);
static inline at::Tensor narrow(const at::Tensor & self, int64_t dim, const at::Tensor & start, int64_t length);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> native_batch_norm(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps);
static inline std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> native_batch_norm_out(at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps);
static inline std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> native_batch_norm_outf(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd);
static inline std::tuple<at::Tensor,at::Tensor> batch_norm_stats(const at::Tensor & input, double eps);
static inline at::Tensor batch_norm_elemt(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps);
static inline at::Tensor & batch_norm_elemt_out(at::Tensor & out, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps);
static inline at::Tensor & batch_norm_elemt_outf(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out);
static inline std::tuple<at::Tensor,at::Tensor> batch_norm_gather_stats(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum, double eps, int64_t count);
static inline std::tuple<at::Tensor,at::Tensor> batch_norm_gather_stats_with_counts(const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum, double eps, const at::Tensor & counts);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> native_batch_norm_backward(const at::Tensor & grad_out, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_invstd, bool train, double eps, std::array<bool,3> output_mask);
static inline std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> batch_norm_backward_reduce(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & weight, bool input_g, bool weight_g, bool bias_g);
static inline 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<at::Tensor> & weight, const at::Tensor & mean_dy, const at::Tensor & mean_dy_xmu, const at::Tensor & count);
static inline std::tuple<at::Tensor,at::Tensor> batch_norm_update_stats(const at::Tensor & input, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum);
static inline bool is_vulkan_available();
static inline bool _nnpack_available();
// static inline at::Tensor _nnpack_spatial_convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef padding, at::IntArrayRef stride=1);
// static inline std::tuple<at::Tensor,at::Tensor,at::Tensor> _nnpack_spatial_convolution_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, std::array<bool,3> output_mask);
// static inline at::Tensor _nnpack_spatial_convolution_backward_input(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding);
// static inline at::Tensor _nnpack_spatial_convolution_backward_weight(const at::Tensor & input, at::IntArrayRef weightsize, const at::Tensor & grad_output, at::IntArrayRef padding);
// static inline at::Tensor ones(at::IntArrayRef size, c10::optional<at::DimnameList> names, at::TensorOptions options={});
// static inline at::Tensor ones(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor ones(at::IntArrayRef size, at::TensorOptions options={});
// static inline at::Tensor ones(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & ones_out(at::Tensor & out, at::IntArrayRef size);
static inline at::Tensor & ones_outf(at::IntArrayRef size, at::Tensor & out);
static inline at::Tensor ones_like(const at::Tensor & self, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor ones_like(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor pairwise_distance(const at::Tensor & x1, const at::Tensor & x2, double p=2, double eps=1e-06, bool keepdim=false);
static inline at::Tensor cdist(const at::Tensor & x1, const at::Tensor & x2, double p=2, c10::optional<int64_t> compute_mode=c10::nullopt);
static inline at::Tensor _euclidean_dist(const at::Tensor & x1, const at::Tensor & x2);
static inline at::Tensor _cdist_forward(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional<int64_t> compute_mode);
static inline at::Tensor _cdist_backward(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist);
static inline at::Tensor pdist(const at::Tensor & self, double p=2);
static inline at::Tensor _pdist_forward(const at::Tensor & self, double p=2);
static inline at::Tensor _pdist_backward(const at::Tensor & grad, const at::Tensor & self, double p, const at::Tensor & pdist);
static inline at::Tensor cosine_similarity(const at::Tensor & x1, const at::Tensor & x2, int64_t dim=1, double eps=1e-08);
static inline at::Tensor permute(const at::Tensor & self, at::IntArrayRef dims);
static inline at::Tensor movedim(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination);
static inline at::Tensor movedim(const at::Tensor & self, int64_t source, int64_t destination);
static inline at::Tensor moveaxis(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination);
static inline at::Tensor moveaxis(const at::Tensor & self, int64_t source, int64_t destination);
static inline at::Tensor pixel_shuffle(const at::Tensor & self, int64_t upscale_factor);
static inline at::Tensor pixel_unshuffle(const at::Tensor & self, int64_t downscale_factor);
static inline at::Tensor channel_shuffle(const at::Tensor & self, int64_t groups);
static inline at::Tensor pinverse(const at::Tensor & self, double rcond=1e-15);
static inline at::Tensor poisson_nll_loss(const at::Tensor & input, const at::Tensor & target, bool log_input, bool full, double eps, int64_t reduction);
static inline at::Tensor rad2deg(const at::Tensor & self);
static inline at::Tensor & rad2deg_(at::Tensor & self);
static inline at::Tensor & rad2deg_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & rad2deg_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor deg2rad(const at::Tensor & self);
static inline at::Tensor & deg2rad_(at::Tensor & self);
static inline at::Tensor & deg2rad_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & deg2rad_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor scalar_tensor(const at::Scalar & s, at::TensorOptions options={});
// static inline at::Tensor scalar_tensor(const at::Scalar & s, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::DimnameList> names, at::TensorOptions options={});
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, at::TensorOptions options={});
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor rand(at::IntArrayRef size, at::TensorOptions options={});
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::Generator> generator, at::TensorOptions options={});
// static inline at::Tensor rand(at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size);
static inline at::Tensor & rand_outf(at::IntArrayRef size, at::Tensor & out);
static inline at::Tensor & rand_out(at::Tensor & out, at::IntArrayRef size, c10::optional<at::Generator> generator);
static inline at::Tensor & rand_outf(at::IntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out);
static inline at::Tensor rand_like(const at::Tensor & self, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor rand_like(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor randint(int64_t high, at::IntArrayRef size, at::TensorOptions options={});
// static inline at::Tensor randint(int64_t high, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor randint(int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator, at::TensorOptions options={});
// static inline at::Tensor randint(int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, at::TensorOptions options={});
// static inline at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator, at::TensorOptions options={});
// static inline at::Tensor randint(int64_t low, int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size);
static inline at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, at::Tensor & out);
static inline at::Tensor & randint_out(at::Tensor & out, int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator);
static inline at::Tensor & randint_outf(int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out);
static inline at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size);
static inline at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, at::Tensor & out);
static inline at::Tensor & randint_out(at::Tensor & out, int64_t low, int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator);
static inline at::Tensor & randint_outf(int64_t low, int64_t high, at::IntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out);
static inline at::Tensor randint_like(const at::Tensor & self, int64_t high, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor randint_like(const at::Tensor & self, int64_t high, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor randint_like(const at::Tensor & self, int64_t low, int64_t high, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor randn(at::IntArrayRef size, at::TensorOptions options={});
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::Generator> generator, at::TensorOptions options={});
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::DimnameList> names, at::TensorOptions options={});
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, at::TensorOptions options={});
// static inline at::Tensor randn(at::IntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size);
static inline at::Tensor & randn_outf(at::IntArrayRef size, at::Tensor & out);
static inline at::Tensor & randn_out(at::Tensor & out, at::IntArrayRef size, c10::optional<at::Generator> generator);
static inline at::Tensor & randn_outf(at::IntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out);
static inline at::Tensor randn_like(const at::Tensor & self, at::TensorOptions options={}, c10::optional<at::MemoryFormat> memory_format=c10::nullopt);
// static inline at::Tensor randn_like(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format);
static inline at::Tensor randperm(int64_t n, at::TensorOptions options=at::kLong);
// static inline at::Tensor randperm(int64_t n, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor randperm(int64_t n, c10::optional<at::Generator> generator, at::TensorOptions options=at::kLong);
// static inline at::Tensor randperm(int64_t n, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & randperm_out(at::Tensor & out, int64_t n);
static inline at::Tensor & randperm_outf(int64_t n, at::Tensor & out);
static inline at::Tensor & randperm_out(at::Tensor & out, int64_t n, c10::optional<at::Generator> generator);
static inline at::Tensor & randperm_outf(int64_t n, c10::optional<at::Generator> generator, at::Tensor & out);
static inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1, at::TensorOptions options={});
// static inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, at::TensorOptions options={});
// static inline at::Tensor range(const at::Scalar & start, const at::Scalar & end, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory);
static inline at::Tensor & range_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step=1);
static inline at::Tensor & range_outf(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out);
static inline at::Tensor ravel(const at::Tensor & self);
static inline at::Tensor reciprocal(const at::Tensor & self);
static inline at::Tensor & reciprocal_(at::Tensor & self);
static inline at::Tensor & reciprocal_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & reciprocal_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor neg(const at::Tensor & self);
static inline at::Tensor & neg_(at::Tensor & self);
static inline at::Tensor & neg_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & neg_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor negative(const at::Tensor & self);
static inline at::Tensor & negative_(at::Tensor & self);
static inline at::Tensor & negative_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & negative_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor repeat_interleave(const at::Tensor & repeats);
static inline at::Tensor repeat_interleave(const at::Tensor & self, const at::Tensor & repeats, c10::optional<int64_t> dim=c10::nullopt);
static inline at::Tensor repeat_interleave(const at::Tensor & self, int64_t repeats, c10::optional<int64_t> dim=c10::nullopt);
static inline at::Tensor reshape(const at::Tensor & self, at::IntArrayRef shape);
// static inline at::Tensor _mkldnn_reshape(const at::Tensor & self, at::IntArrayRef shape);
static inline at::Tensor round(const at::Tensor & self);
static inline at::Tensor & round_(at::Tensor & self);
static inline at::Tensor & round_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & round_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor rrelu(const at::Tensor & self, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional<at::Generator> generator=c10::nullopt);
static inline at::Tensor & rrelu_(at::Tensor & self, const at::Scalar & lower=0.125, const at::Scalar & upper=0.3333333333333333, bool training=false, c10::optional<at::Generator> generator=c10::nullopt);
static inline at::Tensor relu(const at::Tensor & self);
static inline at::Tensor & relu_(at::Tensor & self);
static inline at::Tensor relu6(const at::Tensor & self);
static inline at::Tensor & relu6_(at::Tensor & self);
static inline at::Tensor prelu(const at::Tensor & self, const at::Tensor & weight);
// static inline std::tuple<at::Tensor,at::Tensor> prelu_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight);
static inline at::Tensor gelu(const at::Tensor & self);
static inline at::Tensor gelu_backward(const at::Tensor & grad, const at::Tensor & self);
static inline at::Tensor infinitely_differentiable_gelu_backward(const at::Tensor & grad, const at::Tensor & self);
static inline at::Tensor hardshrink(const at::Tensor & self, const at::Scalar & lambd=0.5);
static inline at::Tensor hardshrink_backward(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd);
static inline at::Tensor rsqrt(const at::Tensor & self);
static inline at::Tensor & rsqrt_(at::Tensor & self);
static inline at::Tensor & rsqrt_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & rsqrt_outf(const at::Tensor & self, at::Tensor & out);
// static inline at::Tensor select(const at::Tensor & self, at::Dimname dim, int64_t index);
static inline at::Tensor select(const at::Tensor & self, int64_t dim, int64_t index);
static inline at::Tensor select_backward(const at::Tensor & grad, at::IntArrayRef input_sizes, int64_t dim, int64_t index);
static inline at::Tensor selu(const at::Tensor & self);
static inline at::Tensor & selu_(at::Tensor & self);
static inline at::Tensor celu(const at::Tensor & self, const at::Scalar & alpha=1.0);
static inline at::Tensor & celu_(at::Tensor & self, const at::Scalar & alpha=1.0);
static inline at::Tensor silu(const at::Tensor & self);
static inline at::Tensor & silu_(at::Tensor & self);
static inline at::Tensor & silu_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & silu_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor silu_backward(const at::Tensor & grad_output, const at::Tensor & self);
static inline at::Tensor mish(const at::Tensor & self);
static inline at::Tensor & mish_(at::Tensor & self);
static inline at::Tensor & mish_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & mish_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor mish_backward(const at::Tensor & grad_output, const at::Tensor & self);
static inline at::Tensor sigmoid(const at::Tensor & self);
static inline at::Tensor & sigmoid_(at::Tensor & self);
static inline at::Tensor & sigmoid_out(at::Tensor & out, const at::Tensor & self);
static inline at::Tensor & sigmoid_outf(const at::Tensor & self, at::Tensor & out);
static inline at::Tensor logit(const at::Tensor & self, c10::optional<double> eps=c10::nullopt);
static inline at::Tensor & logit_(at::Tensor & self, c10::optional<double> eps=c10::nullopt);
static inline at::Tensor & logit_out(at::Tensor & out, const at::Tensor & self, c10::optional<double> eps=c10::nullopt);
static inline at::Tensor & logit_outf(const at::Tensor & self, c10::optional<double> eps, at::Tensor & out);
static inline at::Tensor sin(const at::Tensor & self);
static inline at::Tensor & sin_(at::Tensor & self);