/usr/local/lib64/python3.6/site-packages/torch/include/ATen
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/ATen/NativeFunctions.h (354651B)
#pragma once
// @generated by tools/codegen/gen.py from NativeFunctions.h
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
namespace c10 {
class Scalar;
}
namespace at {
struct Generator;
class Tensor;
struct Type;
} // namespace at
namespace at {
namespace native {
TORCH_API at::Tensor _cast_Byte(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Char(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Double(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Float(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Int(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Long(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Short(const at::Tensor & self, bool non_blocking=false);
TORCH_API at::Tensor _cast_Half(const at::Tensor & self, bool non_blocking=false);
TORCH_API void _backward(const at::Tensor & self, at::TensorList inputs, const c10::optional & gradient={}, c10::optional retain_graph=c10::nullopt, bool create_graph=false);
TORCH_API void set_data(at::Tensor & self, const at::Tensor & new_data);
TORCH_API at::Tensor data(const at::Tensor & self);
TORCH_API bool is_leaf(const at::Tensor & self);
TORCH_API int64_t output_nr(const at::Tensor & self);
TORCH_API int64_t _version(const at::Tensor & self);
TORCH_API at::Tensor & requires_grad_(at::Tensor & self, bool requires_grad=true);
TORCH_API void retain_grad(at::Tensor & self);
TORCH_API bool retains_grad(const at::Tensor & self);
TORCH_API at::Tensor _fw_primal(const at::Tensor & self, int64_t level);
TORCH_API at::Tensor _make_dual(const at::Tensor & primal, const at::Tensor & tangent, int64_t level);
TORCH_API ::std::tuple _unpack_dual(const at::Tensor & dual, int64_t level);
TORCH_API at::Tensor & rename_(at::Tensor & self, c10::optional names);
TORCH_API at::Tensor rename(const at::Tensor & self, c10::optional names);
TORCH_API at::Tensor align_to(const at::Tensor & self, at::DimnameList names);
TORCH_API at::Tensor align_to(const at::Tensor & self, at::DimnameList order, int64_t ellipsis_idx);
TORCH_API at::Tensor align_as(const at::Tensor & self, const at::Tensor & other);
TORCH_API ::std::vector align_tensors(at::TensorList tensors);
TORCH_API void _assert_async_cpu(const at::Tensor & self);
TORCH_API void _assert_async_cuda(const at::Tensor & self);
TORCH_API at::Tensor refine_names(const at::Tensor & self, at::DimnameList names);
TORCH_API bool _use_cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank);
TORCH_API ::std::tuple _cudnn_ctc_loss(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity);
TORCH_API bool _use_cudnn_rnn_flatten_weight();
TORCH_API at::Tensor _cudnn_rnn_flatten_weight(at::TensorList weight_arr, int64_t weight_stride0, int64_t input_size, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, bool bidirectional);
TORCH_API ::std::tuple _cudnn_rnn(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional & weight_buf, const at::Tensor & hx, const c10::optional & cx, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state);
TORCH_API ::std::tuple> _cudnn_rnn_backward(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional & cx, const at::Tensor & output, const c10::optional & grad_output, const c10::optional & grad_hy, const c10::optional & grad_cy, int64_t mode, int64_t hidden_size, int64_t proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional & dropout_state, const at::Tensor & reserve, ::std::array output_mask);
TORCH_API at::Tensor _cudnn_init_dropout_state(double dropout, bool train, int64_t dropout_seed, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API int64_t _debug_has_internal_overlap(const at::Tensor & self);
TORCH_API ::std::tuple fused_dropout_cuda(const at::Tensor & self, double p, c10::optional generator=c10::nullopt);
TORCH_API at::Tensor masked_scale_cuda(const at::Tensor & self, const at::Tensor & mask, double scale);
TORCH_API ::std::tuple _sobol_engine_draw(const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, c10::optional dtype);
TORCH_API at::Tensor & _sobol_engine_ff_(at::Tensor & self, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated);
TORCH_API at::Tensor & _sobol_engine_scramble_(at::Tensor & self, const at::Tensor & ltm, int64_t dimension);
TORCH_API at::Tensor & _sobol_engine_initialize_state_(at::Tensor & self, int64_t dimension);
TORCH_API at::Tensor _reshape_from_tensor(const at::Tensor & self, const at::Tensor & shape);
TORCH_API at::Tensor _shape_as_tensor(const at::Tensor & self);
TORCH_API at::Tensor dropout(const at::Tensor & input, double p, bool train);
TORCH_API at::Tensor & dropout_(at::Tensor & self, double p, bool train);
TORCH_API at::Tensor feature_dropout(const at::Tensor & input, double p, bool train);
TORCH_API at::Tensor & feature_dropout_(at::Tensor & self, double p, bool train);
TORCH_API at::Tensor alpha_dropout(const at::Tensor & input, double p, bool train);
TORCH_API at::Tensor & alpha_dropout_(at::Tensor & self, double p, bool train);
TORCH_API at::Tensor feature_alpha_dropout(const at::Tensor & input, double p, bool train);
TORCH_API at::Tensor & feature_alpha_dropout_(at::Tensor & self, double p, bool train);
TORCH_API at::Tensor abs(const at::Tensor & self);
TORCH_API at::Tensor & abs_(at::Tensor & self);
TORCH_API at::Tensor & abs_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor absolute(const at::Tensor & self);
TORCH_API at::Tensor & absolute_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & absolute_(at::Tensor & self);
TORCH_API at::Tensor angle(const at::Tensor & self);
TORCH_API at::Tensor & angle_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor view_as_real(const at::Tensor & self);
TORCH_API at::Tensor view_as_complex(const at::Tensor & self);
struct TORCH_API structured_sgn_out : public at::meta::structured_sgn {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor real(const at::Tensor & self);
TORCH_API at::Tensor imag(const at::Tensor & self);
TORCH_API at::Tensor _conj(const at::Tensor & self);
TORCH_API at::Tensor conj(const at::Tensor & self);
TORCH_API at::Tensor _conj_physical(const at::Tensor & self);
TORCH_API at::Tensor conj_physical(const at::Tensor & self);
TORCH_API at::Tensor & conj_physical_(at::Tensor & self);
TORCH_API at::Tensor & conj_physical_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & conj_physical_out_sparse(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor resolve_conj(const at::Tensor & self);
TORCH_API at::Tensor resolve_neg(const at::Tensor & self);
TORCH_API at::Tensor _neg_view(const at::Tensor & self);
struct TORCH_API structured_acos_out : public at::meta::structured_acos {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor arccos(const at::Tensor & self);
TORCH_API at::Tensor & arccos_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & arccos_(at::Tensor & self);
TORCH_API 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);
TORCH_API at::Tensor adaptive_avg_pool1d(const at::Tensor & self, at::IntArrayRef output_size);
TORCH_API ::std::tuple adaptive_max_pool1d(const at::Tensor & self, at::IntArrayRef output_size);
struct TORCH_API structured_add_out : public at::meta::structured_add_Tensor {
void impl(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, const at::Tensor & out);
};
TORCH_API at::Tensor add_sparse(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_out_sparse_cpu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & add_sparse_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_out_sparse_cuda(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor add_sparse_csr(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_out_sparse_csr_cpu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & add_sparse_csr_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_out_sparse_csr_cuda(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor mkldnn_add(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & mkldnn_add_out(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & mkldnn_add_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor add_relu(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_relu_out(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & add_relu_(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor add_relu(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_relu_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor add(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1);
TORCH_API at::Tensor & add_(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha=1);
struct TORCH_API structured_addmv_out_cpu : public at::meta::structured_addmv {
void impl(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, const at::Tensor & out);
};
struct TORCH_API structured_addmv_out_cuda : public at::meta::structured_addmv {
void impl(const at::Tensor & self, const at::Tensor & mat, const at::Tensor & vec, const at::Scalar & beta, const at::Scalar & alpha, const at::Tensor & out);
};
TORCH_API at::Tensor math_addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor & math_addr_out(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & addr_(at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor addr(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor & addr_out(const at::Tensor & self, const at::Tensor & vec1, const at::Tensor & vec2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor affine_grid_generator(const at::Tensor & theta, at::IntArrayRef size, bool align_corners);
TORCH_API at::Tensor affine_grid_generator_backward(const at::Tensor & grad, at::IntArrayRef size, bool align_corners);
struct TORCH_API structured_all_out : public at::meta::structured_all_dim {
void impl(const at::Tensor & self, int64_t dim, bool keepdim, const at::Tensor & out);
};
TORCH_API at::Tensor all(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
TORCH_API at::Tensor & all_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out);
TORCH_API bool allclose(const at::Tensor & self, const at::Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false);
struct TORCH_API structured_any_out : public at::meta::structured_any_dim {
void impl(const at::Tensor & self, int64_t dim, bool keepdim, const at::Tensor & out);
};
TORCH_API at::Tensor any(const at::Tensor & self, at::Dimname dim, bool keepdim=false);
TORCH_API at::Tensor & any_out(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out);
TORCH_API at::Tensor arange(const at::Scalar & end, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor arange(const at::Scalar & start, const at::Scalar & end, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor arange(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor & arange_out(const at::Scalar & end, at::Tensor & out);
TORCH_API at::Tensor & arange_cpu_out(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out);
TORCH_API at::Tensor & arange_cuda_out(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out);
TORCH_API at::Tensor _dim_arange(const at::Tensor & like, int64_t dim);
struct TORCH_API structured_argmax_out : public at::meta::structured_argmax {
void impl(const at::Tensor & self, c10::optional dim, bool keepdim, const at::Tensor & out);
};
struct TORCH_API structured_argmin_out : public at::meta::structured_argmin {
void impl(const at::Tensor & self, c10::optional dim, bool keepdim, const at::Tensor & out);
};
struct TORCH_API structured_acosh_out : public at::meta::structured_acosh {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor arccosh(const at::Tensor & self);
TORCH_API at::Tensor & arccosh_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & arccosh_(at::Tensor & self);
struct TORCH_API structured_asinh_out : public at::meta::structured_asinh {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor arcsinh(const at::Tensor & self);
TORCH_API at::Tensor & arcsinh_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & arcsinh_(at::Tensor & self);
struct TORCH_API structured_atanh_out : public at::meta::structured_atanh {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor arctanh(const at::Tensor & self);
TORCH_API at::Tensor & arctanh_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & arctanh_(at::Tensor & self);
TORCH_API at::Tensor as_strided_tensorimpl(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, c10::optional storage_offset=c10::nullopt);
TORCH_API at::Tensor as_strided_qtensorimpl(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, c10::optional storage_offset=c10::nullopt);
TORCH_API const at::Tensor & as_strided_(const at::Tensor & self, at::IntArrayRef size, at::IntArrayRef stride, c10::optional storage_offset=c10::nullopt);
struct TORCH_API structured_asin_out : public at::meta::structured_asin {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor asin_sparse(const at::Tensor & self);
TORCH_API at::Tensor & asin_out_sparse(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & asin_sparse_(at::Tensor & self);
TORCH_API at::Tensor arcsin(const at::Tensor & self);
TORCH_API at::Tensor & arcsin_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & arcsin_(at::Tensor & self);
struct TORCH_API structured_atan_out : public at::meta::structured_atan {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor arctan(const at::Tensor & self);
TORCH_API at::Tensor & arctan_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor & arctan_(at::Tensor & self);
TORCH_API at::Tensor atleast_1d(const at::Tensor & self);
TORCH_API ::std::vector atleast_1d(at::TensorList tensors);
TORCH_API at::Tensor atleast_2d(const at::Tensor & self);
TORCH_API ::std::vector atleast_2d(at::TensorList tensors);
TORCH_API at::Tensor atleast_3d(const at::Tensor & self);
TORCH_API ::std::vector atleast_3d(at::TensorList tensors);
TORCH_API at::Tensor baddbmm_cpu(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor & baddbmm_out_cpu(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & baddbmm__cpu(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor baddbmm_cuda(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor & baddbmm_out_cuda(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out);
TORCH_API at::Tensor & baddbmm__cuda(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor & _baddbmm_mkl_(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta=1, const at::Scalar & alpha=1);
TORCH_API at::Tensor bartlett_window(int64_t window_length, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor bartlett_window(int64_t window_length, bool periodic, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor batch_norm(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps, bool cudnn_enabled);
TORCH_API at::Tensor quantized_batch_norm(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const at::Tensor & mean, const at::Tensor & var, double eps, double output_scale, int64_t output_zero_point);
TORCH_API ::std::tuple _batch_norm_impl_index(const at::Tensor & input, const c10::optional & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double momentum, double eps, bool cudnn_enabled);
TORCH_API ::std::tuple _batch_norm_impl_index_backward(int64_t impl_index, const at::Tensor & input, const at::Tensor & grad_output, const c10::optional & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_var_transform, bool train, double eps, ::std::array output_mask, const at::Tensor & reservedSpace);
TORCH_API at::Tensor bernoulli(const at::Tensor & self, c10::optional generator=c10::nullopt);
TORCH_API at::Tensor & bernoulli_out(const at::Tensor & self, c10::optional generator, at::Tensor & out);
TORCH_API at::Tensor & bernoulli_(at::Tensor & self, const at::Tensor & p, c10::optional generator=c10::nullopt);
TORCH_API at::Tensor & bernoulli_(at::Tensor & self, double p=0.5, c10::optional generator=c10::nullopt);
TORCH_API at::Tensor bernoulli(const at::Tensor & self, double p, c10::optional generator=c10::nullopt);
TORCH_API at::Tensor bilinear(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const c10::optional & bias);
TORCH_API at::Tensor binary_cross_entropy_cpu(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean);
TORCH_API at::Tensor & binary_cross_entropy_out_cpu(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, at::Tensor & out);
TORCH_API at::Tensor binary_cross_entropy_cuda(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean);
TORCH_API at::Tensor & binary_cross_entropy_out_cuda(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, at::Tensor & out);
TORCH_API at::Tensor binary_cross_entropy_backward_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean);
TORCH_API at::Tensor & binary_cross_entropy_backward_out_cpu(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, at::Tensor & grad_input);
TORCH_API at::Tensor binary_cross_entropy_backward_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, int64_t reduction=at::Reduction::Mean);
TORCH_API at::Tensor & binary_cross_entropy_backward_out_cuda(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight, int64_t reduction, at::Tensor & grad_input);
TORCH_API at::Tensor binary_cross_entropy_with_logits(const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, const c10::optional & pos_weight={}, int64_t reduction=at::Reduction::Mean);
TORCH_API at::Tensor binary_cross_entropy_with_logits_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional & weight={}, const c10::optional & pos_weight={}, int64_t reduction=at::Reduction::Mean);
TORCH_API at::Tensor _bincount_cpu(const at::Tensor & self, const c10::optional & weights={}, int64_t minlength=0);
TORCH_API at::Tensor _bincount_cuda(const at::Tensor & self, const c10::optional & weights={}, int64_t minlength=0);
struct TORCH_API structured_bitwise_not_out : public at::meta::structured_bitwise_not {
void impl(const at::Tensor & self, const at::Tensor & out);
};
struct TORCH_API structured_copysign_out : public at::meta::structured_copysign_Tensor {
void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
};
TORCH_API at::Tensor copysign(const at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor & copysign_out(const at::Tensor & self, const at::Scalar & other, at::Tensor & out);
TORCH_API at::Tensor & copysign_(at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor logical_not(const at::Tensor & self);
TORCH_API at::Tensor & logical_not_(at::Tensor & self);
TORCH_API at::Tensor & logical_not_out(const at::Tensor & self, at::Tensor & out);
TORCH_API at::Tensor logical_xor(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & logical_xor_(at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & logical_xor_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor logical_and(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & logical_and_(at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & logical_and_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor logical_or(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & logical_or_(at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & logical_or_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor blackman_window(int64_t window_length, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor blackman_window(int64_t window_length, bool periodic, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional pin_memory={});
TORCH_API at::Tensor bmm_cpu(const at::Tensor & self, const at::Tensor & mat2);
TORCH_API at::Tensor & bmm_out_cpu(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out);
TORCH_API at::Tensor bmm_cuda(const at::Tensor & self, const at::Tensor & mat2);
TORCH_API at::Tensor & bmm_out_cuda(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out);
TORCH_API at::Tensor bmm_sparse_cpu(const at::Tensor & self, const at::Tensor & mat2);
TORCH_API at::Tensor & bmm_out_sparse_cpu(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out);
TORCH_API at::Tensor bmm_sparse_cuda(const at::Tensor & self, const at::Tensor & mat2);
TORCH_API at::Tensor & bmm_out_sparse_cuda(const at::Tensor & self, const at::Tensor & mat2, at::Tensor & out);
TORCH_API ::std::vector broadcast_tensors(at::TensorList tensors);
TORCH_API at::Tensor broadcast_to(const at::Tensor & self, at::IntArrayRef size);
TORCH_API at::Tensor cat(at::TensorList tensors, int64_t dim=0);
TORCH_API at::Tensor & cat_out(at::TensorList tensors, int64_t dim, at::Tensor & out);
TORCH_API at::Tensor cat(at::TensorList tensors, at::Dimname dim);
TORCH_API at::Tensor & cat_out(at::TensorList tensors, at::Dimname dim, at::Tensor & out);
TORCH_API at::Tensor concat(at::TensorList tensors, int64_t dim=0);
TORCH_API at::Tensor & concat_out(at::TensorList tensors, int64_t dim, at::Tensor & out);
TORCH_API at::Tensor concat(at::TensorList tensors, at::Dimname dim);
TORCH_API at::Tensor & concat_out(at::TensorList tensors, at::Dimname dim, at::Tensor & out);
TORCH_API at::Tensor block_diag(at::TensorList tensors);
TORCH_API at::Tensor ceil(const at::Tensor & self);
TORCH_API at::Tensor & ceil_(at::Tensor & self);
struct TORCH_API structured_ceil_out : public at::meta::structured_ceil {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API at::Tensor chain_matmul(at::TensorList matrices);
TORCH_API at::Tensor & chain_matmul_out(at::TensorList matrices, at::Tensor & out);
TORCH_API ::std::vector unsafe_chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0);
TORCH_API ::std::vector chunk(const at::Tensor & self, int64_t chunks, int64_t dim=0);
TORCH_API ::std::vector tensor_split(const at::Tensor & self, int64_t sections, int64_t dim=0);
TORCH_API ::std::vector tensor_split(const at::Tensor & self, at::IntArrayRef indices, int64_t dim=0);
TORCH_API ::std::vector tensor_split(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim=0);
TORCH_API at::Tensor & clamp_(at::Tensor & self, const c10::optional & min=c10::nullopt, const c10::optional & max=c10::nullopt);
struct TORCH_API structured_clamp_out : public at::meta::structured_clamp {
void impl(const at::Tensor & self, at::OptionalScalarRef min, at::OptionalScalarRef max, const at::Tensor & out);
};
TORCH_API at::Tensor clamp_quantized_cpu(const at::Tensor & self, const c10::optional & min=c10::nullopt, const c10::optional & max=c10::nullopt);
TORCH_API at::Tensor & clamp_(at::Tensor & self, const c10::optional & min={}, const c10::optional & max={});
TORCH_API at::Tensor clamp(const at::Tensor & self, const c10::optional & min={}, const c10::optional & max={});
TORCH_API at::Tensor & clamp_out(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out);
TORCH_API at::Tensor clamp_max(const at::Tensor & self, const at::Scalar & max);
TORCH_API at::Tensor & clamp_max_(at::Tensor & self, const at::Scalar & max);
TORCH_API at::Tensor & clamp_max_out(const at::Tensor & self, const at::Scalar & max, at::Tensor & out);
TORCH_API at::Tensor clamp_max(const at::Tensor & self, const at::Tensor & max);
TORCH_API at::Tensor & clamp_max_(at::Tensor & self, const at::Tensor & max);
TORCH_API at::Tensor & clamp_max_out(const at::Tensor & self, const at::Tensor & max, at::Tensor & out);
TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Scalar & min);
TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Scalar & min);
TORCH_API at::Tensor & clamp_min_out(const at::Tensor & self, const at::Scalar & min, at::Tensor & out);
TORCH_API at::Tensor clamp_min(const at::Tensor & self, const at::Tensor & min);
TORCH_API at::Tensor & clamp_min_(at::Tensor & self, const at::Tensor & min);
TORCH_API at::Tensor & clamp_min_out(const at::Tensor & self, const at::Tensor & min, at::Tensor & out);
TORCH_API at::Tensor clip(const at::Tensor & self, const c10::optional & min=c10::nullopt, const c10::optional & max=c10::nullopt);
TORCH_API at::Tensor & clip_out(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out);
TORCH_API at::Tensor & clip_(at::Tensor & self, const c10::optional & min=c10::nullopt, const c10::optional & max=c10::nullopt);
TORCH_API at::Tensor clip(const at::Tensor & self, const c10::optional & min={}, const c10::optional & max={});
TORCH_API at::Tensor & clip_out(const at::Tensor & self, const c10::optional & min, const c10::optional & max, at::Tensor & out);
TORCH_API at::Tensor & clip_(at::Tensor & self, const c10::optional & min={}, const c10::optional & max={});
TORCH_API bool cudnn_is_acceptable(const at::Tensor & self);
TORCH_API at::Tensor complex(const at::Tensor & real, const at::Tensor & imag);
TORCH_API at::Tensor & complex_out(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out);
TORCH_API at::Tensor polar(const at::Tensor & abs, const at::Tensor & angle);
TORCH_API at::Tensor & polar_out(const at::Tensor & abs, const at::Tensor & angle, at::Tensor & out);
TORCH_API at::Tensor constant_pad_nd(const at::Tensor & self, at::IntArrayRef pad, const at::Scalar & value=0);
TORCH_API at::Tensor contiguous(const at::Tensor & self, at::MemoryFormat memory_format=MemoryFormat::Contiguous);
TORCH_API at::Tensor convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups);
TORCH_API at::Tensor convolution_overrideable(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups);
TORCH_API ::std::tuple 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 output_mask);
TORCH_API at::Tensor _convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional & 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);
TORCH_API at::Tensor _convolution(const at::Tensor & input, const at::Tensor & weight, const c10::optional & 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);
TORCH_API at::Tensor _convolution_mode(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation, int64_t groups);
TORCH_API at::Tensor _convolution_nogroup(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding);
TORCH_API ::std::tuple _convolution_double_backward(const c10::optional & ggI, const c10::optional & ggW, const c10::optional & 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 output_mask);
TORCH_API at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1);
TORCH_API at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1);
TORCH_API at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef dilation=1, int64_t groups=1);
TORCH_API at::Tensor conv1d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, c10::string_view padding="valid", at::IntArrayRef dilation=1, int64_t groups=1);
TORCH_API at::Tensor conv2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, c10::string_view padding="valid", at::IntArrayRef dilation=1, int64_t groups=1);
TORCH_API at::Tensor conv3d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, c10::string_view padding="valid", at::IntArrayRef dilation=1, int64_t groups=1);
TORCH_API at::Tensor conv_tbc(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & bias, int64_t pad=0);
TORCH_API ::std::tuple conv_tbc_backward(const at::Tensor & self, const at::Tensor & input, const at::Tensor & weight, const at::Tensor & bias, int64_t pad);
TORCH_API at::Tensor conv_transpose1d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1);
TORCH_API at::Tensor conv_transpose2d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1);
TORCH_API at::Tensor conv_transpose3d(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias={}, at::IntArrayRef stride=1, at::IntArrayRef padding=0, at::IntArrayRef output_padding=0, int64_t groups=1, at::IntArrayRef dilation=1);
TORCH_API at::Tensor & copy_(at::Tensor & self, const at::Tensor & src, bool non_blocking=false);
TORCH_API at::Tensor & copy_mkldnn_(at::Tensor & self, const at::Tensor & src, bool non_blocking=false);
struct TORCH_API structured_cos_out : public at::meta::structured_cos {
void impl(const at::Tensor & self, const at::Tensor & out);
};
struct TORCH_API structured_cosh_out : public at::meta::structured_cosh {
void impl(const at::Tensor & self, const at::Tensor & out);
};
TORCH_API 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);
TORCH_API at::Tensor count_nonzero_cpu(const at::Tensor & self, at::IntArrayRef dim);
TORCH_API at::Tensor count_nonzero_cuda(const at::Tensor & self, at::IntArrayRef dim);
TORCH_API at::Tensor count_nonzero(const at::Tensor & self, c10::optional dim=c10::nullopt);
TORCH_API at::Tensor cov(const at::Tensor & self, int64_t correction=1, const c10::optional & fweights={}, const c10::optional & aweights={});
TORCH_API at::Tensor corrcoef(const at::Tensor & self);
TORCH_API at::Tensor cudnn_affine_grid_generator_forward(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W);
TORCH_API at::Tensor cudnn_affine_grid_generator_backward(const at::Tensor & grad, int64_t N, int64_t C, int64_t H, int64_t W);
TORCH_API ::std::tuple cudnn_batch_norm(const at::Tensor & input, const at::Tensor & weight, const c10::optional & bias, const c10::optional & running_mean, const c10::optional & running_var, bool training, double exponential_average_factor, double epsilon);
TORCH_API ::std::tuple cudnn_batch_norm_backward(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional & running_mean, const c10::optional & running_var, const c10::optional & save_mean, const c10::optional & save_var, double epsilon, const at::Tensor & reserveSpace);
TORCH_API at::Tensor cudnn_convolution_deprecated(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
TORCH_API at::Tensor cudnn_convolution_deprecated2(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
TORCH_API at::Tensor cudnn_convolution(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32);
TORCH_API at::Tensor cudnn_convolution_backward_input(at::IntArrayRef self_size, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32);
TORCH_API ::std::tuple cudnn_convolution_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, ::std::array output_mask);
TORCH_API at::Tensor cudnn_convolution_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32);
TORCH_API at::Tensor cudnn_convolution_transpose_deprecated(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
TORCH_API at::Tensor cudnn_convolution_transpose_deprecated2(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic);
TORCH_API at::Tensor cudnn_convolution_transpose(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32);
TORCH_API ::std::tuple cudnn_convolution_transpose_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, ::std::array output_mask);
TORCH_API at::Tensor cudnn_convolution_transpose_backward_input(const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32);
TORCH_API at::Tensor cudnn_convolution_transpose_backward_weight(at::IntArrayRef weight_size, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32);
TORCH_API at::Tensor cudnn_convolution_relu(const at::Tensor & self, const at::Tensor & weight, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups);
TORCH_API at::Tensor cudnn_convolution_add_relu(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const c10::optional & alpha, const c10::optional & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups);
TORCH_API at::Tensor cudnn_grid_sampler_forward(const at::Tensor & self, const at::Tensor & grid);
TORCH_API ::std::tuple cudnn_grid_sampler_backward(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output);
TORCH_API ::std::tuple cummax(const at::Tensor & self, int64_t dim);
TORCH_API ::std::tuple cummax_out(const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices);
TORCH_API ::std::tuple cummax(const at::Tensor & self, at::Dimname dim);
TORCH_API ::std::tuple cummax_out(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices);
TORCH_API void cummax_helper_cpu(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim);
TORCH_API void cummax_helper_cuda(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim);
TORCH_API ::std::tuple cummin(const at::Tensor & self, int64_t dim);
TORCH_API ::std::tuple cummin_out(const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices);
TORCH_API ::std::tuple cummin(const at::Tensor & self, at::Dimname dim);
TORCH_API ::std::tuple cummin_out(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices);
TORCH_API void cummin_helper_cpu(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim);
TORCH_API void cummin_helper_cuda(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim);
TORCH_API at::Tensor cummaxmin_backward(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t dim);
struct TORCH_API structured_cumprod_out : public at::meta::structured_cumprod {
void impl(const at::Tensor & self, int64_t dim, c10::optional dtype, const at::Tensor & out);
};
TORCH_API at::Tensor cumprod(const at::Tensor & self, at::Dimname dim, c10::optional dtype=c10::nullopt);
TORCH_API at::Tensor & cumprod_out(const at::Tensor & self, at::Dimname dim, c10::optional dtype, at::Tensor & out);
TORCH_API at::Tensor & cumprod_(at::Tensor & self, at::Dimname dim, c10::optional dtype=c10::nullopt);
TORCH_API at::Tensor cumprod_backward(const at::Tensor & grad, const at::Tensor & input, int64_t dim, const at::Tensor & output);
struct TORCH_API structured_cumsum_out : public at::meta::structured_cumsum {
void impl(const at::Tensor & self, int64_t dim, c10::optional dtype, const at::Tensor & out);
};
TORCH_API at::Tensor cumsum(const at::Tensor & self, at::Dimname dim, c10::optional dtype=c10::nullopt);
TORCH_API at::Tensor & cumsum_out(const at::Tensor & self, at::Dimname dim, c10::optional dtype, at::Tensor & out);
TORCH_API at::Tensor & cumsum_(at::Tensor & self, at::Dimname dim, c10::optional dtype=c10::nullopt);
TORCH_API at::Tensor cumulative_trapezoid(const at::Tensor & y, const at::Tensor & x, int64_t dim=-1);
TORCH_API at::Tensor cumulative_trapezoid(const at::Tensor & y, const at::Scalar & dx=1, int64_t dim=-1);
TORCH_API 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);
TORCH_API 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);
TORCH_API ::std::tuple ctc_loss_cpu(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false);
TORCH_API ::std::tuple ctc_loss_gpu(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank=0, bool zero_infinity=false);
TORCH_API at::Tensor ctc_loss_backward_cpu(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false);
TORCH_API at::Tensor ctc_loss_backward_gpu(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity=false);
TORCH_API at::Tensor diag_embed(const at::Tensor & self, int64_t offset=0, int64_t dim1=-2, int64_t dim2=-1);
TORCH_API at::Tensor diagflat(const at::Tensor & self, int64_t offset=0);
TORCH_API at::Tensor diagonal(const at::Tensor & self, int64_t offset=0, int64_t dim1=0, int64_t dim2=1);
TORCH_API at::Tensor diagonal(const at::Tensor & self, at::Dimname outdim, at::Dimname dim1, at::Dimname dim2, int64_t offset=0);
TORCH_API at::Tensor diagonal_backward(const at::Tensor & grad_output, at::IntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2);
TORCH_API at::Tensor & fill_diagonal_(at::Tensor & self, const at::Scalar & fill_value, bool wrap=false);
TORCH_API at::Tensor diff(const at::Tensor & self, int64_t n=1, int64_t dim=-1, const c10::optional & prepend={}, const c10::optional & append={});
TORCH_API at::Tensor & diff_out(const at::Tensor & self, int64_t n, int64_t dim, const c10::optional & prepend, const c10::optional & append, at::Tensor & out);
TORCH_API ::std::vector gradient(const at::Tensor & self, const c10::optional & spacing=c10::nullopt, c10::optional dim=c10::nullopt, int64_t edge_order=1);
TORCH_API ::std::vector gradient(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order=1);
TORCH_API ::std::vector gradient(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order=1);
TORCH_API ::std::vector gradient(const at::Tensor & self, at::ArrayRef spacing, c10::optional dim=c10::nullopt, int64_t edge_order=1);
TORCH_API ::std::vector gradient(const at::Tensor & self, at::ArrayRef spacing, at::IntArrayRef dim, int64_t edge_order=1);
TORCH_API ::std::vector gradient(const at::Tensor & self, at::TensorList spacing, c10::optional dim=c10::nullopt, int64_t edge_order=1);
TORCH_API ::std::vector gradient(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order=1);
struct TORCH_API structured_div_out : public at::meta::structured_div_Tensor {
void impl(const at::Tensor & self, const at::Tensor & other, const at::Tensor & out);
};
TORCH_API at::Tensor div_sparse(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & div_out_sparse_zerodim(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor & div_sparse_(at::Tensor & self, const at::Tensor & other);
struct TORCH_API structured_div_out_mode : public at::meta::structured_div_Tensor_mode {
void impl(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, const at::Tensor & out);
};
TORCH_API at::Tensor div_sparse(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode);
TORCH_API at::Tensor & div_out_sparse_zerodim(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, at::Tensor & out);
TORCH_API at::Tensor & div_sparse_(at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode);
TORCH_API at::Tensor div(const at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor div(const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode);
TORCH_API at::Tensor & div_(at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode);
TORCH_API at::Tensor divide(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & divide_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor & divide_(at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor divide(const at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor & divide_(at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor divide(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode);
TORCH_API at::Tensor & divide_out(const at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode, at::Tensor & out);
TORCH_API at::Tensor & divide_(at::Tensor & self, const at::Tensor & other, c10::optional rounding_mode);
TORCH_API at::Tensor divide(const at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode);
TORCH_API at::Tensor & divide_(at::Tensor & self, const at::Scalar & other, c10::optional rounding_mode);
TORCH_API at::Tensor true_divide(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor & true_divide_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor & true_divide_(at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor true_divide(const at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor & true_divide_(at::Tensor & self, const at::Scalar & other);
TORCH_API at::Tensor & dot_out(const at::Tensor & self, const at::Tensor & tensor, at::Tensor & out);
TORCH_API at::Tensor dot(const at::Tensor & self, const at::Tensor & tensor);
TORCH_API at::Tensor dot_cuda(const at::Tensor & self, const at::Tensor & tensor);
TORCH_API at::Tensor & vdot_out(const at::Tensor & self, const at::Tensor & other, at::Tensor & out);
TORCH_API at::Tensor vdot(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor vdot_cuda(const at::Tensor & self, const at::Tensor & other);
TORCH_API at::Tensor einsum(c10::string_view equation, at::TensorList tensors);
TORCH_API 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);
TORCH_API 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);
TORCH_API at::Tensor embedding_dense_backward_cpu(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq);
TORCH_API at::Tensor embedding_dense_backward_cuda(const at::Tensor & grad_output, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq);
TORCH_API at::Tensor & embedding_renorm_cpu_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type);
TORCH_API at::Tensor & embedding_renorm_cuda_(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type);
TORCH_API 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);
TORCH_API ::std::tuple _embedding_bag_forward_only_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
TORCH_API ::std::tuple _embedding_bag_forward_only_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
TORCH_API ::std::tuple _rowwise_prune(const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype);
TORCH_API at::Tensor row_stack(at::TensorList tensors);
TORCH_API at::Tensor & row_stack_out(at::TensorList tensors, at::Tensor & out);
TORCH_API ::std::tuple embedding_bag(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false);
TORCH_API ::std::tuple 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 & per_sample_weights, bool include_last_offset, c10::optional padding_idx);
TORCH_API ::std::tuple _embedding_bag_cpu(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
TORCH_API ::std::tuple _embedding_bag_cuda(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq=false, int64_t mode=0, bool sparse=false, const c10::optional & per_sample_weights={}, bool include_last_offset=false, int64_t padding_idx=-1);
TORCH_API at::Tensor _embedding_bag_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 & per_sample_weights, int64_t padding_idx=-1);
TORCH_API 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 & per_sample_weights, int64_t padding_idx=-1);
TORCH_API at::Tensor _embedding_bag_dense_backward_cpu(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional & per_sample_weights, int64_t padding_idx=-1);
TORCH_API at::Tensor _embedding_bag_dense_backward_cuda(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, int64_t num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional & per_sample_weights, int64_t padding_idx=-1);
TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward_cpu(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1);
TORCH_API at::Tensor _embedding_bag_per_sample_weights_backward_cuda(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx=-1);
TORCH_API at::Tensor empty(at::IntArrayRef size, c10::optional names, c10::optional dtype={}, c10::optional layout={}, c10::optional device={}, c10::optional