text
stringlengths 12
786k
|
|---|
let _linalg_qr_helper self ~ mode = let out__ = CArray . make t 2 in stubs__linalg_qr_helper ( CArray . start out__ ) self mode ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _log_softmax self ~ dim ~ half_to_float = let out__ = CArray . make t 1 in stubs__log_softmax ( CArray . start out__ ) self ( Int64 . of_int dim ) ( if half_to_float then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _log_softmax_backward_data ~ grad_output ~ output ~ dim self = let out__ = CArray . make t 1 in stubs__log_softmax_backward_data ( CArray . start out__ ) grad_output output ( Int64 . of_int dim ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _log_softmax_backward_data_out ~ out ~ grad_output ~ output ~ dim self = let out__ = CArray . make t 1 in stubs__log_softmax_backward_data_out ( CArray . start out__ ) out grad_output output ( Int64 . of_int dim ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _log_softmax_out ~ out self ~ dim ~ half_to_float = let out__ = CArray . make t 1 in stubs__log_softmax_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) ( if half_to_float then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _logcumsumexp self ~ dim = let out__ = CArray . make t 1 in stubs__logcumsumexp ( CArray . start out__ ) self ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _logcumsumexp_out ~ out self ~ dim = let out__ = CArray . make t 1 in stubs__logcumsumexp_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _lu_with_info self ~ pivot ~ check_errors = let out__ = CArray . make t 3 in stubs__lu_with_info ( CArray . start out__ ) self ( if pivot then 1 else 0 ) ( if check_errors then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; t0 , t1 , t2 |
let _make_dual ~ primal ~ tangent ~ level = let out__ = CArray . make t 1 in stubs__make_dual ( CArray . start out__ ) primal tangent ( Int64 . of_int level ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _make_per_channel_quantized_tensor self ~ scale ~ zero_point ~ axis = let out__ = CArray . make t 1 in stubs__make_per_channel_quantized_tensor ( CArray . start out__ ) self scale zero_point ( Int64 . of_int axis ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _make_per_tensor_quantized_tensor self ~ scale ~ zero_point = let out__ = CArray . make t 1 in stubs__make_per_tensor_quantized_tensor ( CArray . start out__ ) self scale ( Int64 . of_int zero_point ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _masked_scale self ~ mask ~ scale = let out__ = CArray . make t 1 in stubs__masked_scale ( CArray . start out__ ) self mask scale ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _mkldnn_reshape self ~ shape = let out__ = CArray . make t 1 in stubs__mkldnn_reshape ( CArray . start out__ ) self ( List . map Int64 . of_int shape |> CArray . of_list int64_t |> CArray . start ) ( List . length shape ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _mkldnn_transpose self ~ dim0 ~ dim1 = let out__ = CArray . make t 1 in stubs__mkldnn_transpose ( CArray . start out__ ) self ( Int64 . of_int dim0 ) ( Int64 . of_int dim1 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _mkldnn_transpose_ self ~ dim0 ~ dim1 = let out__ = CArray . make t 1 in stubs__mkldnn_transpose_ ( CArray . start out__ ) self ( Int64 . of_int dim0 ) ( Int64 . of_int dim1 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _neg_view self = let out__ = CArray . make t 1 in stubs__neg_view ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _nnpack_spatial_convolution input ~ weight ~ bias ~ padding ~ stride = let out__ = CArray . make t 1 in stubs__nnpack_spatial_convolution ( CArray . start out__ ) input weight ( match bias with | Some v -> v | None -> null ) ( List . map Int64 . of_int padding |> CArray . of_list int64_t |> CArray . start ) ( List . length padding ) ( List . map Int64 . of_int stride |> CArray . of_list int64_t |> CArray . start ) ( List . length stride ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _nnpack_spatial_convolution_backward_input input ~ grad_output ~ weight ~ padding = let out__ = CArray . make t 1 in stubs__nnpack_spatial_convolution_backward_input ( CArray . start out__ ) input grad_output weight ( List . map Int64 . of_int padding |> CArray . of_list int64_t |> CArray . start ) ( List . length padding ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _nnpack_spatial_convolution_backward_weight input ~ weightsize ~ grad_output ~ padding = let out__ = CArray . make t 1 in stubs__nnpack_spatial_convolution_backward_weight ( CArray . start out__ ) input ( List . map Int64 . of_int weightsize |> CArray . of_list int64_t |> CArray . start ) ( List . length weightsize ) grad_output ( List . map Int64 . of_int padding |> CArray . of_list int64_t |> CArray . start ) ( List . length padding ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _pack_padded_sequence input ~ lengths ~ batch_first = let out__ = CArray . make t 2 in stubs__pack_padded_sequence ( CArray . start out__ ) input lengths ( if batch_first then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _pack_padded_sequence_backward ~ grad ~ input_size ~ batch_sizes ~ batch_first = let out__ = CArray . make t 1 in stubs__pack_padded_sequence_backward ( CArray . start out__ ) grad ( List . map Int64 . of_int input_size |> CArray . of_list int64_t |> CArray . start ) ( List . length input_size ) batch_sizes ( if batch_first then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _pad_packed_sequence ~ data ~ batch_sizes ~ batch_first ~ padding_value ~ total_length = let out__ = CArray . make t 2 in stubs__pad_packed_sequence ( CArray . start out__ ) data batch_sizes ( if batch_first then 1 else 0 ) padding_value ( Int64 . of_int total_length ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _pdist_backward ~ grad self ~ p ~ pdist = let out__ = CArray . make t 1 in stubs__pdist_backward ( CArray . start out__ ) grad self p pdist ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _pin_memory self ~ device = let out__ = CArray . make t 1 in stubs__pin_memory ( CArray . start out__ ) self ( Device . to_int device ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _remove_batch_dim self ~ level ~ batch_size ~ out_dim = let out__ = CArray . make t 1 in stubs__remove_batch_dim ( CArray . start out__ ) self ( Int64 . of_int level ) ( Int64 . of_int batch_size ) ( Int64 . of_int out_dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _reshape_alias self ~ size ~ stride = let out__ = CArray . make t 1 in stubs__reshape_alias ( CArray . start out__ ) self ( List . map Int64 . of_int size |> CArray . of_list int64_t |> CArray . start ) ( List . length size ) ( List . map Int64 . of_int stride |> CArray . of_list int64_t |> CArray . start ) ( List . length stride ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _reshape_from_tensor self ~ shape = let out__ = CArray . make t 1 in stubs__reshape_from_tensor ( CArray . start out__ ) self shape ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _rowwise_prune ~ weight ~ mask ~ compressed_indices_dtype = let out__ = CArray . make t 2 in stubs__rowwise_prune ( CArray . start out__ ) weight mask ( Kind . packed_to_int compressed_indices_dtype ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _s_where ~ condition self other = let out__ = CArray . make t 1 in stubs__s_where ( CArray . start out__ ) condition self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sample_dirichlet self = let out__ = CArray . make t 1 in stubs__sample_dirichlet ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _saturate_weight_to_fp16 ~ weight = let out__ = CArray . make t 1 in stubs__saturate_weight_to_fp16 ( CArray . start out__ ) weight ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _segment_reduce_backward ~ grad ~ output ~ data ~ reduce ~ lengths ~ axis = let out__ = CArray . make t 1 in stubs__segment_reduce_backward ( CArray . start out__ ) grad output data reduce ( match lengths with | Some v -> v | None -> null ) ( Int64 . of_int axis ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _shape_as_tensor self = let out__ = CArray . make t 1 in stubs__shape_as_tensor ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sobol_engine_draw ~ quasi ~ n ~ sobolstate ~ dimension ~ num_generated ~ dtype = let out__ = CArray . make t 2 in stubs__sobol_engine_draw ( CArray . start out__ ) quasi ( Int64 . of_int n ) sobolstate ( Int64 . of_int dimension ) ( Int64 . of_int num_generated ) ( Kind . packed_to_int dtype ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _sobol_engine_ff_ self ~ n ~ sobolstate ~ dimension ~ num_generated = let out__ = CArray . make t 1 in stubs__sobol_engine_ff_ ( CArray . start out__ ) self ( Int64 . of_int n ) sobolstate ( Int64 . of_int dimension ) ( Int64 . of_int num_generated ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sobol_engine_initialize_state_ self ~ dimension = let out__ = CArray . make t 1 in stubs__sobol_engine_initialize_state_ ( CArray . start out__ ) self ( Int64 . of_int dimension ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sobol_engine_scramble_ self ~ ltm ~ dimension = let out__ = CArray . make t 1 in stubs__sobol_engine_scramble_ ( CArray . start out__ ) self ltm ( Int64 . of_int dimension ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _softmax self ~ dim ~ half_to_float = let out__ = CArray . make t 1 in stubs__softmax ( CArray . start out__ ) self ( Int64 . of_int dim ) ( if half_to_float then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _softmax_backward_data ~ grad_output ~ output ~ dim self = let out__ = CArray . make t 1 in stubs__softmax_backward_data ( CArray . start out__ ) grad_output output ( Int64 . of_int dim ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _softmax_backward_data_out ~ grad_input ~ grad_output ~ output ~ dim self = let out__ = CArray . make t 1 in stubs__softmax_backward_data_out ( CArray . start out__ ) grad_input grad_output output ( Int64 . of_int dim ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _softmax_out ~ out self ~ dim ~ half_to_float = let out__ = CArray . make t 1 in stubs__softmax_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) ( if half_to_float then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _solve_helper self ~ a = let out__ = CArray . make t 2 in stubs__solve_helper ( CArray . start out__ ) self a ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _sparse_addmm self ~ sparse ~ dense = let out__ = CArray . make t 1 in stubs__sparse_addmm ( CArray . start out__ ) self sparse dense ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_coo_tensor_unsafe ~ indices ~ values ~ size ~ options = let out__ = CArray . make t 1 in stubs__sparse_coo_tensor_unsafe ( CArray . start out__ ) indices values ( List . map Int64 . of_int size |> CArray . of_list int64_t |> CArray . start ) ( List . length size ) ( Kind . packed_to_int ( fst options ) ) ( Device . to_int ( snd options ) ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_coo_tensor_with_dims ~ sparse_dim ~ dense_dim ~ size ~ options = let out__ = CArray . make t 1 in stubs__sparse_coo_tensor_with_dims ( CArray . start out__ ) ( Int64 . of_int sparse_dim ) ( Int64 . of_int dense_dim ) ( List . map Int64 . of_int size |> CArray . of_list int64_t |> CArray . start ) ( List . length size ) ( Kind . packed_to_int ( fst options ) ) ( Device . to_int ( snd options ) ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_coo_tensor_with_dims_and_tensors ~ sparse_dim ~ dense_dim ~ size ~ indices ~ values ~ options = let out__ = CArray . make t 1 in stubs__sparse_coo_tensor_with_dims_and_tensors ( CArray . start out__ ) ( Int64 . of_int sparse_dim ) ( Int64 . of_int dense_dim ) ( List . map Int64 . of_int size |> CArray . of_list int64_t |> CArray . start ) ( List . length size ) indices values ( Kind . packed_to_int ( fst options ) ) ( Device . to_int ( snd options ) ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_csr_tensor_unsafe ~ crow_indices ~ col_indices ~ values ~ size ~ options = let out__ = CArray . make t 1 in stubs__sparse_csr_tensor_unsafe ( CArray . start out__ ) crow_indices col_indices values ( List . map Int64 . of_int size |> CArray . of_list int64_t |> CArray . start ) ( List . length size ) ( Kind . packed_to_int ( fst options ) ) ( Device . to_int ( snd options ) ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_log_softmax self ~ dim ~ half_to_float = let out__ = CArray . make t 1 in stubs__sparse_log_softmax ( CArray . start out__ ) self ( Int64 . of_int dim ) ( if half_to_float then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_log_softmax_backward_data ~ grad_output ~ output ~ dim self = let out__ = CArray . make t 1 in stubs__sparse_log_softmax_backward_data ( CArray . start out__ ) grad_output output ( Int64 . of_int dim ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_log_softmax_int self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs__sparse_log_softmax_int ( CArray . start out__ ) self ( Int64 . of_int dim ) ( Kind . packed_to_int dtype ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_mask_helper ~ tr ~ mask_indices = let out__ = CArray . make t 1 in stubs__sparse_mask_helper ( CArray . start out__ ) tr mask_indices ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_mm ~ sparse ~ dense = let out__ = CArray . make t 1 in stubs__sparse_mm ( CArray . start out__ ) sparse dense ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_softmax self ~ dim ~ half_to_float = let out__ = CArray . make t 1 in stubs__sparse_softmax ( CArray . start out__ ) self ( Int64 . of_int dim ) ( if half_to_float then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_softmax_backward_data ~ grad_output ~ output ~ dim self = let out__ = CArray . make t 1 in stubs__sparse_softmax_backward_data ( CArray . start out__ ) grad_output output ( Int64 . of_int dim ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_softmax_int self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs__sparse_softmax_int ( CArray . start out__ ) self ( Int64 . of_int dim ) ( Kind . packed_to_int dtype ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_sparse_matmul self other = let out__ = CArray . make t 1 in stubs__sparse_sparse_matmul ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_sum self = let out__ = CArray . make t 1 in stubs__sparse_sum ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_sum_backward ~ grad self ~ dim = let out__ = CArray . make t 1 in stubs__sparse_sum_backward ( CArray . start out__ ) grad self ( List . map Int64 . of_int dim |> CArray . of_list int64_t |> CArray . start ) ( List . length dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_sum_dim self ~ dim = let out__ = CArray . make t 1 in stubs__sparse_sum_dim ( CArray . start out__ ) self ( List . map Int64 . of_int dim |> CArray . of_list int64_t |> CArray . start ) ( List . length dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_sum_dim_dtype self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs__sparse_sum_dim_dtype ( CArray . start out__ ) self ( List . map Int64 . of_int dim |> CArray . of_list int64_t |> CArray . start ) ( List . length dim ) ( Kind . packed_to_int dtype ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _sparse_sum_dtype self ~ dtype = let out__ = CArray . make t 1 in stubs__sparse_sum_dtype ( CArray . start out__ ) self ( Kind . packed_to_int dtype ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _stack tensors ~ dim = let out__ = CArray . make t 1 in stubs__stack ( CArray . start out__ ) ( CArray . of_list t tensors |> CArray . start ) ( List . length tensors ) ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _stack_out ~ out tensors ~ dim = let out__ = CArray . make t 1 in stubs__stack_out ( CArray . start out__ ) out ( CArray . of_list t tensors |> CArray . start ) ( List . length tensors ) ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _standard_gamma self = let out__ = CArray . make t 1 in stubs__standard_gamma ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _standard_gamma_grad self ~ output = let out__ = CArray . make t 1 in stubs__standard_gamma_grad ( CArray . start out__ ) self output ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _svd_helper self ~ some ~ compute_uv = let out__ = CArray . make t 3 in stubs__svd_helper ( CArray . start out__ ) self ( if some then 1 else 0 ) ( if compute_uv then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; t0 , t1 , t2 |
let _symeig_helper self ~ eigenvectors ~ upper = let out__ = CArray . make t 2 in stubs__symeig_helper ( CArray . start out__ ) self ( if eigenvectors then 1 else 0 ) ( if upper then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _test_ambiguous_defaults ~ dummy ~ a ~ b = let out__ = CArray . make t 1 in stubs__test_ambiguous_defaults ( CArray . start out__ ) dummy ( Int64 . of_int a ) ( Int64 . of_int b ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _test_ambiguous_defaults_b ~ dummy ~ a ~ b = let out__ = CArray . make t 1 in stubs__test_ambiguous_defaults_b ( CArray . start out__ ) dummy ( Int64 . of_int a ) b ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _test_optional_filled_intlist ~ values ~ addends = let out__ = CArray . make t 1 in stubs__test_optional_filled_intlist ( CArray . start out__ ) values ( List . map Int64 . of_int addends |> CArray . of_list int64_t |> CArray . start ) ( List . length addends ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _test_optional_intlist ~ values ~ addends = let out__ = CArray . make t 1 in stubs__test_optional_intlist ( CArray . start out__ ) values ( List . map Int64 . of_int addends |> CArray . of_list int64_t |> CArray . start ) ( List . length addends ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _test_serialization_subcmul self other = let out__ = CArray . make t 1 in stubs__test_serialization_subcmul ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _test_string_default ~ dummy ~ a ~ b = let out__ = CArray . make t 1 in stubs__test_string_default ( CArray . start out__ ) dummy a b ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _thnn_differentiable_gru_cell_backward ~ grad_hy ~ input_gates ~ hidden_gates ~ hx ~ input_bias ~ hidden_bias = let out__ = CArray . make t 5 in stubs__thnn_differentiable_gru_cell_backward ( CArray . start out__ ) grad_hy input_gates hidden_gates hx ( match input_bias with | Some v -> v | None -> null ) ( match hidden_bias with | Some v -> v | None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; let t3 = CArray . get out__ 3 in Gc . finalise C . Tensor . free t3 ; let t4 = CArray . get out__ 4 in Gc . finalise C . Tensor . free t4 ; t0 , t1 , t2 , t3 , t4 |
let _thnn_differentiable_lstm_cell_backward ~ grad_hy ~ grad_cy ~ input_gates ~ hidden_gates ~ input_bias ~ hidden_bias ~ cx ~ cy = let out__ = CArray . make t 5 in stubs__thnn_differentiable_lstm_cell_backward ( CArray . start out__ ) ( match grad_hy with | Some v -> v | None -> null ) ( match grad_cy with | Some v -> v | None -> null ) input_gates hidden_gates ( match input_bias with | Some v -> v | None -> null ) ( match hidden_bias with | Some v -> v | None -> null ) cx cy ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; let t3 = CArray . get out__ 3 in Gc . finalise C . Tensor . free t3 ; let t4 = CArray . get out__ 4 in Gc . finalise C . Tensor . free t4 ; t0 , t1 , t2 , t3 , t4 |
let _thnn_fused_gru_cell ~ input_gates ~ hidden_gates ~ hx ~ input_bias ~ hidden_bias = let out__ = CArray . make t 2 in stubs__thnn_fused_gru_cell ( CArray . start out__ ) input_gates hidden_gates hx ( match input_bias with | Some v -> v | None -> null ) ( match hidden_bias with | Some v -> v | None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _thnn_fused_gru_cell_backward ~ grad_hy ~ workspace ~ has_bias = let out__ = CArray . make t 5 in stubs__thnn_fused_gru_cell_backward ( CArray . start out__ ) grad_hy workspace ( if has_bias then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; let t3 = CArray . get out__ 3 in Gc . finalise C . Tensor . free t3 ; let t4 = CArray . get out__ 4 in Gc . finalise C . Tensor . free t4 ; t0 , t1 , t2 , t3 , t4 |
let _thnn_fused_lstm_cell ~ input_gates ~ hidden_gates ~ cx ~ input_bias ~ hidden_bias = let out__ = CArray . make t 3 in stubs__thnn_fused_lstm_cell ( CArray . start out__ ) input_gates hidden_gates cx ( match input_bias with | Some v -> v | None -> null ) ( match hidden_bias with | Some v -> v | None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; t0 , t1 , t2 |
let _thnn_fused_lstm_cell_backward ~ grad_hy ~ grad_cy ~ cx ~ cy ~ workspace ~ has_bias = let out__ = CArray . make t 5 in stubs__thnn_fused_lstm_cell_backward ( CArray . start out__ ) ( match grad_hy with | Some v -> v | None -> null ) ( match grad_cy with | Some v -> v | None -> null ) cx cy workspace ( if has_bias then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; let t3 = CArray . get out__ 3 in Gc . finalise C . Tensor . free t3 ; let t4 = CArray . get out__ 4 in Gc . finalise C . Tensor . free t4 ; t0 , t1 , t2 , t3 , t4 |
let _to_copy self ~ options ~ non_blocking = let out__ = CArray . make t 1 in stubs__to_copy ( CArray . start out__ ) self ( Kind . packed_to_int ( fst options ) ) ( Device . to_int ( snd options ) ) ( if non_blocking then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _to_cpu tensors = stubs__to_cpu ( CArray . of_list t tensors |> CArray . start ) ( List . length tensors ) |> to_tensor_list |
let _trilinear ~ i1 ~ i2 ~ i3 ~ expand1 ~ expand2 ~ expand3 ~ sumdim ~ unroll_dim = let out__ = CArray . make t 1 in stubs__trilinear ( CArray . start out__ ) i1 i2 i3 ( List . map Int64 . of_int expand1 |> CArray . of_list int64_t |> CArray . start ) ( List . length expand1 ) ( List . map Int64 . of_int expand2 |> CArray . of_list int64_t |> CArray . start ) ( List . length expand2 ) ( List . map Int64 . of_int expand3 |> CArray . of_list int64_t |> CArray . start ) ( List . length expand3 ) ( List . map Int64 . of_int sumdim |> CArray . of_list int64_t |> CArray . start ) ( List . length sumdim ) ( Int64 . of_int unroll_dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _unique self ~ sorted ~ return_inverse = let out__ = CArray . make t 2 in stubs__unique ( CArray . start out__ ) self ( if sorted then 1 else 0 ) ( if return_inverse then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _unique2 self ~ sorted ~ return_inverse ~ return_counts = let out__ = CArray . make t 3 in stubs__unique2 ( CArray . start out__ ) self ( if sorted then 1 else 0 ) ( if return_inverse then 1 else 0 ) ( if return_counts then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; let t2 = CArray . get out__ 2 in Gc . finalise C . Tensor . free t2 ; t0 , t1 , t2 |
let _unpack_dual ~ dual ~ level = let out__ = CArray . make t 2 in stubs__unpack_dual ( CArray . start out__ ) dual ( Int64 . of_int level ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _unsafe_view self ~ size = let out__ = CArray . make t 1 in stubs__unsafe_view ( CArray . start out__ ) self ( List . map Int64 . of_int size |> CArray . of_list int64_t |> CArray . start ) ( List . length size ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _values self = let out__ = CArray . make t 1 in stubs__values ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _weight_norm ~ v ~ g ~ dim = let out__ = CArray . make t 1 in stubs__weight_norm ( CArray . start out__ ) v g ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let _weight_norm_cuda_interface ~ v ~ g ~ dim = let out__ = CArray . make t 2 in stubs__weight_norm_cuda_interface ( CArray . start out__ ) v g ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _weight_norm_cuda_interface_backward ~ grad_w ~ saved_v ~ saved_g ~ saved_norms ~ dim = let out__ = CArray . make t 2 in stubs__weight_norm_cuda_interface_backward ( CArray . start out__ ) grad_w saved_v saved_g saved_norms ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let _weight_norm_differentiable_backward ~ grad_w ~ saved_v ~ saved_g ~ saved_norms ~ dim = let out__ = CArray . make t 2 in stubs__weight_norm_differentiable_backward ( CArray . start out__ ) grad_w saved_v saved_g saved_norms ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; let t1 = CArray . get out__ 1 in Gc . finalise C . Tensor . free t1 ; t0 , t1 |
let abs self = let out__ = CArray . make t 1 in stubs_abs ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let abs_ self = let out__ = CArray . make t 1 in stubs_abs_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let abs_out ~ out self = let out__ = CArray . make t 1 in stubs_abs_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let absolute self = let out__ = CArray . make t 1 in stubs_absolute ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let absolute_ self = let out__ = CArray . make t 1 in stubs_absolute_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let absolute_out ~ out self = let out__ = CArray . make t 1 in stubs_absolute_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let acos self = let out__ = CArray . make t 1 in stubs_acos ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let acos_ self = let out__ = CArray . make t 1 in stubs_acos_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let acos_out ~ out self = let out__ = CArray . make t 1 in stubs_acos_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.