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let replication_pad1d_backward_grad_input ~ grad_input ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad1d_backward_grad_input ( CArray . start out__ ) grad_input grad_output self ( 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 replication_pad1d_out ~ out self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad1d_out ( CArray . start out__ ) out self ( 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 replication_pad2d self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad2d ( CArray . start out__ ) self ( 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 replication_pad2d_backward ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad2d_backward ( CArray . start out__ ) grad_output self ( 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 replication_pad2d_backward_grad_input ~ grad_input ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad2d_backward_grad_input ( CArray . start out__ ) grad_input grad_output self ( 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 replication_pad2d_out ~ out self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad2d_out ( CArray . start out__ ) out self ( 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 replication_pad3d self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad3d ( CArray . start out__ ) self ( 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 replication_pad3d_backward ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad3d_backward ( CArray . start out__ ) grad_output self ( 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 replication_pad3d_backward_grad_input ~ grad_input ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad3d_backward_grad_input ( CArray . start out__ ) grad_input grad_output self ( 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 replication_pad3d_out ~ out self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad3d_out ( CArray . start out__ ) out self ( 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 requires_grad_ self ~ requires_grad = let out__ = CArray . make t 1 in stubs_requires_grad_ ( CArray . start out__ ) self ( if requires_grad then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let reshape self ~ shape = let out__ = CArray . make t 1 in stubs_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 reshape_as self other = let out__ = CArray . make t 1 in stubs_reshape_as ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let resize_ self ~ size = let out__ = CArray . make t 1 in stubs_resize_ ( 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 resize_as_ self ~ the_template = let out__ = CArray . make t 1 in stubs_resize_as_ ( CArray . start out__ ) self the_template ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let resize_as_sparse_ self ~ the_template = let out__ = CArray . make t 1 in stubs_resize_as_sparse_ ( CArray . start out__ ) self the_template ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let resolve_conj self = let out__ = CArray . make t 1 in stubs_resolve_conj ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let resolve_neg self = let out__ = CArray . make t 1 in stubs_resolve_neg ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rnn_relu input ~ hx ~ params ~ has_biases ~ num_layers ~ dropout ~ train ~ bidirectional ~ batch_first = let out__ = CArray . make t 2 in stubs_rnn_relu ( CArray . start out__ ) input hx ( CArray . of_list t params |> CArray . start ) ( List . length params ) ( if has_biases then 1 else 0 ) ( Int64 . of_int num_layers ) dropout ( if train then 1 else 0 ) ( if bidirectional then 1 else 0 ) ( 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 rnn_relu_cell input ~ hx ~ w_ih ~ w_hh ~ b_ih ~ b_hh = let out__ = CArray . make t 1 in stubs_rnn_relu_cell ( CArray . start out__ ) input hx w_ih w_hh ( match b_ih with | Some v -> v | None -> null ) ( match b_hh with | Some v -> v | None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rnn_relu_data ~ data ~ batch_sizes ~ hx ~ params ~ has_biases ~ num_layers ~ dropout ~ train ~ bidirectional = let out__ = CArray . make t 2 in stubs_rnn_relu_data ( CArray . start out__ ) data batch_sizes hx ( CArray . of_list t params |> CArray . start ) ( List . length params ) ( if has_biases then 1 else 0 ) ( Int64 . of_int num_layers ) dropout ( if train then 1 else 0 ) ( if bidirectional 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 rnn_tanh input ~ hx ~ params ~ has_biases ~ num_layers ~ dropout ~ train ~ bidirectional ~ batch_first = let out__ = CArray . make t 2 in stubs_rnn_tanh ( CArray . start out__ ) input hx ( CArray . of_list t params |> CArray . start ) ( List . length params ) ( if has_biases then 1 else 0 ) ( Int64 . of_int num_layers ) dropout ( if train then 1 else 0 ) ( if bidirectional then 1 else 0 ) ( 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 rnn_tanh_cell input ~ hx ~ w_ih ~ w_hh ~ b_ih ~ b_hh = let out__ = CArray . make t 1 in stubs_rnn_tanh_cell ( CArray . start out__ ) input hx w_ih w_hh ( match b_ih with | Some v -> v | None -> null ) ( match b_hh with | Some v -> v | None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rnn_tanh_data ~ data ~ batch_sizes ~ hx ~ params ~ has_biases ~ num_layers ~ dropout ~ train ~ bidirectional = let out__ = CArray . make t 2 in stubs_rnn_tanh_data ( CArray . start out__ ) data batch_sizes hx ( CArray . of_list t params |> CArray . start ) ( List . length params ) ( if has_biases then 1 else 0 ) ( Int64 . of_int num_layers ) dropout ( if train then 1 else 0 ) ( if bidirectional 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 roll self ~ shifts ~ dims = let out__ = CArray . make t 1 in stubs_roll ( CArray . start out__ ) self ( List . map Int64 . of_int shifts |> CArray . of_list int64_t |> CArray . start ) ( List . length shifts ) ( List . map Int64 . of_int dims |> CArray . of_list int64_t |> CArray . start ) ( List . length dims ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rot90 self ~ k ~ dims = let out__ = CArray . make t 1 in stubs_rot90 ( CArray . start out__ ) self ( Int64 . of_int k ) ( List . map Int64 . of_int dims |> CArray . of_list int64_t |> CArray . start ) ( List . length dims ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let round self = let out__ = CArray . make t 1 in stubs_round ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let round_ self = let out__ = CArray . make t 1 in stubs_round_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let round_out ~ out self = let out__ = CArray . make t 1 in stubs_round_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let row_stack tensors = let out__ = CArray . make t 1 in stubs_row_stack ( CArray . start out__ ) ( CArray . of_list t tensors |> CArray . start ) ( List . length tensors ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let row_stack_out ~ out tensors = let out__ = CArray . make t 1 in stubs_row_stack_out ( CArray . start out__ ) out ( CArray . of_list t tensors |> CArray . start ) ( List . length tensors ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rrelu self ~ training = let out__ = CArray . make t 1 in stubs_rrelu ( CArray . start out__ ) self ( if training then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rrelu_ self ~ training = let out__ = CArray . make t 1 in stubs_rrelu_ ( CArray . start out__ ) self ( if training then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rrelu_with_noise self ~ noise ~ training = let out__ = CArray . make t 1 in stubs_rrelu_with_noise ( CArray . start out__ ) self noise ( if training then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rrelu_with_noise_ self ~ noise ~ training = let out__ = CArray . make t 1 in stubs_rrelu_with_noise_ ( CArray . start out__ ) self noise ( if training then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rrelu_with_noise_backward ~ grad_output self ~ noise ~ lower ~ upper ~ training ~ self_is_result = let out__ = CArray . make t 1 in stubs_rrelu_with_noise_backward ( CArray . start out__ ) grad_output self noise lower upper ( if training then 1 else 0 ) ( if self_is_result then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rrelu_with_noise_out ~ out self ~ noise ~ training = let out__ = CArray . make t 1 in stubs_rrelu_with_noise_out ( CArray . start out__ ) out self noise ( if training then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rsqrt self = let out__ = CArray . make t 1 in stubs_rsqrt ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rsqrt_ self = let out__ = CArray . make t 1 in stubs_rsqrt_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rsqrt_out ~ out self = let out__ = CArray . make t 1 in stubs_rsqrt_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rsub self other = let out__ = CArray . make t 1 in stubs_rsub ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let rsub_scalar self other = let out__ = CArray . make t 1 in stubs_rsub_scalar ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scalar_tensor ~ s ~ options = let out__ = CArray . make t 1 in stubs_scalar_tensor ( CArray . start out__ ) s ( 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 scatter self ~ dim ~ index ~ src = let out__ = CArray . make t 1 in stubs_scatter ( CArray . start out__ ) self ( Int64 . of_int dim ) index src ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_ self ~ dim ~ index ~ src = let out__ = CArray . make t 1 in stubs_scatter_ ( CArray . start out__ ) self ( Int64 . of_int dim ) index src ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_add self ~ dim ~ index ~ src = let out__ = CArray . make t 1 in stubs_scatter_add ( CArray . start out__ ) self ( Int64 . of_int dim ) index src ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_add_ self ~ dim ~ index ~ src = let out__ = CArray . make t 1 in stubs_scatter_add_ ( CArray . start out__ ) self ( Int64 . of_int dim ) index src ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_add_out ~ out self ~ dim ~ index ~ src = let out__ = CArray . make t 1 in stubs_scatter_add_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) index src ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_reduce self ~ dim ~ index ~ src ~ reduce = let out__ = CArray . make t 1 in stubs_scatter_reduce ( CArray . start out__ ) self ( Int64 . of_int dim ) index src reduce ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_reduce_ self ~ dim ~ index ~ src ~ reduce = let out__ = CArray . make t 1 in stubs_scatter_reduce_ ( CArray . start out__ ) self ( Int64 . of_int dim ) index src reduce ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_reduce_out ~ out self ~ dim ~ index ~ src ~ reduce = let out__ = CArray . make t 1 in stubs_scatter_reduce_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) index src reduce ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_src_out ~ out self ~ dim ~ index ~ src = let out__ = CArray . make t 1 in stubs_scatter_src_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) index src ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_value self ~ dim ~ index ~ value = let out__ = CArray . make t 1 in stubs_scatter_value ( CArray . start out__ ) self ( Int64 . of_int dim ) index value ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_value_ self ~ dim ~ index ~ value = let out__ = CArray . make t 1 in stubs_scatter_value_ ( CArray . start out__ ) self ( Int64 . of_int dim ) index value ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_value_out ~ out self ~ dim ~ index ~ value = let out__ = CArray . make t 1 in stubs_scatter_value_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) index value ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_value_reduce self ~ dim ~ index ~ value ~ reduce = let out__ = CArray . make t 1 in stubs_scatter_value_reduce ( CArray . start out__ ) self ( Int64 . of_int dim ) index value reduce ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_value_reduce_ self ~ dim ~ index ~ value ~ reduce = let out__ = CArray . make t 1 in stubs_scatter_value_reduce_ ( CArray . start out__ ) self ( Int64 . of_int dim ) index value reduce ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let scatter_value_reduce_out ~ out self ~ dim ~ index ~ value ~ reduce = let out__ = CArray . make t 1 in stubs_scatter_value_reduce_out ( CArray . start out__ ) out self ( Int64 . of_int dim ) index value reduce ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let searchsorted ~ sorted_sequence self ~ out_int32 ~ right = let out__ = CArray . make t 1 in stubs_searchsorted ( CArray . start out__ ) sorted_sequence self ( if out_int32 then 1 else 0 ) ( if right then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let searchsorted_scalar ~ sorted_sequence self ~ out_int32 ~ right = let out__ = CArray . make t 1 in stubs_searchsorted_scalar ( CArray . start out__ ) sorted_sequence self ( if out_int32 then 1 else 0 ) ( if right then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let searchsorted_tensor_out ~ out ~ sorted_sequence self ~ out_int32 ~ right = let out__ = CArray . make t 1 in stubs_searchsorted_tensor_out ( CArray . start out__ ) out sorted_sequence self ( if out_int32 then 1 else 0 ) ( if right then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let segment_reduce ~ data ~ reduce ~ lengths ~ indices ~ axis ~ unsafe ~ initial = let out__ = CArray . make t 1 in stubs_segment_reduce ( CArray . start out__ ) data reduce ( match lengths with | Some v -> v | None -> null ) ( match indices with | Some v -> v | None -> null ) ( Int64 . of_int axis ) ( if unsafe then 1 else 0 ) initial ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let select self ~ dim ~ index = let out__ = CArray . make t 1 in stubs_select ( CArray . start out__ ) self ( Int64 . of_int dim ) ( Int64 . of_int index ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let select_backward ~ grad_output ~ input_sizes ~ dim ~ index = let out__ = CArray . make t 1 in stubs_select_backward ( CArray . start out__ ) grad_output ( List . map Int64 . of_int input_sizes |> CArray . of_list int64_t |> CArray . start ) ( List . length input_sizes ) ( Int64 . of_int dim ) ( Int64 . of_int index ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let selu self = let out__ = CArray . make t 1 in stubs_selu ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let selu_ self = let out__ = CArray . make t 1 in stubs_selu_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let set_ self = let out__ = CArray . make t 1 in stubs_set_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let set_requires_grad self ~ r = let out__ = CArray . make t 1 in stubs_set_requires_grad ( CArray . start out__ ) self ( if r then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let set_source_tensor_ self ~ source = let out__ = CArray . make t 1 in stubs_set_source_tensor_ ( CArray . start out__ ) self source ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sgn self = let out__ = CArray . make t 1 in stubs_sgn ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sgn_ self = let out__ = CArray . make t 1 in stubs_sgn_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sgn_out ~ out self = let out__ = CArray . make t 1 in stubs_sgn_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sigmoid self = let out__ = CArray . make t 1 in stubs_sigmoid ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sigmoid_ self = let out__ = CArray . make t 1 in stubs_sigmoid_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sigmoid_backward ~ grad_output ~ output = let out__ = CArray . make t 1 in stubs_sigmoid_backward ( CArray . start out__ ) grad_output output ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sigmoid_backward_grad_input ~ grad_input ~ grad_output ~ output = let out__ = CArray . make t 1 in stubs_sigmoid_backward_grad_input ( CArray . start out__ ) grad_input grad_output output ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sigmoid_out ~ out self = let out__ = CArray . make t 1 in stubs_sigmoid_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sign self = let out__ = CArray . make t 1 in stubs_sign ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sign_ self = let out__ = CArray . make t 1 in stubs_sign_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sign_out ~ out self = let out__ = CArray . make t 1 in stubs_sign_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let signbit self = let out__ = CArray . make t 1 in stubs_signbit ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let signbit_out ~ out self = let out__ = CArray . make t 1 in stubs_signbit_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let silu self = let out__ = CArray . make t 1 in stubs_silu ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let silu_ self = let out__ = CArray . make t 1 in stubs_silu_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let silu_backward ~ grad_output self = let out__ = CArray . make t 1 in stubs_silu_backward ( CArray . start out__ ) grad_output self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let silu_backward_grad_input ~ grad_input ~ grad_output self = let out__ = CArray . make t 1 in stubs_silu_backward_grad_input ( CArray . start out__ ) grad_input grad_output self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let silu_out ~ out self = let out__ = CArray . make t 1 in stubs_silu_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sin self = let out__ = CArray . make t 1 in stubs_sin ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sin_ self = let out__ = CArray . make t 1 in stubs_sin_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sin_out ~ out self = let out__ = CArray . make t 1 in stubs_sin_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sinc self = let out__ = CArray . make t 1 in stubs_sinc ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sinc_ self = let out__ = CArray . make t 1 in stubs_sinc_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sinc_out ~ out self = let out__ = CArray . make t 1 in stubs_sinc_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sinh self = let out__ = CArray . make t 1 in stubs_sinh ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sinh_ self = let out__ = CArray . make t 1 in stubs_sinh_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let sinh_out ~ out self = let out__ = CArray . make t 1 in stubs_sinh_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let slice self ~ dim ~ start ~ end_ ~ step = let out__ = CArray . make t 1 in stubs_slice ( CArray . start out__ ) self ( Int64 . of_int dim ) ( Int64 . of_int start ) ( Int64 . of_int end_ ) ( Int64 . of_int step ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let slice_backward ~ grad_output ~ input_sizes ~ dim ~ start ~ end_ ~ step = let out__ = CArray . make t 1 in stubs_slice_backward ( CArray . start out__ ) grad_output ( List . map Int64 . of_int input_sizes |> CArray . of_list int64_t |> CArray . start ) ( List . length input_sizes ) ( Int64 . of_int dim ) ( Int64 . of_int start ) ( Int64 . of_int end_ ) ( Int64 . of_int step ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0 |
let slogdet self = let out__ = CArray . make t 2 in stubs_slogdet ( CArray . start out__ ) self ; 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 slow_conv3d self ~ weight ~ kernel_size ~ bias ~ stride ~ padding = let out__ = CArray . make t 1 in stubs_slow_conv3d ( CArray . start out__ ) self weight ( List . map Int64 . of_int kernel_size |> CArray . of_list int64_t |> CArray . start ) ( List . length kernel_size ) ( match bias with | Some v -> v | None -> null ) ( List . map Int64 . of_int stride |> CArray . of_list int64_t |> CArray . start ) ( List . length stride ) ( 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 |
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