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OCaml_program_corpus

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let ravel self = let out__ = CArray . make t 1 in stubs_ravel ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let real self = let out__ = CArray . make t 1 in stubs_real ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let reciprocal self = let out__ = CArray . make t 1 in stubs_reciprocal ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let reciprocal_ self = let out__ = CArray . make t 1 in stubs_reciprocal_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let reciprocal_out ~ out self = let out__ = CArray . make t 1 in stubs_reciprocal_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let reflection_pad1d self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_pad1d ( 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 reflection_pad1d_backward ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_pad1d_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 reflection_pad1d_backward_grad_input ~ grad_input ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad1d_out ~ out self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad2d self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad2d_backward ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad2d_backward_grad_input ~ grad_input ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad2d_out ~ out self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad3d self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad3d_backward ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad3d_backward_grad_input ~ grad_input ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 reflection_pad3d_out ~ out self ~ padding = let out__ = CArray . make t 1 in stubs_reflection_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 relu self = let out__ = CArray . make t 1 in stubs_relu ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let relu6 self = let out__ = CArray . make t 1 in stubs_relu6 ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let relu6_ self = let out__ = CArray . make t 1 in stubs_relu6_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let relu_ self = let out__ = CArray . make t 1 in stubs_relu_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder self other = let out__ = CArray . make t 1 in stubs_remainder ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder_ self other = let out__ = CArray . make t 1 in stubs_remainder_ ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder_scalar_out ~ out self other = let out__ = CArray . make t 1 in stubs_remainder_scalar_out ( CArray . start out__ ) out self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder_scalar_tensor self other = let out__ = CArray . make t 1 in stubs_remainder_scalar_tensor ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder_tensor self other = let out__ = CArray . make t 1 in stubs_remainder_tensor ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder_tensor_ self other = let out__ = CArray . make t 1 in stubs_remainder_tensor_ ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let remainder_tensor_out ~ out self other = let out__ = CArray . make t 1 in stubs_remainder_tensor_out ( CArray . start out__ ) out self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let renorm self ~ p ~ dim ~ maxnorm = let out__ = CArray . make t 1 in stubs_renorm ( CArray . start out__ ) self p ( Int64 . of_int dim ) maxnorm ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let renorm_ self ~ p ~ dim ~ maxnorm = let out__ = CArray . make t 1 in stubs_renorm_ ( CArray . start out__ ) self p ( Int64 . of_int dim ) maxnorm ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let renorm_out ~ out self ~ p ~ dim ~ maxnorm = let out__ = CArray . make t 1 in stubs_renorm_out ( CArray . start out__ ) out self p ( Int64 . of_int dim ) maxnorm ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let repeat self ~ repeats = let out__ = CArray . make t 1 in stubs_repeat ( CArray . start out__ ) self ( List . map Int64 . of_int repeats \|> CArray . of_list int64_t \|> CArray . start ) ( List . length repeats ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let repeat_interleave ~ repeats ~ output_size = let out__ = CArray . make t 1 in stubs_repeat_interleave ( CArray . start out__ ) repeats ( Int64 . of_int output_size ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let repeat_interleave_self_int self ~ repeats ~ dim ~ output_size = let out__ = CArray . make t 1 in stubs_repeat_interleave_self_int ( CArray . start out__ ) self ( Int64 . of_int repeats ) ( Int64 . of_int dim ) ( Int64 . of_int output_size ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let repeat_interleave_self_tensor self ~ repeats ~ dim ~ output_size = let out__ = CArray . make t 1 in stubs_repeat_interleave_self_tensor ( CArray . start out__ ) self repeats ( Int64 . of_int dim ) ( Int64 . of_int output_size ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let replication_pad1d self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad1d ( 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_pad1d_backward ~ grad_output self ~ padding = let out__ = CArray . make t 1 in stubs_replication_pad1d_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_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

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