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AllenGeng
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OCaml_program_corpus

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let conv1d_padding input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_conv1d_padding ( CArray . start out__ ) input weight ( match bias with \| Some v -> v \| None -> null ) ( List . map Int64 . of_int stride \|> CArray . of_list int64_t \|> CArray . start ) ( List . length stride ) padding ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv2d input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_conv2d ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv2d_padding input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_conv2d_padding ( CArray . start out__ ) input weight ( match bias with \| Some v -> v \| None -> null ) ( List . map Int64 . of_int stride \|> CArray . of_list int64_t \|> CArray . start ) ( List . length stride ) padding ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv3d input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_conv3d ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv3d_padding input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_conv3d_padding ( CArray . start out__ ) input weight ( match bias with \| Some v -> v \| None -> null ) ( List . map Int64 . of_int stride \|> CArray . of_list int64_t \|> CArray . start ) ( List . length stride ) padding ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv_depthwise3d self ~ weight ~ kernel_size ~ bias ~ stride ~ padding ~ dilation = let out__ = CArray . make t 1 in stubs_conv_depthwise3d ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv_depthwise3d_backward ~ grad_input ~ grad_weight ~ grad_bias ~ grad_output self ~ weight ~ kernel_size ~ stride ~ padding ~ dilation = let out__ = CArray . make t 3 in stubs_conv_depthwise3d_backward ( CArray . start out__ ) grad_input grad_weight grad_bias grad_output self weight ( List . map Int64 . of_int kernel_size \|> CArray . of_list int64_t \|> CArray . start ) ( List . length kernel_size ) ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ; 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 conv_tbc self ~ weight ~ bias ~ pad = let out__ = CArray . make t 1 in stubs_conv_tbc ( CArray . start out__ ) self weight bias ( Int64 . of_int pad ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv_tbc_backward self input ~ weight ~ bias ~ pad = let out__ = CArray . make t 3 in stubs_conv_tbc_backward ( CArray . start out__ ) self input weight bias ( Int64 . of_int pad ) ; 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 conv_transpose1d input ~ weight ~ bias ~ stride ~ padding ~ output_padding ~ groups ~ dilation = let out__ = CArray . make t 1 in stubs_conv_transpose1d ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( Int64 . of_int groups ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv_transpose2d input ~ weight ~ bias ~ stride ~ padding ~ output_padding ~ groups ~ dilation = let out__ = CArray . make t 1 in stubs_conv_transpose2d ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( Int64 . of_int groups ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let conv_transpose3d input ~ weight ~ bias ~ stride ~ padding ~ output_padding ~ groups ~ dilation = let out__ = CArray . make t 1 in stubs_conv_transpose3d ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( Int64 . of_int groups ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let convolution input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ transposed ~ output_padding ~ groups = let out__ = CArray . make t 1 in stubs_convolution ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( if transposed then 1 else 0 ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let convolution_overrideable input ~ weight ~ bias ~ stride ~ padding ~ dilation ~ transposed ~ output_padding ~ groups = let out__ = CArray . make t 1 in stubs_convolution_overrideable ( CArray . start out__ ) input weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( if transposed then 1 else 0 ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copy_sparse_to_sparse_ self ~ src ~ non_blocking = let out__ = CArray . make t 1 in stubs_copy_sparse_to_sparse_ ( CArray . start out__ ) self src ( if non_blocking then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copysign self other = let out__ = CArray . make t 1 in stubs_copysign ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copysign_ self other = let out__ = CArray . make t 1 in stubs_copysign_ ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copysign_out ~ out self other = let out__ = CArray . make t 1 in stubs_copysign_out ( CArray . start out__ ) out self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copysign_scalar self other = let out__ = CArray . make t 1 in stubs_copysign_scalar ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copysign_scalar_ self other = let out__ = CArray . make t 1 in stubs_copysign_scalar_ ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let copysign_scalar_out ~ out self other = let out__ = CArray . make t 1 in stubs_copysign_scalar_out ( CArray . start out__ ) out self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let corrcoef self = let out__ = CArray . make t 1 in stubs_corrcoef ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cos self = let out__ = CArray . make t 1 in stubs_cos ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cos_ self = let out__ = CArray . make t 1 in stubs_cos_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cos_out ~ out self = let out__ = CArray . make t 1 in stubs_cos_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cosh self = let out__ = CArray . make t 1 in stubs_cosh ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cosh_ self = let out__ = CArray . make t 1 in stubs_cosh_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cosh_out ~ out self = let out__ = CArray . make t 1 in stubs_cosh_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cosine_embedding_loss ~ input1 ~ input2 ~ target ~ margin ~ reduction = let out__ = CArray . make t 1 in stubs_cosine_embedding_loss ( CArray . start out__ ) input1 input2 target margin ( Reduction . to_int reduction \|> Int64 . of_int ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cosine_similarity ~ x1 ~ x2 ~ dim ~ eps = let out__ = CArray . make t 1 in stubs_cosine_similarity ( CArray . start out__ ) x1 x2 ( Int64 . of_int dim ) eps ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cov self ~ correction ~ fweights ~ aweights = let out__ = CArray . make t 1 in stubs_cov ( CArray . start out__ ) self ( Int64 . of_int correction ) ( match fweights with \| Some v -> v \| None -> null ) ( match aweights with \| Some v -> v \| None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cross self other ~ dim = let out__ = CArray . make t 1 in stubs_cross ( CArray . start out__ ) self other ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cross_entropy_loss self ~ target ~ weight ~ reduction ~ ignore_index ~ label_smoothing = let out__ = CArray . make t 1 in stubs_cross_entropy_loss ( CArray . start out__ ) self target ( match weight with \| Some v -> v \| None -> null ) ( Reduction . to_int reduction \|> Int64 . of_int ) ( Int64 . of_int ignore_index ) label_smoothing ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cross_out ~ out self other ~ dim = let out__ = CArray . make t 1 in stubs_cross_out ( CArray . start out__ ) out self other ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let crow_indices self = let out__ = CArray . make t 1 in stubs_crow_indices ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let ctc_loss ~ log_probs ~ targets ~ input_lengths ~ target_lengths ~ blank ~ reduction ~ zero_infinity = let out__ = CArray . make t 1 in stubs_ctc_loss ( CArray . start out__ ) log_probs targets ( List . map Int64 . of_int input_lengths \|> CArray . of_list int64_t \|> CArray . start ) ( List . length input_lengths ) ( List . map Int64 . of_int target_lengths \|> CArray . of_list int64_t \|> CArray . start ) ( List . length target_lengths ) ( Int64 . of_int blank ) ( Reduction . to_int reduction \|> Int64 . of_int ) ( if zero_infinity then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let ctc_loss_tensor ~ log_probs ~ targets ~ input_lengths ~ target_lengths ~ blank ~ reduction ~ zero_infinity = let out__ = CArray . make t 1 in stubs_ctc_loss_tensor ( CArray . start out__ ) log_probs targets input_lengths target_lengths ( Int64 . of_int blank ) ( Reduction . to_int reduction \|> Int64 . of_int ) ( if zero_infinity then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_affine_grid_generator ~ theta ~ n ~ c ~ h ~ w = let out__ = CArray . make t 1 in stubs_cudnn_affine_grid_generator ( CArray . start out__ ) theta ( Int64 . of_int n ) ( Int64 . of_int c ) ( Int64 . of_int h ) ( Int64 . of_int w ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_affine_grid_generator_backward ~ grad ~ n ~ c ~ h ~ w = let out__ = CArray . make t 1 in stubs_cudnn_affine_grid_generator_backward ( CArray . start out__ ) grad ( Int64 . of_int n ) ( Int64 . of_int c ) ( Int64 . of_int h ) ( Int64 . of_int w ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_batch_norm input ~ weight ~ bias ~ running_mean ~ running_var ~ training ~ exponential_average_factor ~ epsilon = let out__ = CArray . make t 4 in stubs_cudnn_batch_norm ( CArray . start out__ ) input weight ( match bias with \| Some v -> v \| None -> null ) ( match running_mean with \| Some v -> v \| None -> null ) ( match running_var with \| Some v -> v \| None -> null ) ( if training then 1 else 0 ) exponential_average_factor epsilon ; 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 ; t0 , t1 , t2 , t3
let cudnn_batch_norm_backward input ~ grad_output ~ weight ~ running_mean ~ running_var ~ save_mean ~ save_var ~ epsilon ~ reservespace = let out__ = CArray . make t 3 in stubs_cudnn_batch_norm_backward ( CArray . start out__ ) input grad_output weight ( match running_mean with \| Some v -> v \| None -> null ) ( match running_var with \| Some v -> v \| None -> null ) ( match save_mean with \| Some v -> v \| None -> null ) ( match save_var with \| Some v -> v \| None -> null ) epsilon reservespace ; 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 cudnn_convolution self ~ weight ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic ~ allow_tf32 = let out__ = CArray . make t 1 in stubs_cudnn_convolution ( CArray . start out__ ) self weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ( if allow_tf32 then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_add_relu self ~ weight ~ z ~ alpha ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_cudnn_convolution_add_relu ( CArray . start out__ ) self weight z alpha ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_backward_input ~ self_size ~ grad_output ~ weight ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic ~ allow_tf32 = let out__ = CArray . make t 1 in stubs_cudnn_convolution_backward_input ( CArray . start out__ ) ( List . map Int64 . of_int self_size \|> CArray . of_list int64_t \|> CArray . start ) ( List . length self_size ) grad_output weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ( if allow_tf32 then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_backward_weight ~ weight_size ~ grad_output self ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic ~ allow_tf32 = let out__ = CArray . make t 1 in stubs_cudnn_convolution_backward_weight ( CArray . start out__ ) ( List . map Int64 . of_int weight_size \|> CArray . of_list int64_t \|> CArray . start ) ( List . length weight_size ) grad_output self ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ( if allow_tf32 then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_deprecated self ~ weight ~ bias ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic = let out__ = CArray . make t 1 in stubs_cudnn_convolution_deprecated ( CArray . start out__ ) self 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_deprecated2 self ~ weight ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic = let out__ = CArray . make t 1 in stubs_cudnn_convolution_deprecated2 ( CArray . start out__ ) self weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_relu self ~ weight ~ bias ~ stride ~ padding ~ dilation ~ groups = let out__ = CArray . make t 1 in stubs_cudnn_convolution_relu ( CArray . start out__ ) self weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_transpose self ~ weight ~ padding ~ output_padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic ~ allow_tf32 = let out__ = CArray . make t 1 in stubs_cudnn_convolution_transpose ( CArray . start out__ ) self weight ( List . map Int64 . of_int padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length padding ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( List . map Int64 . of_int stride \|> CArray . of_list int64_t \|> CArray . start ) ( List . length stride ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ( if allow_tf32 then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_transpose_backward_input ~ grad_output ~ weight ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic ~ allow_tf32 = let out__ = CArray . make t 1 in stubs_cudnn_convolution_transpose_backward_input ( CArray . start out__ ) grad_output weight ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ( if allow_tf32 then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_transpose_backward_weight ~ weight_size ~ grad_output self ~ padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic ~ allow_tf32 = let out__ = CArray . make t 1 in stubs_cudnn_convolution_transpose_backward_weight ( CArray . start out__ ) ( List . map Int64 . of_int weight_size \|> CArray . of_list int64_t \|> CArray . start ) ( List . length weight_size ) grad_output self ( 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 ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ( if allow_tf32 then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_transpose_deprecated self ~ weight ~ bias ~ padding ~ output_padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic = let out__ = CArray . make t 1 in stubs_cudnn_convolution_transpose_deprecated ( CArray . start out__ ) self 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 output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( List . map Int64 . of_int stride \|> CArray . of_list int64_t \|> CArray . start ) ( List . length stride ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_convolution_transpose_deprecated2 self ~ weight ~ padding ~ output_padding ~ stride ~ dilation ~ groups ~ benchmark ~ deterministic = let out__ = CArray . make t 1 in stubs_cudnn_convolution_transpose_deprecated2 ( CArray . start out__ ) self weight ( List . map Int64 . of_int padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length padding ) ( List . map Int64 . of_int output_padding \|> CArray . of_list int64_t \|> CArray . start ) ( List . length output_padding ) ( List . map Int64 . of_int stride \|> CArray . of_list int64_t \|> CArray . start ) ( List . length stride ) ( List . map Int64 . of_int dilation \|> CArray . of_list int64_t \|> CArray . start ) ( List . length dilation ) ( Int64 . of_int groups ) ( if benchmark then 1 else 0 ) ( if deterministic then 1 else 0 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_grid_sampler self ~ grid = let out__ = CArray . make t 1 in stubs_cudnn_grid_sampler ( CArray . start out__ ) self grid ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cudnn_grid_sampler_backward self ~ grid ~ grad_output = let out__ = CArray . make t 2 in stubs_cudnn_grid_sampler_backward ( CArray . start out__ ) self grid grad_output ; 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 cummax self ~ dim = let out__ = CArray . make t 2 in stubs_cummax ( CArray . start out__ ) self ( 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 cummax_out ~ values ~ indices self ~ dim = let out__ = CArray . make t 2 in stubs_cummax_out ( CArray . start out__ ) values indices self ( 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 cummaxmin_backward ~ grad input ~ indices ~ dim = let out__ = CArray . make t 1 in stubs_cummaxmin_backward ( CArray . start out__ ) grad input indices ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cummin self ~ dim = let out__ = CArray . make t 2 in stubs_cummin ( CArray . start out__ ) self ( 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 cummin_out ~ values ~ indices self ~ dim = let out__ = CArray . make t 2 in stubs_cummin_out ( CArray . start out__ ) values indices self ( 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 cumprod self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs_cumprod ( 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 cumprod_ self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs_cumprod_ ( 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 cumprod_backward ~ grad input ~ dim ~ output = let out__ = CArray . make t 1 in stubs_cumprod_backward ( CArray . start out__ ) grad input ( Int64 . of_int dim ) output ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cumprod_out ~ out self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs_cumprod_out ( CArray . start out__ ) 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 cumsum self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs_cumsum ( 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 cumsum_ self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs_cumsum_ ( 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 cumsum_out ~ out self ~ dim ~ dtype = let out__ = CArray . make t 1 in stubs_cumsum_out ( CArray . start out__ ) 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 cumulative_trapezoid ~ y ~ dim = let out__ = CArray . make t 1 in stubs_cumulative_trapezoid ( CArray . start out__ ) y ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let cumulative_trapezoid_x ~ y ~ x ~ dim = let out__ = CArray . make t 1 in stubs_cumulative_trapezoid_x ( CArray . start out__ ) y x ( Int64 . of_int dim ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let data self = let out__ = CArray . make t 1 in stubs_data ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let deg2rad self = let out__ = CArray . make t 1 in stubs_deg2rad ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let deg2rad_ self = let out__ = CArray . make t 1 in stubs_deg2rad_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let deg2rad_out ~ out self = let out__ = CArray . make t 1 in stubs_deg2rad_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let dequantize self = let out__ = CArray . make t 1 in stubs_dequantize ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let dequantize_tensors tensors = stubs_dequantize_tensors ( CArray . of_list t tensors \|> CArray . start ) ( List . length tensors ) \|> to_tensor_list
let det self = let out__ = CArray . make t 1 in stubs_det ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let detach self = let out__ = CArray . make t 1 in stubs_detach ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let detach_ self = let out__ = CArray . make t 1 in stubs_detach_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diag self ~ diagonal = let out__ = CArray . make t 1 in stubs_diag ( CArray . start out__ ) self ( Int64 . of_int diagonal ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diag_backward ~ grad ~ input_sizes ~ diagonal = let out__ = CArray . make t 1 in stubs_diag_backward ( CArray . start out__ ) grad ( List . map Int64 . of_int input_sizes \|> CArray . of_list int64_t \|> CArray . start ) ( List . length input_sizes ) ( Int64 . of_int diagonal ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diag_embed self ~ offset ~ dim1 ~ dim2 = let out__ = CArray . make t 1 in stubs_diag_embed ( CArray . start out__ ) self ( Int64 . of_int offset ) ( Int64 . of_int dim1 ) ( Int64 . of_int dim2 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diag_out ~ out self ~ diagonal = let out__ = CArray . make t 1 in stubs_diag_out ( CArray . start out__ ) out self ( Int64 . of_int diagonal ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diagflat self ~ offset = let out__ = CArray . make t 1 in stubs_diagflat ( CArray . start out__ ) self ( Int64 . of_int offset ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diagonal self ~ offset ~ dim1 ~ dim2 = let out__ = CArray . make t 1 in stubs_diagonal ( CArray . start out__ ) self ( Int64 . of_int offset ) ( Int64 . of_int dim1 ) ( Int64 . of_int dim2 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diagonal_backward ~ grad_output ~ input_sizes ~ offset ~ dim1 ~ dim2 = let out__ = CArray . make t 1 in stubs_diagonal_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 offset ) ( Int64 . of_int dim1 ) ( Int64 . of_int dim2 ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diff self ~ n ~ dim ~ prepend ~ append = let out__ = CArray . make t 1 in stubs_diff ( CArray . start out__ ) self ( Int64 . of_int n ) ( Int64 . of_int dim ) ( match prepend with \| Some v -> v \| None -> null ) ( match append with \| Some v -> v \| None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let diff_out ~ out self ~ n ~ dim ~ prepend ~ append = let out__ = CArray . make t 1 in stubs_diff_out ( CArray . start out__ ) out self ( Int64 . of_int n ) ( Int64 . of_int dim ) ( match prepend with \| Some v -> v \| None -> null ) ( match append with \| Some v -> v \| None -> null ) ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let digamma self = let out__ = CArray . make t 1 in stubs_digamma ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let digamma_ self = let out__ = CArray . make t 1 in stubs_digamma_ ( CArray . start out__ ) self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let digamma_out ~ out self = let out__ = CArray . make t 1 in stubs_digamma_out ( CArray . start out__ ) out self ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let dist self other = let out__ = CArray . make t 1 in stubs_dist ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div self other = let out__ = CArray . make t 1 in stubs_div ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_ self other = let out__ = CArray . make t 1 in stubs_div_ ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_out ~ out self other = let out__ = CArray . make t 1 in stubs_div_out ( CArray . start out__ ) out self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_out_mode ~ out self other ~ rounding_mode = let out__ = CArray . make t 1 in stubs_div_out_mode ( CArray . start out__ ) out self other rounding_mode ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_scalar self other = let out__ = CArray . make t 1 in stubs_div_scalar ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_scalar_ self other = let out__ = CArray . make t 1 in stubs_div_scalar_ ( CArray . start out__ ) self other ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_scalar_mode self other ~ rounding_mode = let out__ = CArray . make t 1 in stubs_div_scalar_mode ( CArray . start out__ ) self other rounding_mode ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_scalar_mode_ self other ~ rounding_mode = let out__ = CArray . make t 1 in stubs_div_scalar_mode_ ( CArray . start out__ ) self other rounding_mode ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0
let div_tensor_mode self other ~ rounding_mode = let out__ = CArray . make t 1 in stubs_div_tensor_mode ( CArray . start out__ ) self other rounding_mode ; let t0 = CArray . get out__ 0 in Gc . finalise C . Tensor . free t0 ; t0

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