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See collapse_view for the corresponding view operation. rrN)rrr)rr'r(r7rr3rrrrs ")tensorsrUrc Cs|dj}d}t|D]P\}}tt||jD]6\}\}}||krL||}q.||kr.td|dq.qt|dj} || |<t|d| t| dS)Nrz0Sizes of tensors must match except in dimension zV. Expected {common_length} but got {length} for tensor number {tensor_idx} in the listr ) rrrErrcopyrrr0) rbrUrZ concat_lengthZ tensor_idxZtensorrZ common_lengthr2r3rrr _cat_metas"   rdcCs t||Sr)rr)rbrUrrr _cat_atensrez Concatenates tensors along the specified dimension. 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Where pred is true the result contains the element from a, and where pred is false the result contains the element from b. z0where(Tensor pred, Tensor a, Tensor b) -> Tensor)rrrcCs6t|tstt|tjstt|}t|||dSN)rr)rrrrrrrrrrrrrr_convert_element_type_metaSs rpc Cst|sd}n2z |j}Wn&tk r@}zd}W5d}~XYnXtj||j||d}tt||W5QRSQRXdS)NF)rr requires_grad) rZ is_grad_dtyperq ExceptionrZ empty_likerrr)rrrqeresultrrr_convert_element_type_aten]s   ruz6 Creates a copy of a tensor with the given dtype. z:convert_element_type(Tensor a, ScalarType dtype) -> Tensor)rrrcCs4t|tstt|ttjfs"tt|t|dS)N)r) rrrrrrrrZcanonicalize_devicerrrrr_device_put_meta}srwcCs ||Srtorvrrr_device_put_atensrzz5 Creates a copy of a tensor on the given device. z-device_put(Tensor a, Device device) -> TensorcCst|j}t|dSr")r dtype_to_typerr)r number_typerrr _item_metas r}z< Converts a tensor with one element to a Python number. zitem(Tensor a) -> Scalar)rrcCst|}t|dSr"rr{rrr|rrr_maximum_value_metas rrcCs6|tjkrdS|js|jr&t|jSt|jSdS)NT)rrris_floating_pointfinfomaxiinforrrr_maximum_value_atens    rz2 Return the maximum finite value for a dtype. z)maximum_value(ScalarType dtype) -> ScalarcCst|}t|dSr"r~rrrr_minimum_value_metas rcCs6|tjkrdS|js|jr&t|jSt|jSdSr)rrrrrr.rrrrr_minimum_value_atens    rz2 Return the mimimum finite value for a dtype. z(minium_value(ScalarType dtype) -> ScalarcCst|j}t|||dSrn)rr0rrrorrr_to_dtype_metas rcCs ||Srrx)rrrrr_to_dtype_atensrzA Creates a contiguous copy of a tensor with the given dtype. z.to_dtype(Tensor a, ScalarType dtype) -> TensorrcCsLt|tstt|tst||krHd||}t||S)Nz>Attempting to copy {0} elements to a tensor with {1} elements!)rrrr/r+r)rrr1rrr _copy_to_metas rcCs ||Sr)Zcopy_rrrr _copy_to_atensrz; Copies the data in b to a and returns the modified a. z-copy_to(Tensor(a!) a, Tensor b) -> Tensor(a!)cCs ||SrZresize_rfrrr _resize_meta-srcCs ||Srrrfrrr _resize_aten1srz Gives a tensor with no elements a new shape, returning the modified tensor. The tensor's strides are contiguous and its values are unitialized. z2resize(Tensor(a!) a, SymInt[] shape) -> Tensor(a!) output_dtypecCsBt|tst|dkr|j}t|j|}t|t|||j dS)z\ Meta function for single output reduction operations Stride logic is incorrect Nr) rrrrrZcompute_reduction_output_shaperrr0r)inprArZ output_shaperrr_reduction_metaEsrcCs.t|jrt|j}n|j}t|||dS)Nr)rrrrr)rrAZ correctionrrrr_var_reduction_metaVs rzx Computes the sum of elements in the input tensor over the list of dimensions specified in the dim argument z| Computes the product of elements in the input tensor over the list of dimensions specified in the dim argument z Computes the maximum value of elements in the input tensor over the list of dimensions specified in the dim argument z Computes the minimum value of elements in the input tensor over the list of dimensions specified in the dim argument ze Computes the biased variance of x over the list of dimensions specified in the dim argument )rcCst|dt|tj|dS)Creates a reduction prim.zE(Tensor inp, int[]? dims, *, ScalarType? output_dtype=None) -> Tensorr)rrrrrrrrrr_make_reduction_primssrcCst|dt|tj|dS)rzU(Tensor inp, int[]? dims, *, int correction, ScalarType? output_dtype=None) -> Tensorr)rrrrrrrr_make_var_reduction_prim~srr)rrArrcCsN|dk r:t|ddD] }|dks$ttj|||d}q|Stj|||dSdS)NT)reverserr)r=rrr)rrArdrrr _prod_atens  rz Constructs a 1-D tensor with values from the interval [start, end) taken with common difference `step` beginning from `start`. )r'r(rMrrrqrcsttr"ttr"t|tr"tt|dkddttoLtfddt|dkrpkp~|dko~kdd|dk rn(tdd|fDrtj }nt }|dkrt n|}t |f}t |}t||||dS) NrcSsdS)Nzstep must be nonzerorrrrrrrz_arange_meta..csddS)Nzunsupported range: z -> rrr(r'rrrrcSsdS)Nz7upper bound and lower bound inconsistent with step signrrrrrrrcss|]}t|tVqdSr)rr)rrrrrrsz_arange_meta..r)rcomplexrrrrFrCallrZint64Zget_default_dtyperr7r0r)r'r(rMrrrqrrrrr _arange_metas6   rc Cstj|||||tjd|dS)NF)rrZlayoutZ pin_memoryrq)rrZstrided)r'r(rMrrrqrrr _arange_atens rzqarange(Scalar start, Scalar end, Scalar step, *, ScalarType? dtype, Device? device, bool requires_grad) -> Tensor)rrrrqrcCst|}t||||dSNrrr0r)rrrrqrrrr _empty_meta s rcCstj||||dSN)rrrq)rempty)rrrrqrrr _empty_aten srz\ Creates a tensor with uninitialized values and the specified shape, dtype, and device. zWempty(SymInt[] shape, *, ScalarType dtype, Device device, bool requires_grad) -> Tensor)rrrrrqrcCst||||dSrr_)rrrrrqrrr_empty_strided_meta# srz1 Creates a tensor with uninitialized values. zqempty_strided(SymInt[] shape, SymInt[] strides, *, ScalarType dtype, Device device, bool requires_grad) -> Tensor)r fill_valuerrrqrcCst|}t||||dSrr)rrrrrqrrrr _full_meta< s rcCstj|||||dSr)rfull)rrrrrqrrr _full_atenH s rzi Creates a tensor filled with the given fill value, and with the specified shape, dtype, and device. zifull(SymInt[] shape, Scalar fill_value, *, ScalarType dtype, Device device, bool requires_grad) -> Tensor)rrrrrqrcCs.t|}|dkr|}t||||dS)Nr)rrr)rrr/rr)rrrrrqrrrr_full_like_metad s  rcCstj|||||dSr)r full_like)rrrrrqrrr_full_like_atens s rz Creates a tensor filled with the given fill value, and the same shape, dtype, and device as the given tensor by default. The dtype and device settings can be overridden by specifying them explicitly. zhfull_like(Tensor a, Scalar fill_value, *, ScalarType dtype, Device device, bool requires_grad) -> Tensor)scalarrrrcCs g}t|}t|||||dSrr)rrrrrrrr_scalar_tensor_meta s rcCs4t|tr$|dkst|s$tdtj|||dS)Nz-Complex scalar requires complex tensor dtype.r)rrrr TypeErrorrr)rrrrrr_scalar_tensor_aten s rzG Wraps a Number into a Tensor with the specified dtype and device. zQscalar_tensor(Scalar s, *, ScalarType? dtype=None, Device? device=None) -> Tensor)A full_matricesrcCst|dtj|jddd|j}|dd}|dd\}}t||}|||rV|n|f}tj|dd}t|||j|jd} ||f} t| } t| | | rt |jn|j|jd} ||r|n||f} |jj dk}tj| |d}t| ||j|jd}| | |fS)Nz linalg.svdF)Zallow_low_precision_dtypes)Z row_majorrZcuda) rZcheck_is_matrixZcheck_fp_or_complexrrr.r0rrrrr)rrZA_shapebatchmnkZshape_UZ strides_UUZshape_SZ strides_SSZshape_VhZis_cudaZ strides_VhZVhrrr _svd_meta s,      rcCstjj||dS)N)r)rZlinalgr)rrrrr _svd_aten srz Returns the SVD of a matrix or batch of matrices. 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Only supports floating-point types. zrnormal(SymInt[] shape, *, Scalar mean, Scalar std, ScalarType dtype, Device device, bool requires_grad) -> Tensor)rlowhighrrrcCst|}t||||dSrr)rrrrrrrrr _uniform_meta1 s rcCs tj|||d}||||Sr)rrZuniform_)rrrrrrrrr _uniform_aten= s rzN Constructs a tensor filled with values drawn uniformly from low to high. z^uniform(SymInt[] shape, *, Scalar low, Scalar high, ScalarType dtype, Device device) -> Tensor)rrUonesidedrcCsjt|j|}t|t|j}|rB|d}||dd||<t|j}t|}t ||||j dS)Nrrrr) rr>rvalidate_no_repeating_dimsrrZcorresponding_complex_dtyperr0rr)rrUrrZlast_dimrrrrr _fft_r2c_meta^ s    rcCsd}t||||SNr)rZ_fft_r2c)rrUr normalizationrrr _fft_r2c_atenq srz7 Performs a real to complex Fast Fourier Transform z;fft_r2c(Tensor self, *, int[] dim, bool onesided) -> Tensor)rrUforwardrcCs<t|j|}t||j}t|}t|||j|jdSr) rr>rrrr0rrr)rrUrrrrrr _fft_c2c_meta s  rcCsd}t||||Sr)rZ_fft_c2c)rrUrrrrr _fft_c2c_aten srz> Performs either a Fast Fourier Transform, or its inverse z:fft_c2c(Tensor self, *, int[] dim, bool forward) -> Tensor)rrU last_dim_sizercCsVt|j|}t|t|j}|||d<t|j}t|}t ||||j dS)Nrr) rr>rrrrrrr0rr)rrUrrrrrrr _fft_c2r_meta s     rcCsd}t||||Sr)rZ_fft_c2r)rrUrrrrr _fft_c2r_aten srz? Performs a complex to real Inverse Fast Fourier Transform zBfft_c2r(Tensor self, *, int[] dim, SymInt last_dim_size) -> Tensor)N)N)N)N)rr)rr(K contextlib itertoolsrFrweakrefenumr functoolsrrtypingrrrrr r r r rZtorch._prims_commonZ _prims_commonrZ torch.libraryr rZtorch._CrZtorch._prims.nvfuser_primsrrrrrrrrrrrrZtorch._prims_common.wrappersrrrrZtorch.overridesr r!Ztorch.utils._pytreer"r#r$ZlibraryLibraryrrrrr__all__rrrrrrrrrrrr&rr'rr(r)r*r+r,r-r.specialr3r4Zi0r/Zi0er0i1r1Zi1er2r5rr6r7rZ_conj_physicalrr8r9r:Zerfinvr;r<r=r>r?rrr@rAZVIEWrBrCrrDrErFrGrHrJrKrIrLrorMrNrOrPrQrRrSrTrUrVrWrXrYrZrr[r\r]r^r_r`rarbrcZgammaincrdZ gammainccrerfrgr rhr rirjrkrlrmrnZbitwise_left_shiftrpZbitwise_right_shiftrqrrrsrtrrrZ_as_strided_docrur!r&Z_broadcast_in_dim_docrvr4r5r8Z_collapse_view_docrwr9Z _conj_docrxryrzrB__annotations__rJrNZ _slice_docrRrTZ_slice_in_dim_docr{rXrYZ_split_dim_docr|rZr[Z _squeeze_docr}r]r^Z_transpose_docr~r`raZ _view_of_docrrrdreZ_cat_docrrgrjZ _reshape_docrrkZ_rev_docZfliprrmZ _where_docrrpruZ_convert_element_type_docrrwrzZ_device_put_docrr}Z _item_docrrrZ_maximum_value_docrrrZ_minimum_value_docrrrZ _to_dtype_docrrrZ _copy_to_docZINPLACErrrZ _resize_docrrrZ_sum_docZ _prod_docZ _amax_docZ _amin_docZ_var_docrrrrrrrrZ _arange_docrrrrrrZ _empty_docrrZ_empty_strided_docrrrZ _full_docrrrZ_full_like_docrrrZ_scalar_tensor_docrrrZ_svd_docrfloatrrrZ _normal_docrrrZ _uniform_docrrrZ _fft_r2c_docrrrZ _fft_c2c_docrrrZ _fft_c2r_docrrrrrs  (   4 % - ;   O                /    :     W    9      ,        "                 '         "