o Zh@sdZddlZddlZddlmZddZGdddeeZGd d d e e Z d d Z d dZ d'ddZd(ddZddZddZddZddddZddZdd Zd!d"Zd)d#d$Zd%d&ZdS)*zLAssorted utilities, which do not need anything other then torch and stdlib. N) _dtypes_implcCs2t|trdSzt|WdStyYdSw)NFT) isinstancestrlen Exception)seqr A/var/www/auris/lib/python3.10/site-packages/torch/_numpy/_util.py is_sequences   r c@ eZdZdS) AxisErrorN__name__ __module__ __qualname__r r r r r r c@r )UFuncTypeErrorNrr r r r rrrcCs |dur|j|kr||}|SN)dtypeto)tensorrr r r cast_if_needed s rcCs$t|jdkr|tj}|S)N)rZ _categoryrrZdefault_dtypesZ float_dtype)xr r r cast_int_to_float'srcCs@| |kr |ksntd|d||dkr||7}|S)Nzaxis z) is out of bounds for array of dimension r)r )axndimargnamer r r normalize_axis_index/s rFcst|ttfvrzt|g}Wn tyYnwtfdd|D}|sCtttt |t|krCr?t ddt d|S)a Normalizes an axis argument into a tuple of non-negative integer axes. This handles shorthands such as ``1`` and converts them to ``(1,)``, as well as performing the handling of negative indices covered by `normalize_axis_index`. By default, this forbids axes from being specified multiple times. Used internally by multi-axis-checking logic. Parameters ---------- axis : int, iterable of int The un-normalized index or indices of the axis. ndim : int The number of dimensions of the array that `axis` should be normalized against. argname : str, optional A prefix to put before the error message, typically the name of the argument. allow_duplicate : bool, optional If False, the default, disallow an axis from being specified twice. Returns ------- normalized_axes : tuple of int The normalized axis index, such that `0 <= normalized_axis < ndim` csg|]}t|qSr )r.0rrrr r \sz(normalize_axis_tuple..zrepeated axis in `z ` argumentz repeated axis) typetuplelistoperatorindex TypeErrorrsetmapint ValueError)axisrrZallow_duplicater r"r normalize_axis_tuple8s r/cCs(|dur|St|dkrtd|dS)Nrzdoes not handle tuple axisr)rNotImplementedErrorr.r r r allow_only_single_axises  r2csTtttfvr ftt|}t|t|fddt|D}|S)Ncs g|] }|vr dntqSr)nextr r.Zshape_itr r r#ts z expand_shape..)r$r&r%rr/iterrange)Z arr_shaper.Zout_ndimshaper r5r expand_shapems r9cCs<|durd|}||}|St|j|}||}|S)Nr3)expand contiguousr9r8Zreshape)rr.rr8r r r apply_keepdimsxs r<r1cGs*|durtdd|D}|dfS||fS)z#Flatten the arrays if axis is None.Ncss|]}|VqdSr)flatten)r!arr r r sz$axis_none_flatten..rr%)r.tensorsr r r axis_none_flattensrBcCs>tj}||j||dstd|jd|d|dt||S)aDtype-cast tensor to target_dtype. Parameters ---------- t : torch.Tensor The tensor to cast target_dtype : torch dtype object The array dtype to cast all tensors to casting : str The casting mode, see `np.can_cast` Returns ------- `torch.Tensor` of the `target_dtype` dtype Raises ------ ValueError if the argument cannot be cast according to the `casting` rule )castingzCannot cast array data from z to z according to the rule '')rZ can_cast_implrr)r)t target_dtyperCZcan_castr r r typecast_tensors  rGcstfdd|DS)Nc3s|] }t|VqdSr)rG)r!rErCrFr r r?sz#typecast_tensors..r@)rArFrCr rHr typecast_tensorssrIc CsHzt|}W|Sty#}zd|dt|d}t|d}~ww)Nzfailed to convert z! to ndarray. Internal error is: .)torchZ as_tensorrrr0)objreZmesgr r r _try_convert_to_tensors rNc Cst|tjr |}nt}tttjz t|}Wt|nt|wt ||}||j }|dkr@| d||j }|rF| }|S)aThe core logic of the array(...) function. Parameters ---------- obj : tensor_like The thing to coerce dtype : torch.dtype object or None Coerce to this torch dtype copy : bool Copy or not ndmin : int The results as least this many dimensions is_weak : bool Whether obj is a weakly typed python scalar. Returns ------- tensor : torch.Tensor a tensor object with requested dtype, ndim and copy semantics. Notes ----- This is almost a "tensor_like" coersion function. Does not handle wrapper ndarrays (those should be handled in the ndarray-aware layer prior to invoking this function). rr3)rrKZTensorZget_default_dtypeZset_default_dtyperZget_default_dtype_forZfloat32rNrrviewr8clone)rLrcopyZndminrZ default_dtypeZ ndim_extrar r r _coerce_to_tensors    rRcGsddlm}t|dkrtSt|dkr<|d}t||r!|jSt|tr:g}|D] }t|}||q*t|S|St|tsCJt|S)zHConvert all ndarrays from `inputs` to tensors. (other things are intact)r)ndarrayr) Z_ndarrayrSrr-rrr%ndarrays_to_tensorsappend)ZinputsrSZinput_resultZ sub_inputZ sub_resultr r r rTs      rTr)NF)NFr)__doc__r'rKrr r- IndexErrorr r) RuntimeErrorrrrrr/r2r9r<rBrGrIrNrRrTr r r r s(    -     8