g^(hdZddlZddlZddlmZdZGddeeZGdd e e Z d Z d Z dd Zdd ZdZdZdZdddZdZdZdZddZdZy)zLAssorted utilities, which do not need anything other then torch and stdlib. N) _dtypes_implc\t|try t|y#t$rYywxYw)NFT) isinstancestrlen Exception)seqs P/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/torch/_numpy/_util.py is_sequencer s4#s C  s  ++c eZdZy) AxisErrorN__name__ __module__ __qualname__r rrrrc eZdZy)UFuncTypeErrorNrrrr rrrrrcJ| |j|k7r|j|}|SN)dtypeto)tensorrs r cast_if_neededr s& V\\U25! Mrctj|jdkr-|jtjj }|S)N)r _categoryrrdefault_dtypes float_dtype)xs r cast_int_to_floatr$'s;agg&* DD,,.:: ; HrcX| |cxkr|ksntd|d||dkr||z }|S)Nzaxis z) is out of bounds for array of dimension r)r)axndimargnames r normalize_axis_indexr)/s? ER $ %t#LTFSTT Av d  Irc jt|ttfvr tj|g}t|Dcgc]}t |||c}}|sJtttt|t|k7r|rtd|dtd|S#t $rY}wxYwcc}w)a Normalizes an axis argument into a tuple of non-negative integer axes. This handles shorthands such as ``1`` and converts them to ``(1,)``, as well as performing the handling of negative indices covered by `normalize_axis_index`. By default, this forbids axes from being specified multiple times. Used internally by multi-axis-checking logic. Parameters ---------- axis : int, iterable of int The un-normalized index or indices of the axis. ndim : int The number of dimensions of the array that `axis` should be normalized against. argname : str, optional A prefix to put before the error message, typically the name of the argument. allow_duplicate : bool, optional If False, the default, disallow an axis from being specified twice. Returns ------- normalized_axes : tuple of int The normalized axis index, such that `0 <= normalized_axis < ndim` zrepeated axis in `z ` argumentz repeated axis) typetuplelistoperatorindex TypeErrorr)rsetmapint ValueError)axisr'r(allow_duplicater&s r normalize_axis_tupler78s< Dz%& NN4()D DIb&r49I JD s3s3~#673t9D 1'*EF F_- - K   JsB!B0! B-,B-cF||St|dk7r td|dS)Nrzdoes not handle tuple axisr)rNotImplementedErrorr5s r allow_only_single_axisr;es, |  4yA~!">?? 7Nrct|ttfvr|f}t|t|z}t ||}t |}t |Dcgc]}||vrdn t|}}|Scc}w)Nr)r+r-r,rr7iterrangenext) arr_shaper5out_ndimshape_itr&shapes r expand_shaperDmsq Dz$&w4y3y>)H h /DIH;@? KR"*Q$x. 0 KE K L LsA2c|&d|z}|j|j}|St|j|}|j |}|S)Nr)expand contiguousrDrCreshape)rr5r'rCs r apply_keepdimsrJxsS |t u%002 MV\\40& Mrr:c:|td|D}|dfS||fS)z#Flatten the arrays if axis is None.c3<K|]}|jywr)flatten).0ars r z$axis_none_flatten..s7 7srr,)r5tensorss r axis_none_flattenrSs+ |7w77z}rc tj}||j||std|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 '')r can_cast_implrr0r)t target_dtyperUcan_casts r typecast_tensorr[s_,))H AGG\7 ;*177)4~5gYa A   !\ **rc0tfd|DS)Nc38K|]}t|ywr)r[)rNrXrUrYs r rPz#typecast_tensors..sLqL':LsrQ)rRrYrUs ``r typecast_tensorsr^s LGL LLrc tj|}|S#t$r"}d|dt|d}t |d}~wwxYw)Nzfailed to convert z! to ndarray. Internal error is: .)torch as_tensorr rr9)objremesgs r _try_convert_to_tensorrfsS(% M (#C5(J3q6(RST!$''(s A?Act|tjr|}nktj}tjt j tj t|}tj|t||}||jz }|dkDr!|jd|z|jz}|r|j}|S#tj|wxYw)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). rrF)rraTensorget_default_dtypeset_default_dtyperget_default_dtype_forfloat32rfrr'viewrCclone)rcrcopyndminr default_dtype ndim_extras r _coerce_to_tensorrss6#u||$ //1   B B5== QR 3+C0F  # #M 2FE *F$JA~TJ.=>  M  # #M 2s ) CC5cRddlm}t|dk(r tSt|dk(r_|d}t ||r |j St |t r0g}|D]}t|}|j| t |S|St |t sJt|S)zHConvert all ndarrays from `inputs` to tensors. (other things are intact)r)ndarrayr) _ndarrayrurr4rrr,ndarrays_to_tensorsappend)inputsruinput_result sub_input sub_results r rwrws! 6{a| V  fg &==  &F# * 0;  j) *= M&%((("6**rr)NF)NFr)__doc__r.rarr r4 IndexErrorrr0 RuntimeErrorrrr$r)r7r;rDrJrSr[r^rfrsrwrrr rs  J  Y   *Z&*+@M5p+r