o Ei@sddlZddlmZddlmZddlZddlmZddl mZ ej ddddd d Z ej dd dZejjej dddd d ddedeejefdedede jdejf ddZee_dS)N)partial)util)Unioncsdfdd S)Nint32cs|||dS)Ndtype)exprs_inexpr_outbackendrcr K/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/einx/op/arange.py s..)Nrr trr r rr r)tracerc sdttr tj|D]}t|tjjjrt dq||fD]}|D]}t|tjjj r6t dq(q"dd|D}t |dkrPt dt |t |dkr[|dj ndt |gd}t |gd}fdd }tjj||} tjj| } tjd d|Dfd d|D| gd \\} } t j|g| g|gd \} | tjj|fS) Nz&Marker in input expression not allowedzConcatenation not allowedcSs.g|]}t|tjjjrtjj|r|qSr ) isinstanceeinxexprstage3Axis is_marked.0rr r r s z!arange_stage3..r&Expected at most one marked axis, got rcsTt|tjjjr&tjj|r(tjjddtD}tjj|}|SdSdS)NcSsg|] }tjjddqS)Nr)rrrr)r_r r rr'sz2arange_stage3..replace..) rrrrrr Concatenationrange Composition)r)ndimr rreplace%szarange_stage3..replacecSsg|]}|qSr ) __deepcopy__raxisr r rr1scsg|] }j|jdqS)r)arangevaluer'r rr rr2s)r )rstrrr getallrrMarker ValueErrorr!lenr*rflattenr%demarkrearrange_stage3 unflatten) expr_inr r rrroot marked_axes expr_out_flatr%expr_out_flat_withconcattensorr r )r rr$r arange_stage3 sJ          r<Tc s:tjj||\}}tjj|}t|dkr1tjjtjj tjj |ddg|dg}t|ddkrDt dt|dt|ddkrWt dt|dtjj tjj |ddfdd}tjjtj|ddgtj|ddgdd|D||d dd \}}||fS) Nrrz%Expected 1 input expression, but got z&Expected 1 output expression, but got csn|d}dd|D}dd|D}t|dkr#tdt|t|t|}tjt|ggS)NrcSs*g|]}t|tjjjtjjjfr|qSr )rrrstage2 NamedAxis UnnamedAxisrr r rr^s z/parse..after_stage2..cSsg|] }tjj|r|qSr )rrr=rrr r rrcsr)r.r1r0rrEquationnpasarray)exprs1exprs2r out_axesmarked_out_axesr$marked_expr_outr r after_stage2\s zparse..after_stage2cSs4g|]\}}tjj|t|dtjfdddqS).N)depth1depth2)rrr@rArBnewaxis)rkvr r rrls"zparse..)cserI)ropr!_clean_description_and_parametersrstage1parse_opr1OpArgs get_unmarkedr0r# get_markedsolver@items) descriptionrO parametersrQrIr6r r rGrparseDs<       r]csdfdd S)Ncs|fi|SNr )r[r kwargsr r rrxsrr^r rr r rrxr)rrOr[r rrOr\returncKs0t|fd|i|\}}t||||d\}}|S)an-dimensional ``arange`` operation. *This function might be removed in a future version.* Runs ``arange`` for every axis in ``input``, and stacks the results along the single marked axis in ``output``. Always uses ``start=0`` and ``step=1``. The `description` argument must meet one of the following formats: 1. ``input -> output`` Runs ``backend.arange`` for every axis in ``input``, and stacks the results along the marked axis in ``output``. The values are stacked in the order that the axes appear in ``input``. 2. ``output`` Implicitly determines the input expression by removing the marked axis from ``output``. Example: ``a b [2]`` resolves to ``a b -> a b [2]`` Args: description: Description string in Einstein notation (see above). backend: Backend to use for all operations. cse: Whether to apply common subexpression elimination to the expressions. Defaults to True. graph: Whether to return the graph representation of the operation instead of computing the result. Defaults to False. **parameters: Additional parameters that specify values for single axes, e.g. ``a=4``. Returns: The result of the n-dimensional arange operation if `graph=False`, otherwise the graph representation of the operation. Examples: Arange two-dimensional coordinates: >>> tensor = einx.arange("a b [2]", a=5, b=6, backend="numpy") >>> tensor.shape (5, 6, 2) >>> tensor[2, 3] array([2, 3], dtype=int32) Arange two-dimensional coordinates with inverted coordinates (`Cartesian ordering `_: First axis of tensor corresponds to second coordinate along stacked axis and vice versa.): >>> tensor = einx.arange("a b -> b a [2]", a=5, b=6, backend="numpy") >>> tensor.shape (6, 5, 2) >>> tensor[2, 3] array([3, 2], dtype=int32) Arange one-dimensional coordinates: >>> einx.arange("a", a=5, backend="numpy").shape (5,) rOr+)r]r<)r[r rrOr\r6r r;r r rr)wsBr))r)T)r functoolsrrnumpyrAtypingr numpy.typingnptjitr< lru_cacher]traceback_utilfilterr,Backendbool ArrayLikeTensorr)r r r rs<     6 2  E