o 2h@sdZddlZddlmZmZmZmZmZmZm Z m Z ddl Z ddl m Z ddlmZmZmZdZgdZeeeeZd$ded eeeefd eed ffd d Z d%ded eeeefdeed eefddZe d&dedededededeedededd eeeeeefffddZe d'dedededededeedededd eeeffddZ      d(dedededededeededed e eeeeeeffeeefffd dZd!ed eefd"d#ZdS))z Testing routines for opt_einsum.N)AnyDictListLiteralOptionalTupleUnionoverload) get_symbol) ArrayTypePathTypeTensorShapeTypeabcdefghijklmopqABC)rrrrrrrrrrrrrstringdimension_dictreturn.csVdurtg}|ddd}|D]}fdd|D}|t|qt|S)aBuilds random tensor shapes for testing. Parameters: string: List of tensor strings to build dimension_dict: Dictionary of index sizes, defaults to indices size of 2-7 Returns: The resulting shapes. Examples: ```python >>> shapes = build_shapes('abbc', {'a': 2, 'b':3, 'c':5}) >>> shapes [(2, 3), (3, 3, 5), (5,)] ``` Nz->r,csg|]}|qSr.0xrrM/var/www/html/chatgem/venv/lib/python3.10/site-packages/opt_einsum/testing.py (sz build_shapes..)_default_dim_dictsplitappendtuple)rrshapestermstermdimsrrr build_shapessr(array_functioncCsZ|dur td}|jj}g}t||dD]}|r!|||q|tqt|S)aBuilds random numpy arrays for testing. Parameters: string: List of tensor strings to build dimension_dict: Dictionary of index _sizes array_function: Function to build the arrays, defaults to np.random.rand Returns: The resulting views. Examples: ```python >>> view = build_views('abbc', {'a': 2, 'b':3, 'c':5}) >>> view[0].shape (2, 3, 3, 5) ``` Nnumpyr)pytest importorskiprandomrandr(r"r#)rrr)npviewsshaperrr build_views-s r2n regularityn_outd_mind_maxseed global_dimreturn_size_dictTcCdSNrr3r4r5r6r7r8r9r:rrr rand_equationOs r>FcCr;r<rr=rrrr>]s r cstd|durj|||d}ddt|D} gfddt|Dfdd } tjt| D]3\} } | |krS| | | 7<qBjd |} | | | vrmjd |} | | | vs`| | | 7<qB|rt |}jd |<t|D] } | | |7<q|7d jd d | }fdd| D}||f}|r|fS|S)a9Generate a random contraction and shapes. Parameters: n: Number of array arguments. regularity: 'Regularity' of the contraction graph. This essentially determines how many indices each tensor shares with others on average. n_out: Number of output indices (i.e. the number of non-contracted indices). Defaults to 0, i.e., a contraction resulting in a scalar. d_min: Minimum dimension size. d_max: Maximum dimension size. seed: If not None, seed numpy's random generator with this. global_dim: Add a global, 'broadcast', dimension to every operand. return_size_dict: Return the mapping of indices to sizes. Returns: eq: The equation string. shapes: The array shapes. size_dict: The dict of index sizes, only returned if ``return_size_dict=True``. Examples: ```python >>> eq, shapes = rand_equation(n=10, regularity=4, n_out=5, seed=42) >>> eq 'oyeqn,tmaq,skpo,vg,hxui,n,fwxmr,hitplcj,kudlgfv,rywjsb->cebda' >>> shapes [(9, 5, 4, 5, 4), (4, 4, 8, 5), (9, 4, 6, 9), (6, 6), (6, 9, 7, 8), (4,), (9, 3, 9, 4, 9), (6, 8, 4, 6, 8, 6, 3), (4, 7, 8, 8, 6, 9, 6), (9, 5, 3, 3, 9, 5)] ``` r*NrcSsg|]}dqS)r)r_rrrrsz!rand_equation..cs$i|]}t|jdqS))r r-randint)ri)r7r6r/rr s$z!rand_equation..c3s>tD]\}}|kr||Vq|V|VqdSr<) enumerater")rDix)r5output size_dictrrgens zrand_equation..genrrBr@z{}->{}rcs"g|] }tfdd|DqS)c3s|]}|VqdSr<r)rrGrIrr sz+rand_equation...)r#)roprKrrrs") r+r,r-r8rangerF permutationlistrCr joinformat)r3r4r5r6r7r8r9r:num_indsinputsrJrDrGwheregdimeqr$retr)r7r6r5r/rHrIrr>js: 0      pathcstdfdd|DS)zBuild random numpy arrays from a path. Parameters: path: The path to build arrays from. Returns: The resulting arrays. r*csg|]}jj|qSr)r-r.rr/rrrsz,build_arrays_from_tuples..)r+r,)rYrrZrbuild_arrays_from_tupless r[r<)NN).....)......)rrr?NFF)__doc__r-typingrrrrrrrr r+opt_einsum.parserr opt_einsum.typingr r r _valid_chars_sizesdictzipr strintr(r2boolr>r[rrrrs( , "    $ k