o EiS@sddlZddlmZddlZddlmZmZddlmZ ej dddddd Z ej d d d d Z ejjej ddddd ddedejdeejedfdede jdeejeejdfff ddZe e_ dS)N)util)UnionTuplecsdfdd S)Ncs|fdd|D|S)Ncg|]}|qSr.0xtrN/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/einx/op/rearrange.py .....r)exprs_in tensors_in exprs_outbackendcr rr  s..Nrr rrrr r sr)tracecs\ttkrtdtdttddtt|Dr-tdtdfddtDjd d tjd \t|}t d dDsZJt d d|DseJtt|kr|tdtdt|dt |}fdd|Dfdd|Dfddt|D}tj |||d }||fS)N Expected z input tensor(s), got css.|]}|D] }t|tjjjVqqdSr)all isinstanceeinxexprstage3Marker)r rootr rrr s z#rearrange_stage3..zMarker 'z' is not allowedc s(g|]\}}tjj||jdddqS) embedding rearrange)nameinit)rtracer call_factoryshape)r tensorr rrr rsz$rearrange_stage3..T)convert_scalarsr-cs|] }tjj|VqdSrrr r!is_flatr r rrr r$!csr/rr0r2rrr r$"r3zGot different number of input (z) and output expressions (z) (after flattening)cg|]}|qSrrr i)rrr r+rcr4rrr5)rrr r,rcs(g|]\}}}tj|||ddqS)r-r)rtranspose_broadcast)r expr_inr,expr_outr-rr r/s) len ValueErroranylistr zip all_to_tensorrflattenr assignment unflatten)rrrrexprs_out_flatindicestensorsr)rrrr rearrange_stage3s8      rFTcsecOstjj||\}}tjj|}t|dt|kr+tdt|ddt|tjj ddt |d|Ddd|dDdd| D|d dt|dt|d}|dt|d|t|dd}}||fS) Nrrz input tensors, but got cSsg|] \}}tj||qSrrr Equation)r r8 tensor_shaperrr rFs zparse..cSg|]}tj|qSrrI)r r9rrr rJrcSs4g|]\}}tjj|t|dtjfdddqS).N)depth1depth2)rr rJnpasarraynewaxis)r kvrrr rKs"rG) ropr!_clean_description_and_parametersr stage1parse_opr:r;solver>items) descriptionrH tensor_shapes parametersrUexprsrrrrr parse:s,    * r_csddfdd S)Nr-cs$|gfdd|DRi|S)Ncrrrrr rr rYrrr)r[rrEkwargsrrr rXsrrrrrr rXr)rrHr[rErrHr]return.cOsTt|gdd|DRd|i|\}}t||||d\}}t|dkr(|dS|S)aRearranges the input tensors to match the output expressions. Args: description: Description string for the operation in einx notation. Must not contain brackets. tensors: Input tensors or tensor factories matching the description string. backend: Backend to use for all operations. If None, determines the backend from the input tensors. Defaults to None. 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 rearrange operation if ``graph=False``, otherwise the graph representation of the operation. Examples: Transpose the row and column axes of a batch of images: >>> x = np.random.uniform(size=(4, 64, 48, 3)) >>> einx.rearrange("b h w c -> b w h c", x).shape (4, 48, 64, 3,) Insert new axis (repeats elements along the new axis): >>> x = np.random.uniform(size=(10, 10)) >>> einx.rearrange("a b -> a c b", x, c=100).shape (10, 100, 10,) Concatenate two tensors along the first axis: >>> a, b = ( ... np.random.uniform(size=(10, 10)), ... np.random.uniform(size=(20, 10)), ... ) >>> einx.rearrange("a b, c b -> (a + c) b", a, b).shape (30, 10,) Split a tensor: >>> x = np.random.uniform(size=(10, 2)) >>> a, b = einx.rearrange("a (1 + 1) -> a, a", x) >>> a.shape, b.shape ((10,), (10,)) Swap the first and last third of a tensor along a given axis: >>> x = np.arange(6) >>> einx.rearrange("(b + c + d) -> (d + c + b)", x, b=2, c=2) array([4, 5, 2, 3, 0, 1]) cSrLr)rr) get_shape)r r,rrr rrMzrearrange..rHr-rr)r_rFr:)r[rrHrEr]rrrrr r&VsB  r&r)rrnumpyrPtypingrr numpy.typingnptjitrF lru_cacher_traceback_utilfilterstrTensorBackendbool ArrayLiker&rrrr s>   - C