o Xi!@sddlmZddlZddlmZmZddlZddlm Z m Z d=d d Z d>d?ddZ d@ddZ dAddZdBdCd!d"Zddd#dDd(d)ZdEd+d,ZdFd-d.ZdGd1d2ZdHd6d7ZdId;d<ZdS)J) annotationsN)CallableSequence)ir optimizernodesSequence[ir.Node]returnNonecCsJ|r!|dj}|r|D] }||vr|q dS|D]}|qdSdS)z>Display a list of nodes in the order they appear in the graph.rN)graphdisplay)rr noderQ/home/ubuntu/.local/lib/python3.10/site-packages/onnxscript/rewriter/_ir_utils.py display_nodes s   rTxir.Value | ir.Nodebackwardbool depth_limitintcsbgdfdd t|tjr|dnt|tjr+|dur+|dtdS)z[Display the (backward or forward) subgraph from a given value or node upto a certain depth.r ir.Nodecs|vrdS||krBr,|jD]}|dur)|dur)||dqdS|jD]}|D] \}}||dq5q/dSdS)N)appendinputsproduceroutputsuses)r depthinpoutconsumer_rrslicevisitrrr& s    zdisplay_slice..visitrN)r r) isinstancerNodeValuerr)rrrrr$r display_slices   r*valueir.Valueir.TensorProtocol | NonecCs"|}|durt|g|jSN)rrbasic_constant_propagation const_value)r+r rrrget_const_value5s r1valir.Value | Nonenp.ndarray | NonecCs@|durdSt|}|durz|WStyYdSwdS)aConvenience wrapper to get (optional) numpy value from an optional IR Value. This is intended for use in optimizations/rewriting. Note that this does not yet handle the distinction between inputs with default values (values that are both graph inputs and graph initializers), which should not be treated as a constant, and true constant values. The caller should make the distinction, as a value does not contain enough information to determine this. (TODO) N)r1numpyFileNotFoundError)r2r0rrrget_numpy_value<s   r7rankint | Sequence[int] | NonecCs^t|}|dur-|jdkr-|}|dust|tr!|j|kr!|St|tr-|j|vr-|SdS)aReturns element of a single element tensor constant value, and None otherwise. If an int rank is specified, it checks that the value has the given rank. If the rank is a sequence of ints, it checks that the value has one of the given ranks. Thus, `rank=0` checks for a scalar, `rank=1` checks for a 1D tensor, and `rank=(0,1)` checks for either a scalar or a 1D tensor. Nr)r7sizeitemr'rndimr)r2r8np_valr+rrrget_singleton_valueQs r>)rtolr8expectedfloat | int | Callabler? float | NonecCsVt||d}|dur dSt|r||St|tr||kS|dus#Jtj|||dS)z[Returns True if the value is a single element tensor with given value, and False otherwise.)r8NF)rel_tol)r>callabler'rmathisclose)r2r@r?r8scalarrrris_singleton_valueds   rH list[int]cCsd|durdSt|jtjsdSt|}|durdS|jt|ks(|jjtjj kr*dS| }||kS)zUReturns True if the value is a 1d int64 tensor with given value, and False otherwise.NF) r'typer TypeProtocolr7r:lendtypeDataTypeINT64tolist)r2r@r=valuesrrr is_1d_valuexsrRcCs&|durdS|j}|duo||kS)zZReturns True if the value is statically known to have the given rank, and False otherwise.NFshaper8)r+r8rTrrrhas_ranksrUdimir.SymbolicDim | int | NonecCsR|durdS|j}|durdS|dkr||7}|dks#||kr%dS||S)zPReturns the value of the given dimension, or None if it is not statically known.NrrS)r+rVrTrrrget_dims rXshape1ir.Shape | Noneshape2cCs0|dus|dur dS|s|rdS||kS)z.Check if two shapes are semantically the same.NF)has_unknown_dim)rYr[rrr same_shapes r]dim1ir.SymbolicDim | intdim2cCspt|t|ur dSt|trt|tr||kSt|tjr$t|tjs&J|jdus0|jdur2dS|j|jkS)z2Check if two dimensions are semantically the same.FN)rJr'rr SymbolicDimr+)r^r`rrrsame_dims rb)rrr r )Tr)rrrrrrr r )r+r,r r-)r2r3r r4r.)r2r3r8r9) r2r3r@rAr?rBr8r9r r)r2r3r@rIr r)r+r3r8rr r)r+r3rVrr rW)rYrZr[rZr r)r^r_r`r_r r) __future__rrEtypingrrr5np onnxscriptrrrr*r1r7r>rHrRrUrXr]rbrrrrs$