pi"ddlmZddlmZmZmZmZddlZddlZddl m Z ddl m Z er ddl mZddlZGddZGd d eZy) ) annotations)AnyOptional TYPE_CHECKINGUnionN)ir)V)SequenceceZdZdZ d ddZdddZeddZeddZddZ ddZ dd Z dd Z dd Z dd Zdd ZdddZddZy) KernelInputsz Class to store and provide access to input nodes for kernels. This class takes in a tuple of input nodes and provides methods to access information about these nodes, such as their device type and device. Nc`||_d|_||ni|_t|dkDsJdy)z Initialize with a tuple of input nodes. Args: input_nodes: A tuple of input nodes to store Nrz Expected at least one input node) _input_nodes _device_name_scalarslen)self input_nodesscalarss _/opt/services/ai/voice_agent/venv/lib/python3.12/site-packages/torch/_inductor/kernel_inputs.py__init__zKernelInputs.__init__s;(+/#*#6B ;!#G%GG#c| |jSt|jt|k(s)Jdt|jdt||Dcgc]}|j|c}Scc}w)a7 Return the stored input nodes, optionally reordered. Args: reorder: Optional sequence of indices to reorder the nodes. For example, (2, 0, 1) would return nodes in that order. Returns: The tuple of input nodes, optionally reordered zReorder length mismatch:  vs )rr)rreorderis rnodeszKernelInputs.nodes(sz ?$$ $4$$%W5 'D,=,=(>'?tCL> R 5/66!!!$666sA6c,t|jS)zh Get the number of input nodes. Returns: The number of input nodes )rrrs rcountzKernelInputs.count:s4$$%%rcFtj|jdS)z| Get the device type of the first node. Returns: The device type (e.g., 'cuda', 'cpu') r)rget_device_typerrs r device_typezKernelInputs.device_typeDs !!$"3"3A"677rc<|jdjS)zn Get the device of the first node. Returns: The device of the first node r)r get_devicers rdevicezKernelInputs.deviceOs  #..00rc|jO|j}|jdk(r0tjj |}|j |_|jS)zu Get the device name information. Returns: A tuple of (gpu_name, vendor, model) cuda)rr%r"torchr'get_device_properties gcnArchName)rr%device_propertiess r device_namezKernelInputs.device_nameXsX    $[[]F6)$)JJ$D$DV$L!$5$A$A!   rc:td|jDS)z Get the symbolic shapes of all input nodes. Returns: A tuple of shape tuples for each input node c3<K|]}|jywN)get_size.0nodes r z/KernelInputs.shapes_symbolic..msCT]]_Ctuplerrs rshapes_symboliczKernelInputs.shapes_symbolicfsC1B1BCCCrc:td|jDS)z Get the size hints for shapes of all input nodes. Returns: A tuple of shape tuples with integer hints for each input node c3K|]_}tjjj|j t j jjayw)fallbackN) r graphsizevars size_hintsr0r( _inductorconfigunbacked_symint_fallbackr1s rr4z-KernelInputs.shapes_hinted..vsP  GG   ' ' //HH (  A%A'r6rs r shapes_hintedzKernelInputs.shapes_hintedo& ))    rc:td|jDS)z Get the symbolic strides of all input nodes. Returns: A tuple of stride tuples for each input node c3<K|]}|jywr/) get_strider1s rr4z0KernelInputs.strides_symbolic..sE4T__&Er5r6rs rstrides_symboliczKernelInputs.strides_symbolic~sE43D3DEEErc:td|jDS)z Get the size hints for strides of all input nodes. Returns: A tuple of stride tuples with integer hints for each input node c3K|]_}tjjj|j t j jjaywr;) r r=r>r?rHr(r@rArBr1s rr4z.KernelInputs.strides_hinted..sQ  GG   ' '!//HH (  rCr6rs rstrides_hintedzKernelInputs.strides_hintedrErc:td|jDS)zx Get the dtypes of all input nodes. Returns: A tuple of dtypes for each input node c3<K|]}|jywr/) get_dtyper1s rr4z&KernelInputs.dtypes..sD$T^^%Dr5r6rs rdtypeszKernelInputs.dtypessD$2C2CDDDrc<|j|jS)z Get the dtype of a specific input node. Args: idx: Index of the node to get the dtype from (default: 0) Returns: The dtype of the specified input node )rrO)ridxs rdtypezKernelInputs.dtypes  %//11rcR||jvs Jd|d|j|S)z Get the scalar value for a given name. Args: name: Name of the scalar to get Returns: The scalar value zScalar z not found, but required)r)rnames r get_scalarzKernelInputs.get_scalars4t}}$Nv5M&NN$}}T""rr/)r list[Any]r&Optional[dict[str, Union[float, int]]])rzOptional[Sequence[int]]returnrW)rYint)rYz Optional[str])rYz torch.device)rYztuple[tuple[Any, ...], ...])rYztuple[tuple[int, ...], ...])rYz%tuple[tuple[sympy.Integer, ...], ...])rYztuple[torch.dtype, ...])r)rRrZrYz torch.dtype)rUstrrYzUnion[float, int])__name__ __module__ __qualname____doc__rrpropertyrr"r%r,r8rDrIrLrPrSrVrrr r s;?HH8H 7$&&881 !D  F  E 2 #rr cVeZdZdZ d dfd Z ddZd dZd dZxZS) MMKernelInputsz Specialized KernelInputs for matrix multiplication operations. Provides additional methods to access M, N, K dimensions. cTt|||t|jdk\sJd||}}|dkr|t|z }|dkr|t|z }d|cxkrt|ks nJd|d|cxkrt|ks nJd|||_||_y)z Initialize with a tuple of input nodes. By default, we assume the last 2 input nodes are mat1 and mat2, but the caller can adjust when necessary zExpected at least 2 input nodesrzInvalid mat1_idx: zInvalid mat2_idx: N)superrrr _mat1_idx _mat2_idx)rrrmat1_idxmat2_idxm1_idxm2_idx __class__s rrzMMKernelInputs.__init__s g.4$$%*M,MM*"8 a< c+& &F a< c+& &FF-S--N1CH:/NN-F-S--N1CH:/NN-!!rcl|j|j}|j|j}|jd}|jd}|jd}|jd}tj j j|||||fS)a Get the symbolic M, N, K dimensions for matrix multiplication. Handles both 2D (MM) and 3D (BMM) tensors. M is extracted from the second-to-last dimension of the first operand (mat1). N is extracted from the last dimension of the second operand (mat2). K is extracted from the last dimension of the first operand (mat1). Returns: A tuple of (M, N, K) dimensions )rrgrhr0r r=r> check_equals)rmat1mat2mknk0s r mnk_symboliczMMKernelInputs.mnk_symbolicszz|DNN+zz|DNN+ MMOB  MMOB  MMOB ]]_R  %%a,1ayrc^|j}||j||jfS)zj Get the mat1 and mat2 nodes. Returns: A tuple of (mat1, mat2) nodes )rrgrh)rrs rmat1mat2zMMKernelInputs.mat1mat2s, T^^$eDNN&;;;rc|j}||j}||j}|d}|d}|d}|d}||k(s Jd|d||||fS)a  Get the hinted M, N, K dimensions for matrix multiplication. Handles both 2D (MM) and 3D (BMM) tensors. Uses shapes_hinted from the base class to get integer hints for dimensions. Returns: A tuple of (M, N, K) dimensions as integers rorpzK dimensions don't match: r)rDrgrh)r hinted_shapes mat1_shape mat2_shapertrurvk_checks r mnk_hintedzMMKernelInputs.mnk_hinteds**, "4>>2 "4>>2 rN rN rNR.G|J9!D JJ|1ayr)Nrorp)rrWrrXrirZrjrZ)rYz2tuple[sympy.Integer, sympy.Integer, sympy.Integer])rYztuple[Any, Any])rYztuple[int, int, int]) r\r]r^r_rrxrzr __classcell__)rms@rrcrcsV;? ""8" "  "@ ;4<rrc) __future__rtypingrrrrr(torch._inductor.configtorch._inductorrtorch._inductor.virtualizedr collections.abcr sympyr rcrarrrs@"66 )(e#e#P`\`r