[^(h17dZddlmZddlZddlZddlZddlmZmZddlm Z ddl Z ddl m Z ddl m Z ddlmZej d Zd d hZej&Gd d Zddd ddZdd ddZd dZ d! d"dZdZd#dZd$dZd%dZd&dZd'dZd(dZd(dZ d(dZ!y))zFUtilities for manipulating the torch.Graph object and the torchscript.) annotationsN)IterableSequence)Any)_C)GLOBALS) registrationz^(.+)_(([ifstgz])|(ty))$inplaceatenceZdZUdZded<ded<ded<ded <d ed <d ed <ded<ej eZded<ddZ dd ddZ ddddZ e Z dd ddZ y) GraphContextaExtra context for symbolic functions with all methods from torch.Graph. NOTE: This class is not meant for external consumption. Please do not depend on it outside of torch.onnx as the interface may evolve. Attributes: graph: The _C.Graph being constructed. block: The current _C.Block being constructed. opset: The opset version. original_node: Current node that is being converted from. params_dict: Mapping from graph initializer name to IValue. env: Mapping from Torch domain graph Value to ONNX domain graph Value. values_in_env: Set of all values in env, for constant-time lookups. new_nodes: List that tracks all new nodes that are added (used to make sure metadata is propagated to all new nodes). z_C.Graphgraphz_C.Blockblockintopset_C.Node original_nodezdict[str, _C.IValue] params_dictzdict[_C.Value, _C.Value]envz set[_C.Value] values_in_env)default_factoryz list[_C.Node] new_nodesc.t|j|SN)getattrr)selfnames \/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/torch/onnx/_internal/jit_utils.py __getattr__zGraphContext.__getattr__7stzz4((outputsc&t||g|d|i|S)aCreates an ONNX operator "opname", taking "raw_args" as inputs and "kwargs" as attributes. The set of operators and the inputs/attributes they take is documented at https://github.com/onnx/onnx/blob/master/docs/Operators.md Args: opname: The ONNX operator name, e.g., `Abs` or `Add`, or an operator qualified with a namespace, e.g., `aten::add`. raw_args: The inputs to the operator; usually provided as arguments to the `symbolic` definition. outputs: The number of outputs this operator returns. By default an operator is assumed to return a single output. If `outputs` is greater than one, this functions returns a tuple of output `Value`, representing each output of the ONNX operator in order. kwargs: The attributes of the ONNX operator, whose keys are named according to the following convention: `alpha_f` indicates the `alpha` attribute with type `f`. The valid type specifiers are `f` (float), `i` (int), `s` (string) or `t` (Tensor). An attribute specified with type float accepts either a single float, or a list of floats (e.g., you would say `dims_i` for a `dims` attribute that takes a list of integers). Returns: The value representing the single output of this operator (see the `outputs` keyword argument for multi-return nodes). r#)_add_op)ropnamer#raw_argskwargss ropzGraphContext.op:s!FtVJhJJ6JJr ) overload_namec4|jdg|||d|S)z~Generates an ONNX ATen op node. This function is for backward compatibility with the old symbolic functions. z aten::ATen) operator_soverload_name_s)r))roperatorr+argsr(s raten_opzGraphContext.aten_op_s9 tww    )     r c|jjd|j}|jj}t j |||t ||g|d|i|S)aCreates an ONNX operator from onnx-script function, taking "raw_args" as inputs and "kwargs" as attributes. onnx-script repository: https://github.com/microsoft/onnx-script Args: onnx_fn: ONNXFunction from onnx-script; An example can be found at https://github.com/microsoft/onnx-script#example raw_args: The inputs to the operator; usually provided as arguments to the `symbolic` definition. outputs: The number of outputs this operator returns. By default an operator is assumed to return a single output. If `outputs` is greater than one, this functions returns a tuple of output `Value`, representing each output of the ONNX operator in order. kwargs: The attributes of the ONNX operator, whose keys are named according to the following convention: `alpha_f` indicates the `alpha` attribute with type `f`. The valid type specifiers are `f` (float), `i` (int), `s` (string) or `t` (Tensor). An attribute specified with type float accepts either a single float, or a list of floats (e.g., you would say `dims_i` for a `dims` attribute that takes a list of integers). Returns: The value representing the single output of this operator (see the `outputs` keyword argument for multi-return nodes). ::r#)rdomainrversionr custom_onnx_symbolicr%)ronnx_fnr#r'r( symbolic_name opset_versions r onnxscript_opzGraphContext.onnxscript_oppsfF#==//07<<.A  -- G ))-GPt]QXQwQ&QQr N)rstrreturnr)r&r;r'torch.Tensor | _C.Valuer#r)r/r;r+r;)r'r=r#r)__name__ __module__ __qualname____doc____annotations__ dataclassesfieldlistrrr)r1atr:r rr r s" O O J%% !!  0{00FI}F) #K#K+#K #KJBD   B  (R+(R (Rr r r!)r#n_blockscJ|j|g|d|i|}t|tr|dj}n|j}g}t |D]:} |j } t j|| } |j| <|t||fS)aPCreates an ONNX operator "opname", taking inputs and attributes. Args: graph_context: The context for the current graph. opname: The ONNX operator name, e.g., `Abs` or `Add`, or an operator qualified with a namespace, e.g., `aten::add`. inputs: The inputs to the operator. outputs: The number of outputs this operator returns. By default an operator is assumed to return a single output. If `outputs` is greater than one, this functions returns a tuple of output `Value`, representing each output of the ONNX operator in order. n_blocks: The number of sub-blocks to create in the node. attributes: The attributes of the ONNX operator. Returns: A tuple of (output_values, new_contexts, node) where: output_values: One or more output value of this operator (see the `outputs` keyword argument for multi-return nodes). new_contexts: A tuple of new graph contexts for each sub-block. node: The node representing the operator. r#r)r) r) isinstancernoderangeaddBlockrCreplaceappendtuple) graph_contextr&r#rHinputs attributes output_valuesrK new_contexts_ new_block new_contexts radd_op_with_blocksrYs>%M$$VTfTgTTM-*Q$$&!!#L 8_)MMO !))-yI K( ) % -t 33r r"c |Dcgc]}t||}}|jDcic] \}}| || } }}d|vrd|z}t|j||| |j|j |t j} |jj| |dk(r| jSt| jScc}wcc}}w)a@Creates an ONNX operator "opname", taking "args" as inputs and attributes "kwargs". The set of operators and the inputs/attributes they take is documented at https://github.com/onnx/onnx/blob/master/docs/Operators.md This function is monkey-patched onto Graph. Args: graph_context: The Torch Graph or Block. opname: The ONNX operator name, e.g., `Abs` or `Add`, or an operator qualified with a namespace, e.g., `aten::add`. args: The inputs to the operator; usually provided as arguments to the `symbolic` definition. outputs: The number of outputs this operator returns. By default an operator is assumed to return a single output. If `outputs` is greater than one, this functions returns a tuple of output `Value`, representing each output of the ONNX operator in order. kwargs: The attributes of the ONNX operator, whose keys are named according to the following convention: `alpha_f` indicates the `alpha` attribute with type `f`. The valid type specifiers are `f` (float), `i` (int), `s` (string) or `t` (Tensor). An attribute specified with type float accepts either a single float, or a list of floats (e.g., you would say `dims_i` for a `dims` attribute that takes a list of integers). Returns: (Union[_C.Value, Tuple[_C.Value, ...]]) The value representing the single output of this operator (see the `outputs` keyword argument for multi-return nodes). r3zonnx::)rr9 n_outputsshape_inferencer!) _const_if_tensoritems _create_noderrrronnx_shape_inferencerrOoutputrPr#) rQr&r#r0r(argrRkvrSrKs rr%r%sL?C Cs}c2 CF C$*<<>C41aQ]!Q$CJC 6F" !--#))44 D""4(!|{{}   -DDsC CCc^||St|tjr|St|d|S)Nzonnx::Constant)value_z)rJrValuer%)rQrbs rr]r] s/ { #rxx  ="2C @@r cHt|tjr'|}|j|||} |j | } nTt|tj r:|} | j ||} |dkDr!td|D]} | jt j} t| |k(sJ|jd} t|jD]\}}|tvrt!| ||| |rtj"| ||| S)z:Creates an node 'domain_op', taking inputs and attributes.r!zaten::)r )rJrGraphcreate insertNodeBlockaddNoderL addOutputrPr#len startswithsortedr^_SKIP_NODE_ATTRIBUTES_add_attribute(_jit_pass_onnx_node_shape_type_inference)graph_or_block domain_oprRrSrr9r[r\rrKrrV node_outputsr keyvalues rr_r_s."((+||Ivy9% NBHH -}}Y/ q=1i( !  !(L |  )) )    )DZ--/04 U ' ' tS%d34 33D+}U Kr crt|txr&t|tttj f Sr)rJrr;bytestorchTensor)rys r _is_onnx_listr~9s2 eX & z UELL)0,r c6|jdk(sJ|dS)z,Convert a scalar tensor into a Python value.r!r)numelxs r_scalarr?s 779>> Q4Kr ctj|}|td|d|jd|jd}}t |r|dz }t ||d||S)z7Initializes the right attribute based on type of value.zInvalid attribute specifier 'z<' names must be suffixed with type, e.g. 'dim_i' or 'dims_i'r!srV) _ATTR_PATTERNmatch ValueErrorgroupr~r)rKrxryr mrkinds rrsrsEsC Ay+C51C C  QWWQZ$DU   $74D6 $T5 11r cx|jjtjj Sr)type isSubtypeOfr TensorTypegetrs r _is_tensorrUs& 668   1 1 3 44r ct|sytjtj|j }|j Sr)rtypingcastrrrdevice)ry tensor_types rget_device_from_valuerYs6 e ++bmmUZZ\:K    r cd|vrtd|d|jdd\}}d|vrtd|d||fS)z(Parse node kind into domain and Op name.r3z Node kind: z& is invalid. '::' is not in node kind.r!z) is invalid. '::' should only apear once.)rsplit)rr4r&s rparse_node_kindr`sY 4;tf,RSTTZZa(NFF v~;tf,UVWW 6>r c |dk(S) Check if the domain is official.r rGr4s ris_atenrj V r c |dk(S)rprimrGrs ris_primrorr c |dk(S)ronnxrGrs ris_onnxrtrr ) rQr r&r;rR_C.Valuer#rrHrr<z-tuple[Any, tuple[GraphContext, ...], _C.Node])rQr r&r;r0r=r#r)rQr )T)ruz_C.Graph | _C.Blockrvr;rRrrSdictrrr9rr[rr\boolr<r)rz torch.Tensor)rKrrxr;ryrr r)rrr<r)ryrr<ztorch.device | None)rr;r<ztuple[str, str])r4r;r<r)"rA __future__rrCrercollections.abcrrrr|rtorch.onnx._globalsrtorch.onnx._internalr compilerrr dataclassr rYr%r]r_r~rrsrrrrrrrGr rrsuL # . '- 56 "F+ ~R~R~RJ ,4,4 ,4,4 ,4  ,43,4f <!<! <! #<! <!~A"!$'$$ $ $  $  $$$ $N  2 5   r