Q/j,ddlmZddlZddlZddlZddlmZddlZddlm Z erddl Z eje Z d d dZdZ d d dZy) ) annotationsN) TYPE_CHECKING) _type_utilscddl}|3tjj|jj n(tjj |j}|<|j|jk7r|j|j}|j}||_ |j|_ |jj|j|jj |_|d|j%j'd}|j)D]6\} } |j*j-} | | _t1| | _8t4j6j9||} t4j6j;| rt5j<| t4j6j?| } t4j6j;| st5j@| tC| d5}|jE|jGdjIddd|S#1swY|SxYw)aCreate a TensorProto with external data from a PyTorch tensor. The external data is saved to os.path.join(basepath, location). Args: tensor: Tensor to be saved. name: Name of the tensor (i.e., initializer name in ONNX graph). location: Relative location of the external data file (e.g., "/tmp/initializers/weight_0" when model is "/tmp/model_name.onnx"). basepath: Base path of the external data file (e.g., "/tmp/external_data" while model must be in "/tmp"). Reference for ONNX's external data format: How to load? https://github.com/onnx/onnx/blob/5dac81ac0707bdf88f56c35c0a5e8855d3534673/onnx/external_data_helper.py#L187 How to save? https://github.com/onnx/onnx/blob/5dac81ac0707bdf88f56c35c0a5e8855d3534673/onnx/external_data_helper.py#L43 How to set ONNX fields? https://github.com/onnx/onnx/blob/5dac81ac0707bdf88f56c35c0a5e8855d3534673/onnx/external_data_helper.py#L88 rN)locationoffsetlengthxbT)force)%onnxjit_type_utils JitScalarTypefrom_onnx_type tensor_type elem_type from_dtypedtypeto TensorProtoname onnx_type data_typedimsextendshapeEXTERNAL data_locationuntyped_storagenbytesitems external_dataaddkeystrvalueospathjoinexistsremovedirnamemakedirsopenwritenumpytobytes)tensorrrbasepathdtype_overrider scalar_type tensor_protokey_value_pairskventryexternal_data_file_pathexternal_data_dir_path data_files h/root/repos/pocs/video-evals/.venv/lib/python3.12/site-packages/torch/onnx/_internal/fx/serialization.py'_create_tensor_proto_with_external_datar>s6  % $$33  & & 0 0  ) ) 4 4V\\ B !k&7&7&9V\\&I;,,./#4##%LL(224LV\\*!%!1!1!:!:L ((*113O  %%'1**..0 !f  !ggll8X> ww~~-. )* WW__-DE 77>>0 1 *+ %t ,<   4 088:; <  < s ,0I&&I0cddlm}i}||dd5}|jD]$}|j|j ||<& ddd|S#1swY|SxYw)Nr) safe_openptcpu) frameworkdevice) safetensorsr@keys get_tensorrB)safetensors_filer@tensorsfr7s r=$_convert_safetensors_to_torch_formatrKgsh&G #tE B/a /Aa,,.GAJ // N/ Ns 8AA!c Xddl}i}t|jjD cic]\}} | j|} }} |jj D chc]} | j} } |D]} t | tr| }nFt | tr| jdr t| }n tj| dd}|j)D]\}}|r|j+d d }|| vr| j-|n>| D]9}|j|s|j|s&|}| j-|nt.j0j3||}|jj D cic]} | j| j4}} || vr||| |<t7|||||j9|d}|jjj;|tt=|j)d }|j?D]}|jj|=|j@|t.j0j3||ycc} }wcc} w#ttf$r}dt|vst | tj rXt"j%dt | tj r| j'dtj| d }n|Yd}~Pd}~wwxYwcc} w) aLoad PyTorch tensors from files and add to "onnx_model" as external initializers. Output files: ONNX model file path: ONNX initializer folder: os.path.join(basepath, initializer_location) After running this function, you can do ort_sess = onnxruntime.InferenceSession(os.path.join(basepath, model_location)) to execute the model. Arguments: basepath: Base path of the ONNX external data file (e.g., "/path/to/large_model/"). model_location: Relative location of the ONNX model file. E.g., "model.onnx" so that the model file is saved to "/model.onnx". initializer_location: Relative location of the ONNX initializer folder. E.g., "initializers" so that the initializers are saved to "/initializers/". Note: When initializers are >2GB, must be the same as `model_location`. torch_state_dicts: Dictionaries or files which contain PyTorch tensors to be saved as ONNX initializers. For non-dict arguments, `torch.load` will be used to load them from file-like objects. onnx_model: ONNX model to be saved with external initializers. If an input name matches a tensor loaded from "torch_state_dicts", the tensor will be saved as that input's external initializer. rename_initializer: Replaces "." by "_" for all ONNX initializer names. Not needed by the official torch.onnx.dynamo_export. This is a hack for supporting `FXSymbolicTracer` tracer with fake tensor mode. In short, `FXSymbolicTracer` lifts FX parameters (self.linear_weight) as inputs (`def forward(self, linear_weight)`) and therefore, `.` cannot be used. rNz .safetensorsrBT) map_locationmmapz+mmap can only be used with files saved withzFailed to load the checkpoint with memory-map enabled, retrying without memory-map.Consider updating the checkpoint with mmap by using torch.save() on PyTorch version >= 1.6.)rM._)reverse)!r enumerategraph initializerrinput isinstancedictr$endswithrKtorchload RuntimeError ValueErrorioBytesIOlogwarningseekr replacer*r&r'r(typer>popappendsortedrFsave)r2model_locationinitializer_locationtorch_state_dicts onnx_modelrename_initializerr initializers_to_be_deletedidxr7existing_initializersrUonnx_input_namesel state_dicterr1onnx_input_namerelative_tensor_file_pathmodel_input_typesr5s r=save_model_with_external_datarwtsN!#"+J,<,<,H,H"IQ 1;0@0@0F0FGu GGI> b$ J"c"r{{>'BA"E  "'BU!NJ',,.. >LD&! ||C-'' ''-'7O&//59W /(//@ )+ 5I4(P %:D9I9I9O9O PA P  P,,JN*+@+FGB)!%%dD1 L    ( ( / / =]. >7I>V"&)//14@"*..0.    ( ( -.DIIj"'',,x@AmH%j1  DI#B 3 z&b"**5GGAJ%*ZZ%G #  ^!Qs*I>J7J L' L$BLL$)N) r1z torch.Tensorrr$rr$r2r$r3zonnx.TypeProto | Nonereturnzonnx.TensorProto)F)r2r$rhr$rir$rjz#tuple[dict | str | io.BytesIO, ...]rkzonnx.ModelProtorlboolrxNone) __future__rr]loggingr&typingrrY torch.onnxrr r getLogger__name__r_r>rKrwr=rs"  4g!-1 Q Q QQ Q * Q  Qh & % @B@B@B@B; @B  @B  @B @Br