Instructions to use CatSnowdrop/universal_onnxruntime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use CatSnowdrop/universal_onnxruntime with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py from CatSnowdrop/universal_onnxruntime: direct link, hf CLI and curl.
- Browser
- Download file 2.59 kB
-
https://huggingface.co/CatSnowdrop/universal_onnxruntime/resolve/main/onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py
- Command line
-
hf download hf://CatSnowdrop/universal_onnxruntime/onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py
-
curl -L -o TrtTable.py https://huggingface.co/CatSnowdrop/universal_onnxruntime/resolve/main/onnxruntime/quantization/CalTableFlatBuffers/TrtTable.py
2.59 kB
| # automatically generated by the FlatBuffers compiler, do not modify | |
| # namespace: CalTableFlatBuffers | |
| import flatbuffers | |
| from flatbuffers.compat import import_numpy | |
| np = import_numpy() | |
| class TrtTable: | |
| __slots__ = ["_tab"] | |
| def GetRootAs(cls, buf, offset=0): # noqa: N802 | |
| n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset) | |
| x = TrtTable() | |
| x.Init(buf, n + offset) | |
| return x | |
| def GetRootAsTrtTable(cls, buf, offset=0): # noqa: N802 | |
| """This method is deprecated. Please switch to GetRootAs.""" | |
| return cls.GetRootAs(buf, offset) | |
| # TrtTable | |
| def Init(self, buf, pos): # noqa: N802 | |
| self._tab = flatbuffers.table.Table(buf, pos) | |
| # TrtTable | |
| def Dict(self, j): # noqa: N802 | |
| o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4)) | |
| if o != 0: | |
| x = self._tab.Vector(o) | |
| x += flatbuffers.number_types.UOffsetTFlags.py_type(j) * 4 | |
| x = self._tab.Indirect(x) | |
| from onnxruntime.quantization.CalTableFlatBuffers.KeyValue import KeyValue # noqa: PLC0415 | |
| obj = KeyValue() | |
| obj.Init(self._tab.Bytes, x) | |
| return obj | |
| return None | |
| # TrtTable | |
| def DictLength(self): # noqa: N802 | |
| o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4)) | |
| if o != 0: | |
| return self._tab.VectorLen(o) | |
| return 0 | |
| # TrtTable | |
| def DictIsNone(self): # noqa: N802 | |
| o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4)) | |
| return o == 0 | |
| def Start(builder): # noqa: N802 | |
| builder.StartObject(1) | |
| def TrtTableStart(builder): # noqa: N802 | |
| """This method is deprecated. Please switch to Start.""" | |
| return Start(builder) | |
| def AddDict(builder, dict): # noqa: N802 | |
| builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(dict), 0) | |
| def TrtTableAddDict(builder, dict): # noqa: N802 | |
| """This method is deprecated. Please switch to AddDict.""" | |
| return AddDict(builder, dict) | |
| def StartDictVector(builder, numElems): # noqa: N802 | |
| return builder.StartVector(4, numElems, 4) | |
| def TrtTableStartDictVector(builder, numElems): # noqa: N802 | |
| """This method is deprecated. Please switch to Start.""" | |
| return StartDictVector(builder, numElems) | |
| def End(builder): # noqa: N802 | |
| return builder.EndObject() | |
| def TrtTableEnd(builder): # noqa: N802 | |
| """This method is deprecated. Please switch to End.""" | |
| return End(builder) | |