experimental_experiment.torch_models.dump_helper¶
- experimental_experiment.torch_models.dump_helper.assert_all_close(v1: Any, v2: Any, atol: float | Tuple[float, float] = 1e-05, rtol: float = 1e-05, msg: str = '')[source]¶
Checks that the expected outputs and new outputs are the same.
- Parameters:
v1 – tensor or tuple of tensors
v2 – tensor or tuple of tensors
atol – absolute error or (absolute error, quantile), if quantile is specified, the function checks the error is < atol for quantile %
rtol – relative error
msg – more complex message
See 301: Compares LLAMA exporters for onnxrt backend for an example.
- experimental_experiment.torch_models.dump_helper.build_matching_inputs(model1: str | ModelProto, feeds: Dict[str, Any], model2: str | ModelProto) Dict[str, Any][source]¶
Builds a list of inputs for a model based on the inputs made for another. We assume they both needs the same inputs.
- Parameters:
model1 – first model
feeds – inputs for the first model
model2 – second model, the one we need the inputs for
- Returns:
new inputs
See 301: Compares LLAMA exporters for onnxrt backend for an example.
- experimental_experiment.torch_models.dump_helper.dump_onnx(prefix: str, folder: str | None = None, clean: bool = False)[source]¶
context enabling the dump of models generated by onnxrt backend.
- Parameters:
prefix – prefix for all files
folder – sub folder (created if it does not exist)
clean – if True, cleans the folder
See 301: Compares LLAMA exporters for onnxrt backend for an example.
- experimental_experiment.torch_models.dump_helper.inputs_from_onnx_model(model: str | ModelProto, init: bool = False) List[Tuple[str, int, Tuple[int, ...]]][source]¶
Returns the inputs for a model.
- Parameters:
model – model or filename
init – include the initializer as well
- Returns:
list of inputs and initializers
See 301: Compares LLAMA exporters for onnxrt backend for an example.
- experimental_experiment.torch_models.dump_helper.reorder_functions_in_proto(proto: str | ModelProto) str | ModelProto[source]¶
The reference implementation expects function to be defined. So rank function has to be placed in the first position
- Parameters:
proto – a model
- Returns:
modified model inplace
See 301: Compares LLAMA exporters for onnxrt backend for an example.