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Source code for mmdeploy.apis.extract_model

# Copyright (c) OpenMMLab. All rights reserved.

from typing import Dict, Iterable, Optional, Union

import onnx

from .core import PIPELINE_MANAGER


[docs]@PIPELINE_MANAGER.register_pipeline() def extract_model(model: Union[str, onnx.ModelProto], start_marker: Union[str, Iterable[str]], end_marker: Union[str, Iterable[str]], start_name_map: Optional[Dict[str, str]] = None, end_name_map: Optional[Dict[str, str]] = None, dynamic_axes: Optional[Dict[str, Dict[int, str]]] = None, save_file: Optional[str] = None) -> onnx.ModelProto: """Extract partition-model from an ONNX model. The partition-model is defined by the names of the input and output tensors exactly. Examples: >>> from mmdeploy.apis import extract_model >>> model = 'work_dir/fastrcnn.onnx' >>> start_marker = 'detector:input' >>> end_marker = ['extract_feat:output', 'multiclass_nms[0]:input'] >>> dynamic_axes = { 'input': { 0: 'batch', 2: 'height', 3: 'width' }, 'scores': { 0: 'batch', 1: 'num_boxes', }, 'boxes': { 0: 'batch', 1: 'num_boxes', } } >>> save_file = 'partition_model.onnx' >>> extract_model(model, start_marker, end_marker, \ dynamic_axes=dynamic_axes, \ save_file=save_file) Args: model (str | onnx.ModelProto): Input ONNX model to be extracted. start_marker (str | Sequence[str]): Start marker(s) to extract. end_marker (str | Sequence[str]): End marker(s) to extract. start_name_map (Dict[str, str]): A mapping of start names, defaults to `None`. end_name_map (Dict[str, str]): A mapping of end names, defaults to `None`. dynamic_axes (Dict[str, Dict[int, str]]): A dictionary to specify dynamic axes of input/output, defaults to `None`. save_file (str): A file to save the extracted model, defaults to `None`. Returns: onnx.ModelProto: The extracted model. """ from .onnx import extract_partition return extract_partition(model, start_marker, end_marker, start_name_map, end_name_map, dynamic_axes, save_file)
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