mmdeploy/tests/test_apis/test_extract.py
q.yao b32fc41bed
[Refactor][API2.0] Api refactor2.0 (#529)
* [refactor][API2.0]  Add onnx export and jit trace (#419)

* first commit

* add async call

* add new api onnx export and jit trace

* add decorator

* fix ci

* fix torchscript ci

* fix loader

* better pipemanager

* remove comment, better import

* add kwargs

* remove comment

* better pipeline manager

* remove print

* [Refactor][API2.0] Api partition calibration (#433)

* first commit

* add async call

* add new api onnx export and jit trace

* add decorator

* fix ci

* fix torchscript ci

* fix loader

* better pipemanager

* remove comment, better import

* add partition

* move calibration

* Better create_calib_table

* better deploy

* add kwargs

* remove comment

* better pipeline manager

* rename api, remove reduant variable, and misc

* [Refactor][API2.0] Api ncnn openvino (#435)

* first commit

* add async call

* add new api onnx export and jit trace

* add decorator

* fix ci

* fix torchscript ci

* fix loader

* better pipemanager

* remove comment, better import

* add ncnn api

* finish ncnn api

* add openvino support

* add kwargs

* remove comment

* better pipeline manager

* merge fix

* merge util and onnx2ncnn

* fix docstring

* [Refactor][API2.0] API for TensorRT (#519)

* first commit

* add async call

* add new api onnx export and jit trace

* add decorator

* fix ci

* fix torchscript ci

* fix loader

* better pipemanager

* remove comment, better import

* add partition

* move calibration

* Better create_calib_table

* better deploy

* add kwargs

* remove comment

* Add tensorrt API

* better pipeline manager

* add tensorrt new api

* remove print

* rename api, remove reduant variable, and misc

* add docstring

* [Refactor][API2.0] Api ppl other (#528)

* first commit

* add async call

* add new api onnx export and jit trace

* add decorator

* fix ci

* fix torchscript ci

* fix loader

* better pipemanager

* remove comment, better import

* add kwargs

* Add new APIS for pplnn sdk and misc

* remove comment

* better pipeline manager

* merge fix

* update tools/onnx2pplnn.py

* rename function
2022-05-31 09:18:18 +08:00

42 lines
970 B
Python

# Copyright (c) OpenMMLab. All rights reserved.
import tempfile
import onnx
import torch
from mmdeploy.apis.onnx import extract_partition
from mmdeploy.core import mark
output_file = tempfile.NamedTemporaryFile(suffix='.onnx').name
def test_extract():
@mark('add', outputs='z')
def add(x, y):
return torch.add(x, y)
class TestModel(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, y):
return add(x, y)
model = TestModel().eval()
# dummy input
x = torch.rand(2, 3, 4)
y = torch.rand(2, 3, 4)
torch.onnx.export(model, (x, y), output_file)
onnx_model = onnx.load(output_file)
extracted = extract_partition(onnx_model, 'add:input', 'add:output')
assert extracted.graph.input[0].name == 'x'
assert extracted.graph.input[1].name == 'y'
assert extracted.graph.output[0].name == 'z'
assert extracted.graph.node[0].op_type == 'Add'