add test for mindir export

tests/ut/test_mindir_export.py

@@ -0,0 +1,46 @@
+import sys
+sys.path.append('.')
+import mindspore as ms
+import pytest
+import numpy as np
+from mindocr import list_models, build_model
+from tools.export import export
+
+@pytest.mark.parametrize('name', ['dbnet_resnet50', 'crnn_resnet34'])
+def test_mindir_infer(name):
+    task = 'rec'
+    if 'db' in name:
+        task = 'det'
+
+    export(name, task, pretrained=True)
+
+    fn = f"{name}.mindir"
+
+    ms.set_context(mode=ms.GRAPH_MODE)
+    graph = ms.load(fn)
+    model = ms.nn.GraphCell(graph)
+
+    if task=='rec':
+        c, h, w = 3, 32, 100
+    else:
+        c, h, w = 3, 640, 640
+
+    bs = 1
+    x = ms.Tensor(np.ones([bs, c, h, w]), dtype=ms.float32)
+
+    outputs_mindir = model(x)
+
+    # get original ckpt outputs
+    net = build_model(name, pretrained=True)
+    outputs_ckpt = net(x)
+
+    for i, o in enumerate(outputs_mindir):
+        print('mindir net out: ', outputs_mindir[i].sum(), outputs_mindir[i].shape)
+        print('ckpt net out: ', outputs_ckpt[i].sum(), outputs_mindir[i].shape)
+        assert outputs_mindir[i].sum()==outputs_ckpt[i].sum()
+
+
+if __name__ == '__main__':
+    names = list_models()
+    test_mindir_infer(names[0])
+