[GitHub] [incubator-mxnet] marcoabreu commented on a change in pull request #19697: [v1.x] Add more CV models to onnxruntime inference test, add bert model test.

[GitBox <gi...@apache.org>]

marcoabreu commented on a change in pull request #19697:
URL: https://github.com/apache/incubator-mxnet/pull/19697#discussion_r546435689



##########
File path: tests/python-pytest/onnx/test_onnxruntime.py
##########
@@ -118,4 +121,52 @@ def download_test_images(tmpdir):
     shutil.rmtree(tmp_path)
 
 
+@pytest.mark.parametrize('model', ['bert_12_768_12'])
+def test_bert_inference_onnxruntime(tmp_path, model):
+    import gluonnlp as nlp
+    dataset = 'book_corpus_wiki_en_uncased'
+    ctx = mx.cpu(0)
+    model, vocab = nlp.model.get_model(
+        name=model,
+        ctx=ctx,
+        dataset_name=dataset,
+        pretrained=False,
+        use_pooler=True,
+        use_decoder=False,
+        use_classifier=False)
+    model.initialize(ctx=ctx)
+    model.hybridize(static_alloc=True)
+
+    batch = 5
+    seq_length = 16
+    # create synthetic test data
+    inputs = mx.nd.random.uniform(0, 30522, shape=(batch, seq_length), dtype='float32')
+    token_types = mx.nd.random.uniform(0, 2, shape=(batch, seq_length), dtype='float32')
+    valid_length = mx.nd.array([seq_length] * batch, dtype='float32')
+
+    seq_encoding, cls_encoding = model(inputs, token_types, valid_length)
+
+    prefix = "%s/bert" % tmp_path
+    model.export(prefix)
+    sym_file = "%s-symbol.json" % prefix
+    params_file = "%s-0000.params" % prefix
+    onnx_file = "%s.onnx" % prefix
+
+
+    input_shapes = [(batch, seq_length), (batch, seq_length), (batch,)]
+    converted_model_path = mx.contrib.onnx.export_model(sym_file, params_file, input_shapes, np.float32, onnx_file)
+
+
+    # create onnxruntime session using the generated onnx file
+    ses_opt = onnxruntime.SessionOptions()
+    ses_opt.log_severity_level = 3
+    session = onnxruntime.InferenceSession(onnx_file, ses_opt)
+    onnx_inputs = [inputs, token_types, valid_length]
+    input_dict = dict((session.get_inputs()[i].name, onnx_inputs[i].asnumpy()) for i in range(len(onnx_inputs)))
+    pred_onx = session.run(None, input_dict)[0]
+
+    assert_almost_equal(seq_encoding, pred_onx)
+
+    shutil.rmtree(tmp_path)

Review comment:
       Use try finally




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