add swin test

test/models/private_tests/test_swin.py

@@ -0,0 +1,25 @@
+import onnxruntime as ort
+import numpy as np
+import onnx
+from onnx2kerastl import onnx_to_keras
+from keras_data_format_converter import convert_channels_first_to_last
+import tensorflow as tf
+from test.models.private_tests.aws_utils import aws_s3_download
+import pytest
+
+
+@pytest.mark.parametrize('aws_s3_download', [["swin/", "swin/", False]], indirect=True)
+def test_swin(aws_s3_download):
+    model_path = f'{aws_s3_download}/swin_v2_t.onnx'
+    inpt = np.load(f'{aws_s3_download}/input.npy')
+    result = np.load(f'{aws_s3_download}/output.npy')
+    onnx_model = onnx.load(model_path)
+    keras_model = onnx_to_keras(onnx_model, ['input'], name_policy='attach_weights_name',
+                                allow_partial_compilation=False).converted_model
+    final_model = convert_channels_first_to_last(keras_model, should_transform_inputs_and_outputs=True)
+    res = final_model(inpt)
+    mean_error = (res-result).numpy().__abs__().mean()
+    max_error = (res-result).numpy().__abs__().max()
+    eps = 5e-6
+    assert mean_error < eps
+    assert max_error < eps