diff --git a/test/pytest/test_keras_api.py b/test/pytest/test_keras_api.py
index 606f2bc51d..d9ede0b699 100644
--- a/test/pytest/test_keras_api.py
+++ b/test/pytest/test_keras_api.py
@@ -175,36 +175,38 @@ def test_conv1d(test_case_id, padds, backend, strategy, io_type, synthesis_confi
     # 5e-2 might be too high
     np.testing.assert_allclose(hls_prediction, keras_prediction, rtol=0, atol=5e-2)
 
-    if not (backend in ['Vivado', 'Vitis'] and io_type == 'io_stream' and padds == 'same'):
-        # Vivado/Vitis inserts and additional layer for 'same' padding in io_stream
-        assert len(model.layers) + 2 == len(hls_model.get_layers())
-        assert list(hls_model.get_layers())[1].attributes['name'] == model.layers[0]._name
-        assert list(hls_model.get_layers())[1].attributes['class_name'] == 'Conv1D'
-        assert list(hls_model.get_layers())[1].attributes['activation'] == str(model.layers[0].activation).split()[1]
-        assert list(hls_model.get_layers())[1].attributes['in_width'] == model.layers[0]._batch_input_shape[1]
-        assert list(hls_model.get_layers())[1].attributes['filt_width'] == model.layers[0].kernel_size[0]
-        assert list(hls_model.get_layers())[1].attributes['n_chan'] == model.layers[0].input_shape[2]
-        assert list(hls_model.get_layers())[1].attributes['n_filt'] == model.layers[0].filters
-        assert list(hls_model.get_layers())[1].attributes['stride_width'] == model.layers[0].strides[0]
-        assert list(hls_model.get_layers())[1].attributes['data_format'] == model.layers[0].data_format
-        assert list(hls_model.get_layers())[1].attributes['out_width'] == list(model.layers[0].output_shape)[1]
-
-        out_width = math.ceil(float(model.layers[0]._batch_input_shape[2]) / float(model.layers[0].strides[0]))
-        pad_along_width = max(
-            (out_width - 1) * model.layers[0].strides[0]
-            + model.layers[0].kernel_size[0]
-            - model.layers[0]._batch_input_shape[2],
-            0,
-        )
-        pad_left = pad_along_width // 2
-        pad_right = pad_along_width - pad_left
+    off = 0
+    # Vitis/Vivado adds a padding layer after the input in the io_stream case
+    if backend in ['Vitis', 'Vivado'] and io_type == 'io_stream' and padds == 'same':
+        off = 1
+    assert len(model.layers) + 2 + off == len(hls_model.get_layers())
+    assert list(hls_model.get_layers())[1 + off].attributes['name'] == model.layers[0]._name
+    assert list(hls_model.get_layers())[1 + off].attributes['class_name'] == 'Conv1D'
+    assert list(hls_model.get_layers())[1 + off].attributes['activation'] == str(model.layers[0].activation).split()[1]
+    assert list(hls_model.get_layers())[1].attributes['in_width'] == model.layers[0]._batch_input_shape[1]
+    assert list(hls_model.get_layers())[1 + off].attributes['filt_width'] == model.layers[0].kernel_size[0]
+    assert list(hls_model.get_layers())[1 + off].attributes['n_chan'] == model.layers[0].input_shape[2]
+    assert list(hls_model.get_layers())[1 + off].attributes['n_filt'] == model.layers[0].filters
+    assert list(hls_model.get_layers())[1 + off].attributes['stride_width'] == model.layers[0].strides[0]
+    assert list(hls_model.get_layers())[1 + off].attributes['data_format'] == model.layers[0].data_format
+    assert list(hls_model.get_layers())[1 + off].attributes['out_width'] == list(model.layers[0].output_shape)[1]
+
+    out_width = math.ceil(float(model.layers[0]._batch_input_shape[2]) / float(model.layers[0].strides[0]))
+    pad_along_width = max(
+        (out_width - 1) * model.layers[0].strides[0]
+        + model.layers[0].kernel_size[0]
+        - model.layers[0]._batch_input_shape[2],
+        0,
+    )
+    pad_left = pad_along_width // 2
+    pad_right = pad_along_width - pad_left
 
-        if model.layers[0].padding == 'same':
-            assert list(hls_model.get_layers())[1].attributes['pad_left'] == pad_left
-            assert list(hls_model.get_layers())[1].attributes['pad_right'] == pad_right
-        elif model.layers[0].padding == 'valid':
-            assert list(hls_model.get_layers())[1].attributes['pad_left'] == 0
-            assert list(hls_model.get_layers())[1].attributes['pad_right'] == 0
+    if model.layers[0].padding == 'same':
+        assert list(hls_model.get_layers())[1].attributes['pad_left'] == pad_left
+        assert list(hls_model.get_layers())[1].attributes['pad_right'] == pad_right
+    elif model.layers[0].padding == 'valid':
+        assert list(hls_model.get_layers())[1 + off].attributes['pad_left'] == 0
+        assert list(hls_model.get_layers())[1 + off].attributes['pad_right'] == 0
 
 
 chans_options = ['channels_last']