Add getting started sample code (#1502)

Signed-off-by: Tom Wildenhain <[email protected]>

Author: TomWildenhain-Microsoft

examples/getting_started.py

@@ -0,0 +1,64 @@
+# SPDX-License-Identifier: Apache-2.0
+
+"""
+This example shows how to convert tf functions and keras models using the Python API.
+It also demonstrates converting saved_models from the command line.
+"""
+
+import tensorflow as tf
+import tf2onnx
+import numpy as np
+import onnxruntime as ort
+import os
+
+##################### tf function #####################
+
+@tf.function
+def f(a, b):
+    return a + b
+
+input_signature = [tf.TensorSpec([2, 3], tf.float32), tf.TensorSpec([2, 3], tf.float32)]
+onnx_model, _ = tf2onnx.convert.from_function(f, input_signature, opset=13)
+
+a_val = np.ones([2, 3], np.float32)
+b_val = np.zeros([2, 3], np.float32)
+
+print("Tensorflow result")
+print(f(a_val, b_val).numpy())
+
+print("ORT result")
+sess = ort.InferenceSession(onnx_model.SerializeToString())
+res = sess.run(None, {'a': a_val, 'b': b_val})
+print(res[0])
+
+
+##################### Keras Model #####################
+
+model = tf.keras.Sequential()
+model.add(tf.keras.layers.Dense(4, activation="relu"))
+
+input_signature = [tf.TensorSpec([3, 3], tf.float32, name='x')]
+onnx_model, _ = tf2onnx.convert.from_keras(model, input_signature, opset=13)
+
+x_val = np.ones((3, 3), np.float32)
+
+print("Keras result")
+print(model(x_val).numpy())
+
+print("ORT result")
+sess = ort.InferenceSession(onnx_model.SerializeToString())
+res = sess.run(None, {'x': x_val})
+print(res[0])
+
+
+##################### Saved Model #####################
+
+model.save("savedmodel")
+os.system("python -m tf2onnx.convert --saved-model savedmodel --output model.onnx --opset 13")
+
+print("ORT result")
+sess = ort.InferenceSession("model.onnx")
+res = sess.run(None, {'dense_input:0': x_val})
+print(res[0])
+
+print("Conversion succeeded")

tests/test_example.py

@@ -19,7 +19,7 @@ def run_example(self, name, expected=None):
             "..", "examples", name)
         if not os.path.exists(full):
             raise FileNotFoundError(full)
-        proc = subprocess.run(('python %s' % full).split(),
+        proc = subprocess.run(['python', full],
                               capture_output=True, check=True)
         self.assertEqual(0, proc.returncode)
         out = proc.stdout.decode('ascii')
@@ -51,6 +51,14 @@ def test_end2end_tfhub(self):
                       "Optimizing ONNX model",
                       "Using opset <onnx, 12>"])
 
+    @check_tf_min_version("2.3", "use tf.keras")
+    @check_opset_min_version(13)
+    @check_opset_max_version(13)
+    def test_getting_started(self):
+        self.run_example(
+            "getting_started.py",
+            expected=["Conversion succeeded"])
+
 
 if __name__ == '__main__':
     unittest.main()