add an end2end example

Signed-off-by: xavier dupré <[email protected]>

Author: sdpython

examples/end2end_tfkeras.py

@@ -0,0 +1,47 @@
+import os
+import subprocess
+import numpy as np
+import tensorflow as tf
+from tensorflow import keras
+from tensorflow.keras import layers, Input
+
+
+# Creates the model.
+model = keras.Sequential()
+#model.add(layers.Embedding(input_dim=10, output_dim=4))
+model.add(Input((4, 4)))
+model.add(layers.SimpleRNN(8))
+model.add(layers.Dense(2))
+print(model.summary())
+print(model.inputs)
+print(model.outputs)
+
+# Testing the model.
+input = np.random.randn(2, 4, 4).astype(np.float32)
+expected  = model.predict(input)
+print(expected)
+
+# Training
+# ....
+
+# Saves the model.
+if not os.path.exists("simple_rnn"):
+    os.mkdir("simple_rnn")
+tf.keras.models.save_model(model, "simple_rnn")
+
+# Run the command line.
+proc = subprocess.run('python -m tf2onnx.convert --saved-model simple_rnn '
+                      '--output simple_rnn.onnx --opset 12'.split(),
+                      capture_output=True)
+print(proc.returncode)
+print(proc.stdout.decode('ascii'))
+print(proc.stderr.decode('ascii'))
+
+# Run onnxruntime.
+from onnxruntime import InferenceSession
+session = InferenceSession("simple_rnn.onnx")
+got = session.run(None, {'input_1:0': input})
+print(got[0])
+
+# Differences
+print(np.abs(got[0] - expected).max())