Add test for Pack from TFLite

Author: dkurt

testdata/dnn/tflite/generate.py

@@ -45,3 +45,34 @@ def run_mediapipe_solution(solution, inp_size):
 run_tflite_model("face_detection_short_range", (128, 128))
 
 run_mediapipe_solution(mp.solutions.selfie_segmentation.SelfieSegmentation(model_selection=0), (256, 256))
+
+# Save TensorFlow model as TFLite
+def save_tflite_model(model, inp, name):
+    func = model.__call__.get_concrete_function()
+    converter = tf.lite.TFLiteConverter.from_concrete_functions([func], model)
+    tflite_model = converter.convert()
+
+    with open(f'{name}.tflite', 'wb') as f:
+        f.write(tflite_model)
+
+    out = model(inp)
+
+    np.save(f'{name}_inp.npy', inp.transpose(0, 3, 1, 2))
+    np.save(f'{name}_out_PartitionedCall:0.npy', np.array(out).transpose(0, 3, 1, 2))
+
+
+class ReplicateByPack(tf.Module):
+    @tf.function(input_signature=[tf.TensorSpec(shape=[1, 3, 3, 1], dtype=tf.float32)])
+    def __call__(self, x):
+        pack_1 = tf.stack([x, x], axis=3)
+        reshape_1 = tf.reshape(pack_1, [1, 3, 6, 1])
+        pack_2 = tf.stack([reshape_1, reshape_1], axis=2)
+        reshape_2 = tf.reshape(pack_2, [1, 6, 6, 1])
+        scaled = tf.image.resize(reshape_2, size=(3, 3), method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
+        return scaled + x
+
+model = ReplicateByPack()
+inp = np.random.standard_normal((1, 3, 3, 1)).astype(np.float32)
+
+save_tflite_model(model, inp, 'replicate_by_pack')
+