Update test data

Author: dkurt

testdata/dnn/tflite/generate.py

@@ -48,31 +48,30 @@ def run_mediapipe_solution(solution, inp_size):
 
 # 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)
+    func = model.get_concrete_function()
+    converter = tf.lite.TFLiteConverter.from_concrete_functions([func])
     tflite_model = converter.convert()
 
+    interpreter = tf.lite.Interpreter(model_content=tflite_model)
+
     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))
+    np.save(f'{name}_out_Identity.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
+@tf.function(input_signature=[tf.TensorSpec(shape=[1, 3, 3, 1], dtype=tf.float32)])
+def replicate_by_pack(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')
+save_tflite_model(replicate_by_pack, inp, 'replicate_by_pack')