[GitHub] [tvm] Aleksei-grovety commented on a diff in pull request #14629: [microNPU][ETHOSU] Softmax int8 legalization support

["Aleksei-grovety (via GitHub)" <gi...@apache.org>]

Aleksei-grovety commented on code in PR #14629:
URL: https://github.com/apache/tvm/pull/14629#discussion_r1168696585


##########
tests/python/contrib/test_ethosu/test_legalize.py:
##########
@@ -3076,5 +3076,116 @@ def representative_dataset():
     assert tuple(func_body.args[1].checked_type.shape) == (256,)
 
 
+@pytest.mark.parametrize("ifm_shape", [(1, 12), (1, 12, 32)])
+def test_tflite_softmax(ifm_shape):
+    dtype = "int8"
+
+    def create_tflite_graph():
+        @tf.function
+        def softmax(x):
+            return tf.nn.softmax(x)
+
+        concrete_func = softmax.get_concrete_function(tf.TensorSpec(ifm_shape, dtype=tf.float32))
+        # Convert the model
+        def representative_dataset():
+            for _ in range(100):
+                data = np.random.rand(*tuple(ifm_shape))
+                yield [data.astype(np.float32)]
+
+        converter = tf.lite.TFLiteConverter.from_concrete_functions([concrete_func])
+        converter.optimizations = [tf.lite.Optimize.DEFAULT]
+        converter.representative_dataset = representative_dataset
+        converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
+        converter.inference_input_type = tf.int8
+        converter.inference_output_type = tf.int8
+        tflite_model = converter.convert()
+        return tflite_model
+
+    def verify(ext_func):
+        out_op = ext_func.body
+        ops = []
+        expected_op_names = [
+            "reshape",
+            "reshape",
+            "contrib.ethosu.pooling",
+            "contrib.ethosu.binary_elementwise",

Review Comment:
   I'll add it.



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