[GitHub] [incubator-tvm] Somisary commented on a change in pull request #6355: [BYOC][ETHOSN] Introduce further operator support

[GitBox <gi...@apache.org>]

Somisary commented on a change in pull request #6355:
URL: https://github.com/apache/incubator-tvm/pull/6355#discussion_r485932937



##########
File path: tests/python/contrib/test_ethosn/test_networks.py
##########
@@ -0,0 +1,163 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""Ethos-N integration end-to-end network tests"""
+
+import pytest
+pytest.importorskip('tflite')
+pytest.importorskip('tensorflow')
+
+from tvm import relay
+from tvm.relay.op.contrib.ethosn import ethosn_available, Available
+from tvm.contrib import download
+import tvm.relay.testing.tf as tf_testing
+import tflite.Model
+from . import infrastructure as tei
+
+
+def _get_tflite_model(tflite_model_path, inputs_dict, dtype):
+    with open(tflite_model_path, 'rb') as f:
+        tflite_model_buffer = f.read()
+
+    try:
+        tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buffer, 0)
+    except AttributeError:
+        tflite_model = tflite.Model.GetRootAsModel(tflite_model_buffer, 0)
+    shape_dict = {}
+    dtype_dict = {}
+    for input in inputs_dict:
+        input_shape = inputs_dict[input]
+        shape_dict[input] = input_shape
+        dtype_dict[input] = dtype
+
+    return relay.frontend.from_tflite(
+        tflite_model,
+        shape_dict=shape_dict,
+        dtype_dict=dtype_dict,
+    )
+
+
+def _test_image_network(model_url, model_sub_path, input_dict, compile_hash, output_count, run=True, host_ops=0, npu_partitions=1):
+    if not ethosn_available():
+        return
+
+    def get_model():
+        if model_url[-3:] in ("tgz", "zip"):
+            model_path = tf_testing.get_workload_official(
+                model_url,
+                model_sub_path,
+            )
+        else:
+            model_path = download.download_testdata(
+                model_url,
+                model_sub_path,
+            )
+        return _get_tflite_model(model_path, input_dict, 'uint8')
+
+    outputs = []
+    inputs = {}
+    for input_name in input_dict:
+        input_shape = input_dict[input_name]
+        inputs[input_name] = tei.get_real_image(input_shape[1], input_shape[2])
+
+    for npu in [False, True]:
+        mod, params = get_model()
+        graph, lib, params = tei.build(mod, params, npu=npu, expected_host_ops=host_ops, npu_partitions=npu_partitions)
+        if npu:
+            tei.assert_lib_hash(lib, compile_hash)

Review comment:
       It's not a JSON graph, but a Support Library compiled network which is in a binary format. Testing for hash equality is the simplest way to ensure changes don't happen without the ability to actually execute the graph.




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