Remove Depracated TF2ONNX UT Case (#1843)

Signed-off-by: zehao-intel <[email protected]>
intel · Jun 5, 2024 · 82fc480 · 82fc480
1 parent daa1431
commit 82fc480
Showing 1 changed file with 0 additions and 59 deletions.
diff --git a/test/itex/test_tensorflow_qdq_convert_to_onnx_qdq.py b/test/itex/test_tensorflow_qdq_convert_to_onnx_qdq.py
@@ -57,65 +57,6 @@ def tearDownClass(self):
         if version1_gte_version2(tf.version.VERSION, "2.8.0"):
             shutil.rmtree("workspace")
 
-    @disable_random()
-    @unittest.skipIf(version1_lt_version2(tf.version.VERSION, "2.8.0"), "Only supports tf greater 2.7.0")
-    def test_convert_tf_qdq_to_onnx_qdq(self):
-        x = tf.compat.v1.placeholder(tf.float32, [1, 56, 56, 16], name="input")
-        top_relu = tf.nn.relu(x)
-        paddings = tf.constant([[0, 0], [1, 1], [1, 1], [0, 0]])
-        x_pad = tf.pad(top_relu, paddings, "CONSTANT")
-        conv_weights = tf.compat.v1.get_variable(
-            "weight", [3, 3, 16, 16], initializer=tf.compat.v1.random_normal_initializer()
-        )
-        conv = tf.nn.conv2d(x_pad, conv_weights, strides=[1, 2, 2, 1], padding="VALID")
-        normed = tf.compat.v1.layers.batch_normalization(conv)
-
-        conv_weights2 = tf.compat.v1.get_variable(
-            "weight2", [3, 3, 16, 16], initializer=tf.compat.v1.random_normal_initializer()
-        )
-        conv2 = tf.nn.conv2d(top_relu, conv_weights2, strides=[1, 2, 2, 1], padding="SAME")
-        add = tf.raw_ops.Add(x=normed, y=conv2, name="addv2")
-        relu = tf.nn.relu(add)
-        relu6 = tf.nn.relu6(relu, name="op_to_store")
-
-        out_name = relu6.name.split(":")[0]
-        with tf.compat.v1.Session() as sess:
-            sess.run(tf.compat.v1.global_variables_initializer())
-            output_graph_def = graph_util.convert_variables_to_constants(
-                sess=sess, input_graph_def=sess.graph_def, output_node_names=[out_name]
-            )
-
-            quantizer = Quantization("fake_yaml.yaml")
-            dataset = quantizer.dataset("dummy", shape=(100, 56, 56, 16), label=True)
-            quantizer.eval_dataloader = common.DataLoader(dataset)
-            quantizer.calib_dataloader = common.DataLoader(dataset)
-
-            quantizer.model = output_graph_def
-            output_graph = quantizer.fit()
-
-            from neural_compressor.config import TF2ONNXConfig
-
-            config = TF2ONNXConfig()
-            output_graph.export("workspace/tf_qdq_to_onnx_qdq.onnx", config)
-
-            import onnx
-
-            onnx_model = onnx.load("workspace/tf_qdq_to_onnx_qdq.onnx")
-            onnx.checker.check_model(onnx_model)
-
-            import onnxruntime as ort
-
-            from neural_compressor.data import DATALOADERS, Datasets
-
-            ort_session = ort.InferenceSession("workspace/tf_qdq_to_onnx_qdq.onnx")
-            dataset = Datasets("tensorflow")["dummy"]((100, 56, 56, 16))
-            dataloader = DATALOADERS["tensorflow"](dataset)
-            it = iter(dataloader)
-            input = next(it)
-            input_dict = {"input:0": input[0]}
-            outputs = ort_session.run(None, input_dict)
-            self.assertNotEqual(outputs, None)
-
     @disable_random()
     @unittest.skipIf(version1_lt_version2(tf.version.VERSION, "2.8.0"), "Only supports tf greater 2.7.0")
     def test_convert_tf_fp32_to_onnx_fp32(self):