[GitHub] [tvm] dchauhan-arm commented on a change in pull request #9209: Arm(R) Ethos(TM)-U NPU Depthwise2d operator support

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

dchauhan-arm commented on a change in pull request #9209:
URL: https://github.com/apache/tvm/pull/9209#discussion_r724888277



##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -168,5 +166,95 @@ def create_graph_activation(input_tensor_name, input_tensor_shape, input_tensor_
         infra.verify_source(compiled_models, accel_type)
 
 
+@pytest.mark.parametrize("accel_type", ACCEL_TYPES)
+@pytest.mark.parametrize("ifm_shape", [(1, 55, 55, 3), (1, 23, 32, 7)])
+@pytest.mark.parametrize(
+    "kernel_shape, activation",
+    [((3, 3), "relu"), ((1, 2), None)],
+)
+@pytest.mark.parametrize("padding", ["SAME", "VALID"])
+@pytest.mark.parametrize("strides, dilation", [((1, 1), (2, 2)), ((3, 2), (1, 1))])
+def test_tflite_depthwise_conv2d(
+    accel_type,
+    ifm_shape,
+    kernel_shape,
+    padding,
+    strides,
+    dilation,
+    activation,
+):
+    dtype = "int8"
+
+    def create_tflite_graph():
+        tf.config.run_functions_eagerly(True)
+
+        class Model(tf.Module):
+            @tf.function
+            def depthwise_conv2d(self, x):
+                weight_shape = [kernel_shape[0], kernel_shape[1], ifm_shape[3], 1]
+                weight = tf.constant(np.random.uniform(size=weight_shape), dtype=tf.float32)
+                # The input strides to the TensorFlow API needs to be of shape 1x4
+                tf_strides = [1, strides[0], strides[1], 1]
+                op = tf.nn.depthwise_conv2d(
+                    x, weight, strides=tf_strides, padding=padding, dilations=dilation
+                )
+                if activation:
+                    op = tf.nn.relu(op)
+                return op
+

Review comment:
       LGTM regarding tf.nn.depthwise_conv2d usage. Others' comments cover everything else.




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