[GitHub] [incubator-tvm] siju-samuel commented on a change in pull request #5452: [Frontend][TFLite] L2_POOL_2D operator

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

siju-samuel commented on a change in pull request #5452:
URL: https://github.com/apache/incubator-tvm/pull/5452#discussion_r415987001



##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -561,6 +561,31 @@ def test_forward_pooling():
                       strides=[2, 1])
 
 
+def _test_l2_pool2d(input_shape, ksize, strides, padding, data_format, fused_func_name=None):
+    x = np.arange(np.prod(input_shape), dtype=np.float32).reshape(input_shape) - 1
+
+    with tf.Graph().as_default():
+        in_data = tf.placeholder(
+            dtype=tf.float32, name="input", shape=input_shape)
+        out = tf.sqrt(tf.nn.avg_pool(
+            tf.square(in_data), ksize=ksize, strides=strides,
+            padding=padding, data_format=data_format))
+        out = with_fused_activation_function(out, fused_func_name)
+
+        compare_tflite_with_tvm(x, 'input', [in_data], [out])
+
+
+def test_l2_pool2d():

Review comment:
       add `test_l2_pool2d` to __main__

##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -1770,6 +1775,12 @@ def convert_pool2d(self, op, pool_type):
                 assert self.has_same_qnn_params(input_tensor, output_tensor), \
                         "qnn.op.max_pool2d requires input and output qnn params to be same"
             out = _op.nn.max_pool2d(in_expr, **params)
+        elif pool_type == "l2":
+            # l2_pool_2d is equivalent to square_root(avg_pool(square(in_data)))

Review comment:
       Add a protection check to throw error if you receive quantized inputs.




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