mbrookhart commented on a change in pull request #5930:
URL: https://github.com/apache/incubator-tvm/pull/5930#discussion_r445915192
##########
File path: tests/python/relay/test_dataflow_pattern.py
##########
@@ -1133,6 +1133,37 @@ def test_partition_double_batchnorm():
reference = f2(gamma, f1(gamma, x, mean, var, beta), mean, var, beta)
assert tvm.ir.structural_equal(partitioned, reference)
+def test_overlappting_partitions():
+ x = wildcard()
+ gamma = wildcard()
+ beta = wildcard()
+ moving_mean = wildcard()
+ moving_var = wildcard()
+ bn_node = is_op('nn.batch_norm')(x, gamma, beta, moving_mean, moving_var)
+ tuple_get_item_node = TupleGetItemPattern(bn_node, 0)
+
+ x = relay.var('x')
+ var = relay.var('var')
+ mean = relay.var('mean')
+ beta = relay.var('beta')
+ gamma = relay.var('gamma')
+ BN = relay.op.nn.batch_norm(x, gamma, beta, mean, var, epsilon=1e-5)
+ T1 = BN[0]
+ T2 = BN[0]
+ add = T1 + T2
+
+ assert tuple_get_item_node.partition(add) == add
Review comment:
Partitioning either path is invalid, since either side would need
intermediate nodes from the other, so we expect the original expression to come
back unchanged, thus the `==`. We treat it as a match, but we don't treat it as
something we can independently rewrite.
##########
File path: tests/python/relay/test_dataflow_pattern.py
##########
@@ -1133,6 +1133,37 @@ def test_partition_double_batchnorm():
reference = f2(gamma, f1(gamma, x, mean, var, beta), mean, var, beta)
assert tvm.ir.structural_equal(partitioned, reference)
+def test_overlappting_partitions():
+ x = wildcard()
+ gamma = wildcard()
+ beta = wildcard()
+ moving_mean = wildcard()
+ moving_var = wildcard()
+ bn_node = is_op('nn.batch_norm')(x, gamma, beta, moving_mean, moving_var)
+ tuple_get_item_node = TupleGetItemPattern(bn_node, 0)
+
+ x = relay.var('x')
+ var = relay.var('var')
+ mean = relay.var('mean')
+ beta = relay.var('beta')
+ gamma = relay.var('gamma')
+ BN = relay.op.nn.batch_norm(x, gamma, beta, mean, var, epsilon=1e-5)
+ T1 = BN[0]
+ T2 = BN[0]
+ add = T1 + T2
+
+ assert tuple_get_item_node.partition(add) == add
+
+def test_partition_overused():
+ pattern = is_op("nn.relu")(is_op("nn.conv2d")(wildcard(), wildcard()))
+
+ x = relay.var('input')
+ w = relay.var('weight')
+ conv2d = relay.op.nn.conv2d(x, w)
+ relu = relay.op.nn.relu(conv2d)
+ out = relu + conv2d
+
+ assert pattern.partition(out) == out
Review comment:
Again, fusing the conv and relu would make the rest of the expr invalid,
so we expect the expr to come back unchanged.
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