comaniac commented on a change in pull request #5676:
URL: https://github.com/apache/incubator-tvm/pull/5676#discussion_r431503106
##########
File path: docs/langref/relay_pattern.rst
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@@ -139,3 +237,124 @@ Domination
**********
Match child pattern, find a match for the parent pattern, insuring that the
child ultimately dominates the parrent (i.e., no nodes outside the pattern use
outputs of the parent), and that ever node betwen the child and the pattern
matches the path pattern.
+
+Applications
+============
+
+The pattern language provides not only the pattern matching but also pattern
processing.
+Here we introduce two pattern processing approaches and provide some examples.
+
+Pattern Rewriting
+*****************
+
+If you would like to replace the matched pattern with another subgraph, you
can leverage
+the ``rewrite`` transformation. Here is an example of rewriting a series of
arithmetic operators
+with a single batch_norm op:
+
+.. code-block:: python
+
+ class BatchnormCallback(DFPatternCallback):
+ # A callback class to rewrite the matched pattern to a batch_norm op.
+ def __init__(self):
+ self.x = wildcard()
+ self.var = wildcard()
+ self.mean = wildcard()
+ self.beta = wildcard()
+ self.gamma = wildcard()
+ self.eps = wildcard()
+
+ self.pattern = self.gamma * (self.x -
self.mean)/is_op("sqrt")(self.var + self.eps) + self.beta
+
+ def callback(self, pre, post, node_map):
+ x = node_map[self.x][0]
+ var = node_map[self.var][0]
+ mean = node_map[self.mean][0]
+ beta = node_map[self.beta][0]
+ gamma = node_map[self.gamma][0]
+ eps = node_map[self.eps][0]
+ return relay.op.nn.batch_norm(x, gamma, beta, mean, var, epsilon =
eps.data.asnumpy().item())[0]
+
+ # A graph of arithmetic operators that are functional equivalent to
batch_norm.
+ x = relay.var('x')
+ var = relay.var('var')
+ mean = relay.var('mean')
+ beta = relay.var('beta')
+ gamma = relay.var('gamma')
+ BN = gamma * (x - mean)/relay.op.sqrt(var + relay.const(1e-5)) + beta
+
+ from tvm.relay.dataflow_pattern import rewrite
+ out = rewrite(BatchnormCallback(), BN)
+ assert tvm.ir.structural_equal(out, relay.op.nn.batch_norm(x, gamma,
beta, mean, var, epsilon = 1e-5)[0])
+
+The function ``def callback(self, pre, post, node_map)`` will be invoked when
the rewriter matches
+``self.pattern``. ``node_map`` is a dictionary mapping from pattern nodes to
matched nodes in the graph.
+
+Pattern Partitioning
+********************
+
+If you would like to perform a more complex processing for matched subgraphs
and you are not
+satisfy with ``rewrite``, you may consider partitioning the matched subgraphs
to a separate
Review comment:
done
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