[GitHub] [tvm] billishyahao commented on a diff in pull request #11508: [BYOC][DNNL] Enable layer normalization in DNNL byoc.

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

billishyahao commented on code in PR #11508:
URL: https://github.com/apache/tvm/pull/11508#discussion_r889061002


##########
python/tvm/relay/op/contrib/dnnl.py:
##########
@@ -526,3 +527,52 @@ def visit_call(self, call):
     new_mod["main"] = SubgraphRemover(subgraphs_to_remove, mod, new_mod).visit(mod["main"])
     new_mod = transform.RemoveUnusedFunctions()(new_mod)
     return new_mod
+
+
+class LayerNormRewrite(DFPatternCallback):
+    '''
+    A callback to rewrite the following operators into a single layer normalization operator.
+
+    1   %4 = mean(%3, axis=[-1], keepdims=True) /* ty=Tensor[(1, 3136, 1), float32] */;
+    2   %5 = subtract(%3, %4) /* ty=Tensor[(1, 3136, 64), float32] */;
+    3   %6 = cast(%5, dtype="float32") /* ty=Tensor[(1, 3136, 64), float32] */;
+    4   %7 = power(%6, 2f /* ty=float32 */) /* ty=Tensor[(1, 3136, 64), float32] */;
+    5   %8 = mean(%7, axis=[-1], keepdims=True) /* ty=Tensor[(1, 3136, 1), float32] */;
+    6   %9 = add(%8, 1e-05f /* ty=float32 */) /* ty=Tensor[(1, 3136, 1), float32] */;
+    7   %10 = sqrt(%9) /* ty=Tensor[(1, 3136, 1), float32] */;
+    8   %11 = divide(%5, %10) /* ty=Tensor[(1, 3136, 64), float32] */;
+    9   %12 = multiply(%11, meta[relay.Constant][2] /* ty=Tensor[(64), float32] */) /* ty=Tensor[(1, 3136, 64), float32] */;
+    10   %13 = add(%12, meta[relay.Constant][3] /* ty=Tensor[(64), float32] */) /* ty=Tensor[(1, 3136, 64), float32] */;
+    '''
+
+    def __init__(self):
+        super(LayerNormRewrite, self).__init__()
+        self.data = wildcard()
+        self.eps = wildcard()
+        self.gamma = wildcard()
+        self.beta = wildcard()
+        mu = is_op("mean")(self.data)
+        diff = is_op("subtract")(self.data, mu)
+        cdiff = diff | is_op("cast")(diff)
+        p1 = is_op("power")(cdiff, is_constant())

Review Comment:
   Thanks for pointing it out. I have resolved it by specifying the const magic number in my latest revision.



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