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Use OrPatterns to support SkipLayerNormalization rewrite variations #2277

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merged 1 commit into from
May 8, 2025
Merged

Use OrPatterns to support SkipLayerNormalization rewrite variations #2277

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65 changes: 59 additions & 6 deletions onnxscript/rewriter/ort_fusions/skip_normalization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,15 @@ def __init__(self, name: str, has_bias: bool = False, bias_pre_add: bool = False
def pattern(self, op, input, skip, gamma, bias, epsilon, stash_type):
if self._has_bias and self._bias_pre_add:
input = op.Add(input, bias)
skip_sum = op.Add(input, skip)

# Support different combinations of addition of input and skip
skip_sum_pattern_1 = op.Add(skip, input)
skip_sum_pattern_2 = op.Add(input, skip)
skip_sum = pattern.OrValue(
[skip_sum_pattern_1, skip_sum_pattern_2],
name="skip_sum",
)

if self._has_bias and not self._bias_pre_add:
skip_sum = op.Add(skip_sum, bias)
# Note: ORT's SimplifiedLayerNormalization was placed in onnx domain by mistake.
Expand All @@ -36,7 +44,17 @@ def pattern(self, op, input, skip, gamma, bias, epsilon, stash_type):
)
return normalized, skip_sum

def check(self, op, input, skip, gamma, bias, epsilon, stash_type) -> pattern.MatchResult: # type: ignore[name-defined]
def check(
self,
op,
input,
skip,
gamma,
bias,
epsilon,
stash_type,
**_,
) -> pattern.MatchResult: # type: ignore[name-defined]
"""Check if the pattern matches conditions for use of SkipSimplifiedLayerNormalization op."""
check_result = pattern.MatchResult()
bindings: dict[str, Dim] = {}
Expand Down Expand Up @@ -68,7 +86,17 @@ def no_match(val: ir.Value, dims: Sequence[str]) -> bool:

return check_result

def rewrite(self, op, input, skip, gamma, bias, epsilon, stash_type):
def rewrite(
self,
op,
input,
skip,
gamma,
bias,
epsilon,
stash_type,
**_,
):
if self._has_bias:
normalized, _mean, _inv_std_var, skip_sum = op.SkipSimplifiedLayerNormalization(
input,
Expand Down Expand Up @@ -116,7 +144,12 @@ def __init__(self, name: str, has_bias: bool = False, bias_pre_add: bool = False
def pattern(self, op, input, skip, gamma, beta, bias, epsilon, stash_type):
if self._has_bias and self._bias_pre_add:
input = op.Add(input, bias)
skip_sum = op.Add(input, skip)

# Support different combinations of addition of input and skip
skip_sum_pattern_1 = op.Add(skip, input)
skip_sum_pattern_2 = op.Add(input, skip)
skip_sum = pattern.OrValue([skip_sum_pattern_1, skip_sum_pattern_2], name="skip_sum")

if self._has_bias and not self._bias_pre_add:
skip_sum = op.Add(skip_sum, bias)
normalized = op.LayerNormalization(
Expand All @@ -130,7 +163,16 @@ def pattern(self, op, input, skip, gamma, beta, bias, epsilon, stash_type):
return normalized, skip_sum

def check(
self, op, input, skip, gamma, beta, bias, epsilon, stash_type
self,
op,
input,
skip,
gamma,
beta,
bias,
epsilon,
stash_type,
**_,
) -> pattern.MatchResult: # type: ignore[name-defined]
"""Check if the pattern matches conditions for use of SimplifiedLayerNormalization op."""
check_result = pattern.MatchResult()
Expand Down Expand Up @@ -168,7 +210,18 @@ def no_match(val: ir.Value, dims: Sequence[str]) -> bool:

return check_result

def rewrite(self, op, input, skip, gamma, beta, bias, epsilon, stash_type):
def rewrite(
self,
op,
input,
skip,
gamma,
beta,
bias,
epsilon,
stash_type,
**_,
):
normalized, _mean, _inv_std_var, skip_sum = op.SkipLayerNormalization(
input,
skip,
Expand Down
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