[NFC][Linalg] Introduce ConvMatchBuilder + refactor Conv matchers #169704
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-- This commit is a follow-up and third in the series of adding matchers for conv/pool ops. Refer: llvm#163724 -- It introduces ConvMatchBuilder class in order to reduce the repetitive code across Conv1D/2D/3D/Depthwise/Pooling variants. -- Refer to [Conv2D thread](llvm#168362 (comment)) for further context. Signed-off-by: Abhishek Varma <abhvarma@amd.com>
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@llvm/pr-subscribers-mlir-linalg @llvm/pr-subscribers-mlir Author: Abhishek Varma (Abhishek-Varma) Changes-- This commit is a follow-up and third in the series of adding Signed-off-by: Abhishek Varma <abhvarma@amd.com> Patch is 35.80 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/169704.diff 1 Files Affected:
diff --git a/mlir/lib/Dialect/Linalg/Utils/Utils.cpp b/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
index 6b85e6ba0ede2..f7b86e7c385de 100644
--- a/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
+++ b/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
@@ -416,10 +416,6 @@ static bool matchConvDimAddExprPattern(ArrayAttr indexingMaps, unsigned iDim,
return false;
}
-// ---------------------------------------------
-// Matchers for specific convolution operation.
-// ---------------------------------------------
-
/// Returns true if the given indexing maps matches with the expected indexing
/// maps.
static bool convLayoutMatches(ArrayRef<ArrayRef<AffineExpr>> mapListExpected,
@@ -434,6 +430,92 @@ static bool convLayoutMatches(ArrayRef<ArrayRef<AffineExpr>> mapListExpected,
})));
}
+/// Enum of all kinds of Pooling Op's type.
+enum PoolingType {
+ NONE,
+ MAX_SIGNED,
+ MAX_UNSIGNED,
+ MIN_SIGNED,
+ MIN_UNSIGNED,
+ SUM
+};
+
+/// Helper class for building convolution op matchers with minimal boilerplate.
+/// Reduces repetitive code across Conv1D/2D/3D and Depthwise variants as well
+/// as Pooling ops.
+class ConvMatcherBuilder {
+ LinalgOp op;
+ MLIRContext *ctx;
+ SmallVector<int64_t> *dilations, *strides;
+ ArrayAttr indexingMaps;
+ PoolingType poolingType;
+ bool matched = true;
+
+public:
+ ConvMatcherBuilder(LinalgOp op, unsigned spatialRank, SmallVector<int64_t> *d,
+ SmallVector<int64_t> *s,
+ PoolingType poolingType = PoolingType::NONE)
+ : op(op), ctx(op->getContext()), dilations(d), strides(s),
+ indexingMaps(op.getIndexingMaps()), poolingType(poolingType) {
+ *dilations = SmallVector<int64_t>(spatialRank, 1);
+ *strides = SmallVector<int64_t>(spatialRank, 1);
+ }
+
+ /// Get affine dimension expression for dimension i.
+ AffineExpr dim(unsigned i) { return getAffineDimExpr(i, ctx); }
+
+ /// Build strided expression: base * stride[idx] + kernel * dilation[idx]
+ AffineExpr strided(AffineExpr base, AffineExpr kernel, unsigned idx) {
+ return base * (*strides)[idx] + kernel * (*dilations)[idx];
+ }
+
+ /// Match stride/dilation pattern for a spatial dimension.
+ /// Returns *this for method chaining.
+ ConvMatcherBuilder &matchStride(unsigned iDim, unsigned fDim, unsigned oDim,
+ unsigned idx) {
+ if (matched) {
+ matched = matchConvDimAddExprPattern(indexingMaps, iDim, fDim, oDim,
+ (*dilations)[idx], (*strides)[idx]);
+ }
+ return *this;
+ }
+
+ /// Match expected indexing maps layout.
+ /// Returns *this for method chaining.
+ ConvMatcherBuilder &expectMaps(ArrayRef<ArrayRef<AffineExpr>> maps) {
+ if (matched)
+ matched = convLayoutMatches(maps, indexingMaps, ctx);
+ return *this;
+ }
+
+ /// Match body pattern. This should be called last.
+ bool matchBody() {
+ if (!matched)
+ return false;
+ Block *body = op.getBlock();
+ auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
+ switch (poolingType) {
+ case PoolingType::NONE:
+ return bodyMatcherForConvolutionOps(yieldOp.getOperand(0), body);
+ case PoolingType::MAX_SIGNED:
+ return bodyMatcherForMaxSignedPoolOps(yieldOp.getOperand(0), body);
+ case PoolingType::MAX_UNSIGNED:
+ return bodyMatcherForMaxUnsignedPoolOps(yieldOp.getOperand(0), body);
+ case PoolingType::MIN_SIGNED:
+ return bodyMatcherForMinSignedPoolOps(yieldOp.getOperand(0), body);
+ case PoolingType::MIN_UNSIGNED:
+ return bodyMatcherForMinUnsignedPoolOps(yieldOp.getOperand(0), body);
+ case PoolingType::SUM:
+ return bodyMatcherForSumPoolOps(yieldOp.getOperand(0), body);
+ }
+ return false;
+ }
+};
+
+// ---------------------------------------------
+// Matchers for specific convolution operation.
+// ---------------------------------------------
+
// #inputMap = affine_map<(W, w) -> (W + w)>
// #filterMap = affine_map<(W, w) -> (w)>
// #outputMap = affine_map<(W, w) -> (W)>
@@ -447,29 +529,15 @@ bool isaConvolutionOpOfType<linalg::Conv1DOp>(LinalgOp op,
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(1, 1);
- *strides = SmallVector<int64_t>(1, 1);
- MLIRContext *context = op->getContext();
- AffineExpr W = getAffineDimExpr(0, context);
- AffineExpr w = getAffineDimExpr(1, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/0, /*fDim=*/0,
- /*oDim=*/0, (*dilations)[0], (*strides)[0]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{W * (*strides)[0] + w * (*dilations)[0]},
- /*filterMap=*/{w},
- /*outputMap=*/{W}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/1, dilations, strides);
+ AffineExpr W = m.dim(0);
+ AffineExpr w = m.dim(1);
+
+ return m.matchStride(/*iDim=*/0, /*fDim=*/0, /*oDim=*/0, /*idx=*/0)
+ .expectMaps({/*inputMap=*/{m.strided(W, w, 0)},
+ /*filterMap=*/{w},
+ /*outputMap=*/{W}})
+ .matchBody();
}
// #inputMap = affine_map<(N, W, F, w, c) -> (N, W + w, c)>
@@ -485,32 +553,18 @@ bool isaConvolutionOpOfType<linalg::Conv1DNwcWcfOp>(
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(1, 1);
- *strides = SmallVector<int64_t>(1, 1);
- MLIRContext *context = op->getContext();
- AffineExpr N = getAffineDimExpr(0, context);
- AffineExpr W = getAffineDimExpr(1, context);
- AffineExpr F = getAffineDimExpr(2, context);
- AffineExpr w = getAffineDimExpr(3, context);
- AffineExpr c = getAffineDimExpr(4, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/1, /*fDim=*/0,
- /*oDim=*/1, (*dilations)[0], (*strides)[0]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{N, W * (*strides)[0] + w * (*dilations)[0], c},
- /*filterMap=*/{w, c, F},
- /*outputMap=*/{N, W, F}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/1, dilations, strides);
+ AffineExpr N = m.dim(0);
+ AffineExpr W = m.dim(1);
+ AffineExpr F = m.dim(2);
+ AffineExpr w = m.dim(3);
+ AffineExpr c = m.dim(4);
+
+ return m.matchStride(/*iDim=*/1, /*fDim=*/0, /*oDim=*/1, /*idx=*/0)
+ .expectMaps({/*inputMap=*/{N, m.strided(W, w, 0), c},
+ /*filterMap=*/{w, c, F},
+ /*outputMap=*/{N, W, F}})
+ .matchBody();
}
// #inputMap = affine_map<(N, F, W, c, w) -> (N, c, W + w)>
@@ -526,32 +580,18 @@ bool isaConvolutionOpOfType<linalg::Conv1DNcwFcwOp>(
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(1, 1);
- *strides = SmallVector<int64_t>(1, 1);
- MLIRContext *context = op->getContext();
- AffineExpr N = getAffineDimExpr(0, context);
- AffineExpr F = getAffineDimExpr(1, context);
- AffineExpr W = getAffineDimExpr(2, context);
- AffineExpr c = getAffineDimExpr(3, context);
- AffineExpr w = getAffineDimExpr(4, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/2, /*fDim=*/2,
- /*oDim=*/2, (*dilations)[0], (*strides)[0]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{N, c, W * (*strides)[0] + w * (*dilations)[0]},
- /*filterMap=*/{F, c, w},
- /*outputMap=*/{N, F, W}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/1, dilations, strides);
+ AffineExpr N = m.dim(0);
+ AffineExpr F = m.dim(1);
+ AffineExpr W = m.dim(2);
+ AffineExpr c = m.dim(3);
+ AffineExpr w = m.dim(4);
+
+ return m.matchStride(/*iDim=*/2, /*fDim=*/2, /*oDim=*/2, /*idx=*/0)
+ .expectMaps({/*inputMap=*/{N, c, m.strided(W, w, 0)},
+ /*filterMap=*/{F, c, w},
+ /*outputMap=*/{N, F, W}})
+ .matchBody();
}
// #inputMap = affine_map<(H, W, h, w) -> (H + h, W + w)>
@@ -567,36 +607,18 @@ bool isaConvolutionOpOfType<linalg::Conv2DOp>(LinalgOp op,
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(2, 1);
- *strides = SmallVector<int64_t>(2, 1);
- MLIRContext *context = op->getContext();
- AffineExpr H = getAffineDimExpr(0, context);
- AffineExpr W = getAffineDimExpr(1, context);
- AffineExpr h = getAffineDimExpr(2, context);
- AffineExpr w = getAffineDimExpr(3, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: H * stride + h * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/0, /*fDim=*/0,
- /*oDim=*/0, (*dilations)[0], (*strides)[0]))
- return false;
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/1, /*fDim=*/1,
- /*oDim=*/1, (*dilations)[1], (*strides)[1]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{H * (*strides)[0] + h * (*dilations)[0],
- W * (*strides)[1] + w * (*dilations)[1]},
- /*filterMap=*/{h, w},
- /*outputMap=*/{H, W}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/2, dilations, strides);
+ AffineExpr H = m.dim(0);
+ AffineExpr W = m.dim(1);
+ AffineExpr h = m.dim(2);
+ AffineExpr w = m.dim(3);
+
+ return m.matchStride(/*iDim=*/0, /*fDim=*/0, /*oDim=*/0, /*idx=*/0)
+ .matchStride(/*iDim=*/1, /*fDim=*/1, /*oDim=*/1, /*idx=*/1)
+ .expectMaps({/*inputMap=*/{m.strided(H, h, 0), m.strided(W, w, 1)},
+ /*filterMap=*/{h, w},
+ /*outputMap=*/{H, W}})
+ .matchBody();
}
// #inputMap = affine_map<(D, H, W, d, h, w) -> (D + d, H + h, W + w)>
@@ -612,43 +634,22 @@ bool isaConvolutionOpOfType<linalg::Conv3DOp>(LinalgOp op,
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(3, 1);
- *strides = SmallVector<int64_t>(3, 1);
- MLIRContext *context = op->getContext();
- AffineExpr D = getAffineDimExpr(0, context);
- AffineExpr H = getAffineDimExpr(1, context);
- AffineExpr W = getAffineDimExpr(2, context);
- AffineExpr d = getAffineDimExpr(3, context);
- AffineExpr h = getAffineDimExpr(4, context);
- AffineExpr w = getAffineDimExpr(5, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: D * stride + d * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/0, /*fDim=*/0,
- /*oDim=*/0, (*dilations)[0], (*strides)[0]))
- return false;
- // Match: H * stride + h * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/1, /*fDim=*/1,
- /*oDim=*/1, (*dilations)[1], (*strides)[1]))
- return false;
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/2, /*fDim=*/2,
- /*oDim=*/2, (*dilations)[2], (*strides)[2]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{D * (*strides)[0] + d * (*dilations)[0],
- H * (*strides)[1] + h * (*dilations)[1],
- W * (*strides)[2] + w * (*dilations)[2]},
- /*filterMap=*/{d, h, w},
- /*outputMap=*/{D, H, W}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/3, dilations, strides);
+ AffineExpr D = m.dim(0);
+ AffineExpr H = m.dim(1);
+ AffineExpr W = m.dim(2);
+ AffineExpr d = m.dim(3);
+ AffineExpr h = m.dim(4);
+ AffineExpr w = m.dim(5);
+
+ return m.matchStride(/*iDim=*/0, /*fDim=*/0, /*oDim=*/0, /*idx=*/0)
+ .matchStride(/*iDim=*/1, /*fDim=*/1, /*oDim=*/1, /*idx=*/1)
+ .matchStride(/*iDim=*/2, /*fDim=*/2, /*oDim=*/2, /*idx=*/2)
+ .expectMaps({/*inputMap=*/{m.strided(D, d, 0), m.strided(H, h, 1),
+ m.strided(W, w, 2)},
+ /*filterMap=*/{d, h, w},
+ /*outputMap=*/{D, H, W}})
+ .matchBody();
}
// #inputMap = affine_map<(N, W, C, w) -> (N, C, W + w)>
@@ -664,31 +665,17 @@ bool isaConvolutionOpOfType<linalg::DepthwiseConv1DNcwCwOp>(
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(1, 1);
- *strides = SmallVector<int64_t>(1, 1);
- MLIRContext *context = op->getContext();
- AffineExpr N = getAffineDimExpr(0, context);
- AffineExpr W = getAffineDimExpr(1, context);
- AffineExpr C = getAffineDimExpr(2, context);
- AffineExpr w = getAffineDimExpr(3, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/2, /*fDim=*/1,
- /*oDim=*/2, (*dilations)[0], (*strides)[0]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{N, C, W * (*strides)[0] + w * (*dilations)[0]},
- /*filterMap=*/{C, w},
- /*outputMap=*/{N, C, W}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/1, dilations, strides);
+ AffineExpr N = m.dim(0);
+ AffineExpr W = m.dim(1);
+ AffineExpr C = m.dim(2);
+ AffineExpr w = m.dim(3);
+
+ return m.matchStride(/*iDim=*/2, /*fDim=*/1, /*oDim=*/2, /*idx=*/0)
+ .expectMaps({/*inputMap=*/{N, C, m.strided(W, w, 0)},
+ /*filterMap=*/{C, w},
+ /*outputMap=*/{N, C, W}})
+ .matchBody();
}
// #inputMap = affine_map<(N, W, C, w) -> (N, W + w, C)>
@@ -704,31 +691,17 @@ bool isaConvolutionOpOfType<linalg::DepthwiseConv1DNwcWcOp>(
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(1, 1);
- *strides = SmallVector<int64_t>(1, 1);
- MLIRContext *context = op->getContext();
- AffineExpr N = getAffineDimExpr(0, context);
- AffineExpr W = getAffineDimExpr(1, context);
- AffineExpr C = getAffineDimExpr(2, context);
- AffineExpr w = getAffineDimExpr(3, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/1, /*fDim=*/0,
- /*oDim=*/1, (*dilations)[0], (*strides)[0]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{N, W * (*strides)[0] + w * (*dilations)[0], C},
- /*filterMap=*/{w, C},
- /*outputMap=*/{N, W, C}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/1, dilations, strides);
+ AffineExpr N = m.dim(0);
+ AffineExpr W = m.dim(1);
+ AffineExpr C = m.dim(2);
+ AffineExpr w = m.dim(3);
+
+ return m.matchStride(/*iDim=*/1, /*fDim=*/0, /*oDim=*/1, /*idx=*/0)
+ .expectMaps({/*inputMap=*/{N, m.strided(W, w, 0), C},
+ /*filterMap=*/{w, C},
+ /*outputMap=*/{N, W, C}})
+ .matchBody();
}
// #inputMap = affine_map<(N, W, C, CM, w) -> (N, W + w, C)>
@@ -744,32 +717,18 @@ bool isaConvolutionOpOfType<linalg::DepthwiseConv1DNwcWcmOp>(
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(1, 1);
- *strides = SmallVector<int64_t>(1, 1);
- MLIRContext *context = op->getContext();
- AffineExpr N = getAffineDimExpr(0, context);
- AffineExpr W = getAffineDimExpr(1, context);
- AffineExpr C = getAffineDimExpr(2, context);
- AffineExpr CM = getAffineDimExpr(3, context);
- AffineExpr w = getAffineDimExpr(4, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: W * stride + w * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/1, /*fDim=*/0,
- /*oDim=*/1, (*dilations)[0], (*strides)[0]))
- return false;
- // Match expected indexing maps
- if (!convLayoutMatches(
- {/*inputMap=*/{N, W * (*strides)[0] + w * (*dilations)[0], C},
- /*filterMap=*/{w, C, CM},
- /*outputMap=*/{N, W, C, CM}},
- indexingMaps, context))
- return false;
- // Match body
- Block *body = op.getBlock();
- auto yieldOp = cast<linalg::YieldOp>(body->getTerminator());
- Value yieldVal = yieldOp.getOperand(0);
- return bodyMatcherForConvolutionOps(yieldVal, body);
+ ConvMatcherBuilder m(op, /*spatialRank=*/1, dilations, strides);
+ AffineExpr N = m.dim(0);
+ AffineExpr W = m.dim(1);
+ AffineExpr C = m.dim(2);
+ AffineExpr CM = m.dim(3);
+ AffineExpr w = m.dim(4);
+
+ return m.matchStride(/*iDim=*/1, /*fDim=*/0, /*oDim=*/1, /*idx=*/0)
+ .expectMaps({/*inputMap=*/{N, m.strided(W, w, 0), C},
+ /*filterMap=*/{w, C, CM},
+ /*outputMap=*/{N, W, C, CM}})
+ .matchBody();
}
// #inputMap = affine_map<(N, H, W, C, h, w) -> (N, C, H + h, W + w)>
@@ -785,38 +744,20 @@ bool isaConvolutionOpOfType<linalg::DepthwiseConv2DNchwChwOp>(
assert(isaConvolutionOpInterface(op) &&
"expected op to implement ConvolutionOpInterface");
- *dilations = SmallVector<int64_t>(2, 1);
- *strides = SmallVector<int64_t>(2, 1);
- MLIRContext *context = op->getContext();
- AffineExpr N = getAffineDimExpr(0, context);
- AffineExpr H = getAffineDimExpr(1, context);
- AffineExpr W = getAffineDimExpr(2, context);
- AffineExpr C = getAffineDimExpr(3, context);
- AffineExpr h = getAffineDimExpr(4, context);
- AffineExpr w = getAffineDimExpr(5, context);
- ArrayAttr indexingMaps = op.getIndexingMaps();
- // First fetch dilations/strides :-
- // Match: H * stride + h * dilation
- if (!matchConvDimAddExprPattern(indexingMaps, /*iDim=*/2, /*fDim=*/1,
- /*oDim=*/2, (*dilations)[0], (*strides)[...
[truncated]
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hanhanW
approved these changes
Nov 28, 2025
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hanhanW
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hanhanW
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Very nice cleanup, thanks a ton! Let's also mark the PR with nfc. Just few nits.
Abhishek-Varma
changed the title
Collaborator
|
LLVM Buildbot has detected a new failure on builder Full details are available at: https://lab.llvm.org/buildbot/#/builders/198/builds/10076 Here is the relevant piece of the build log for the reference |
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-- This commit is a follow-up and third in the series of adding
matchers for conv/pool ops. Refer: #163724
-- It introduces ConvMatchBuilder class in order to reduce the
repetitive code across Conv1D/2D/3D/Depthwise/Pooling variants.
-- Refer to Conv2D thread for further context.
Signed-off-by: Abhishek Varma abhvarma@amd.com