Revert "[mlir][linalg] Implement Conv2D using Winograd Conv2D algorithm"

This reverts commit 4240341.

Author: Hsiangkai

mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td

@@ -154,118 +154,4 @@ def Linalg_SoftmaxOp : Linalg_Op<"softmax",
   let hasVerifier = 1;
 }
 
-def Linalg_WinogradFilterTransformOp : Linalg_Op<"winograd_filter_transform"> {
-  let summary = "Winograd filter transform operator";
-  let description = [{
-    Winograd Conv2D algorithm will convert linalg Conv2D operator into batched
-    matrix multiply. Before the matrix multiply, it will convert filter and
-    input into a format suitable for batched matrix multiply. After the matrix
-    multiply, it will convert output to the final result tensor.
-
-    The algorithm F(m x m, r x r) is
-
-    Y = A^T x [(G x g x G^T) @ (B^T x d x B)] x A
-
-    The size of output Y is m x m. The size of filter g is r x r. The size of
-    input d is (m + r - 1) x (m + r - 1). A^T, A, G^T, G, B^T, and B are
-    transformation matrices.
-
-    This operator is defined to represent the high level concept of filter
-    transformation (G x g x G^T) in the Winograd Conv2D algorithm.
-  }];
-
-  let arguments = (ins AnyRankedTensor:$filter,
-                       AnyRankedTensor:$output,
-                       I64Attr:$m,
-                       I64Attr:$r
-  );
-
-  let results = (outs AnyRankedTensor:$result);
-  let assemblyFormat = [{
-    attr-dict
-    `m` `(` $m `)`
-    `r` `(` $r `)`
-    `ins` `(` $filter `:` type($filter) `)`
-    `outs` `(` $output `:` type($output) `)`
-    `->` type($result)
-  }];
-  let hasVerifier = 1;
-}
-
-def Linalg_WinogradInputTransformOp : Linalg_Op<"winograd_input_transform"> {
-  let summary = "Winograd input transform operator";
-  let description = [{
-    Winograd Conv2D algorithm will convert linalg Conv2D operator into batched
-    matrix multiply. Before the matrix multiply, it will convert filter and
-    input into a format suitable for batched matrix multiply. After the matrix
-    multiply, it will convert output to the final result tensor.
-
-    The algorithm F(m x m, r x r) is
-
-    Y = A^T x [(G x g x G^T) @ (B^T x d x B)] x A
-
-    The size of output Y is m x m. The size of filter g is r x r. The size of
-    input d is (m + r - 1) x (m + r - 1). A^T, A, G^T, G, B^T, and B are
-    transformation matrices.
-
-    This operator is defined to represent the high level concept of input
-    transformation (B^T x d x B) in the Winograd Conv2D algorithm.
-  }];
-
-  let arguments = (ins AnyRankedTensor:$input,
-                       AnyRankedTensor:$output,
-                       I64Attr:$m,
-                       I64Attr:$r
-  );
-
-  let results = (outs AnyRankedTensor:$result);
-  let assemblyFormat = [{
-    attr-dict
-    `m` `(` $m `)`
-    `r` `(` $r `)`
-    `ins` `(` $input `:` type($input) `)`
-    `outs` `(` $output `:` type($output) `)`
-    `->` type($result)
-  }];
-  let hasVerifier = 1;
-}
-
-def Linalg_WinogradOutputTransformOp : Linalg_Op<"winograd_output_transform"> {
-  let summary = "Winograd output transform operator";
-  let description = [{
-    Winograd Conv2D algorithm will convert linalg Conv2D operator into batched
-    matrix multiply. Before the matrix multiply, it will convert filter and
-    input into a format suitable for batched matrix multiply. After the matrix
-    multiply, it will convert output to the final result tensor.
-
-    The algorithm F(m x m, r x r) is
-
-    Y = A^T x [(G x g x G^T) @ (B^T x d x B)] x A
-
-    The size of output Y is m x m. The size of filter g is r x r. The size of
-    input d is (m + r - 1) x (m + r - 1). A^T, A, G^T, G, B^T, and B are
-    transformation matrices.
-
-    This operator is defined to represent the high level concept of output
-    transformation (A^T x y x A) in the Winograd Conv2D algorithm.
-  }];
-
-  let arguments = (ins AnyRankedTensor:$value,
-                       AnyRankedTensor:$output,
-                       I64Attr:$m,
-                       I64Attr:$r
-  );
-
-  let results = (outs AnyRankedTensor:$result);
-  let assemblyFormat = [{
-    attr-dict
-    `m` `(` $m `)`
-    `r` `(` $r `)`
-    `ins` `(` $value `:` type($value) `)`
-    `outs` `(` $output `:` type($output) `)`
-    `->` type($result)
-  }];
-  let hasVerifier = 1;
-}
-
 #endif // LINALG_OPS

mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h

@@ -1692,10 +1692,6 @@ void populateTransposeMatmulPatterns(RewritePatternSet &patterns,
 void populateBlockPackMatmulPatterns(RewritePatternSet &patterns,
                                      const ControlBlockPackMatmulFn &controlFn);
 
-/// Patterns to apply Winograd Conv2D algorithm F(m x m, r x r).
-void populateWinogradConv2DPatterns(RewritePatternSet &patterns, int64_t m,
-                                    int64_t r);
-
 } // namespace linalg
 } // namespace mlir
 

mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp

@@ -2734,84 +2734,6 @@ FailureOr<SmallVector<Value>> SoftmaxOp::decomposeOperation(OpBuilder &b) {
   return SmallVector<Value>{result};
 }
 
-//===----------------------------------------------------------------------===//
-// WinogradFilterTransformOp
-//===----------------------------------------------------------------------===//
-
-LogicalResult WinogradFilterTransformOp::verify() {
-  auto filterType = cast<ShapedType>(getFilter().getType());
-  auto outputType = cast<ShapedType>(getOutput().getType());
-  auto filterElemType = filterType.getElementType();
-  auto outputElemType = outputType.getElementType();
-  if (filterElemType != outputElemType) {
-    return emitOpError() << "expected element type of input " << filterElemType
-                         << " to match element type of output "
-                         << outputElemType;
-  }
-
-  unsigned filterRank = filterType.getRank();
-  if (filterRank != 4)
-    return emitOpError() << "expected rank of input is 4";
-
-  unsigned outputRank = outputType.getRank();
-  if (outputRank != 6)
-    return emitOpError() << "expected rank of output is 6";
-
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// WinogradInputTransformOp
-//===----------------------------------------------------------------------===//
-
-LogicalResult WinogradInputTransformOp::verify() {
-  auto inputType = cast<ShapedType>(getInput().getType());
-  auto outputType = cast<ShapedType>(getOutput().getType());
-  auto inputElemType = inputType.getElementType();
-  auto outputElemType = outputType.getElementType();
-  if (inputElemType != outputElemType) {
-    return emitOpError() << "expected element type of input " << inputElemType
-                         << " to match element type of output "
-                         << outputElemType;
-  }
-
-  unsigned inputRank = inputType.getRank();
-  if (inputRank != 4)
-    return emitOpError() << "expected rank of input is 4";
-
-  unsigned outputRank = outputType.getRank();
-  if (outputRank != 6)
-    return emitOpError() << "expected rank of output is 6";
-
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// WinogradOutputTransformOp
-//===----------------------------------------------------------------------===//
-
-LogicalResult WinogradOutputTransformOp::verify() {
-  auto valueType = cast<ShapedType>(getValue().getType());
-  auto outputType = cast<ShapedType>(getOutput().getType());
-  auto valueElemType = valueType.getElementType();
-  auto outputElemType = outputType.getElementType();
-  if (valueElemType != outputElemType) {
-    return emitOpError() << "expected element type of value " << valueElemType
-                         << " to match element type of output "
-                         << outputElemType;
-  }
-
-  unsigned valueRank = valueType.getRank();
-  if (valueRank != 6)
-    return emitOpError() << "expected rank of input is 6";
-
-  unsigned outputRank = outputType.getRank();
-  if (outputRank != 4)
-    return emitOpError() << "expected rank of output is 4";
-
-  return success();
-}
-
 //===----------------------------------------------------------------------===//
 // LinalgDialect
 //===----------------------------------------------------------------------===//

mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt

@@ -38,7 +38,6 @@ add_mlir_dialect_library(MLIRLinalgTransforms
   Transforms.cpp
   TransposeConv2D.cpp
   Vectorization.cpp
-  WinogradConv2D.cpp
 
   ADDITIONAL_HEADER_DIRS
   ${MLIR_MAIN_INCLUDE_DIR}/mlir/Dialect/Linalg