[mlir][linalg] Do not check if added dimension are static in linalg.broadcast.

Added dimensions can be both static and dinamic. Mapped dimension should be the same in the input and the init.

Differential Revision: https://reviews.llvm.org/D138291

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

@@ -1543,13 +1543,7 @@ LogicalResult BroadcastOp::verify() {
   }
 
   for (const auto &[idx, inputDimIdx] : llvm::enumerate(reverseDimMap)) {
-    if (inputDimIdx == kUnmappedDim) {
-      // This dimensions is being added. Should be statically known.
-      if (ShapedType::isDynamic(initShape[idx]))
-        return emitOpError()
-               << "init dim " << idx
-               << " can't be dynamic, because it's not matched to input";
-    } else {
+    if (inputDimIdx != kUnmappedDim) {
       // This dimensions is mapped from the input. Init and input dims should
       // match.
       if (inputShape[inputDimIdx] != initShape[idx])

mlir/test/Dialect/Linalg/invalid.mlir

@@ -728,19 +728,6 @@ func.func @broadcast_mapped_dim_mismatch(
 
 // -----
 
-func.func @broadcast_added_dynamic_mismatch(
-    %input: tensor<4x16xf32>, %init: tensor<4x?x16xf32>)
-    -> tensor<4x?x16xf32> {
-  // expected-error @+1 {{'linalg.broadcast' op init dim 1 can't be dynamic, because it's not matched to input}}
-  %bcast = linalg.broadcast
-      ins(%input:tensor<4x16xf32>)
-      outs(%init:tensor<4x?x16xf32>)
-      dimensions = [0, 2]
-  func.return %bcast : tensor<4x?x16xf32>
-}
-
-// -----
-
 func.func @broadcast_size_1_extension_not_supported(
     %input: tensor<1x16xf32>, %init: tensor<4x?x16xf32>)
     -> tensor<4x?x16xf32> {