diff --git a/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/BufferizableOpInterface.cpp b/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/BufferizableOpInterface.cpp
--- a/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/BufferizableOpInterface.cpp
+++ b/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/BufferizableOpInterface.cpp
@@ -400,20 +400,19 @@
   if (isa<memref::BufferCastOp, memref::TensorLoadOp>(op))
     return success();
 
-  // Check if op has tensor results or operands.
-  auto isaTensor = [](Type t) { return t.isa<TensorType>(); };
-  bool hasTensorResult = any_of(op->getResultTypes(), isaTensor);
-  bool hasTensorOperand = any_of(op->getOperandTypes(), isaTensor);
-  if (!hasTensorResult && !hasTensorOperand)
-    return success();
-
   // Bufferize using `BufferizableOpInterface`.
   b.setInsertionPoint(op);
   if (auto bufferizableOp = dyn_cast<BufferizableOpInterface>(op))
     return bufferizableOp.bufferize(b, state);
 
-  // Other op with tensors. No bufferization method specified.
-  return op->emitError() << "unsupported op with tensors";
+  // Check if op has tensor results or operands.
+  auto isaTensor = [](Type t) { return t.isa<TensorType>(); };
+  bool hasTensorResult = any_of(op->getResultTypes(), isaTensor);
+  bool hasTensorOperand = any_of(op->getOperandTypes(), isaTensor);
+  if (hasTensorResult && hasTensorOperand)
+    return op->emitError() << "unsupported op with tensors";
+
+  return success();
 }
 
 //===----------------------------------------------------------------------===//
diff --git a/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/ComprehensiveBufferize.cpp b/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/ComprehensiveBufferize.cpp
--- a/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/ComprehensiveBufferize.cpp
+++ b/mlir/lib/Dialect/Linalg/ComprehensiveBufferize/ComprehensiveBufferize.cpp
@@ -2454,14 +2454,14 @@
   LogicalResult bufferize(Operation *op, OpBuilder &b,
                           BufferizationState &state) const {
     auto transferReadOp = cast<vector::TransferReadOp>(op);
+    if (!transferReadOp.getShapedType().isa<TensorType>())
+      return success();
 
     // Take a guard before anything else.
     OpBuilder::InsertionGuard g(b);
     b.setInsertionPoint(op);
 
     // TransferReadOp always reads from the bufferized op.source().
-    assert(transferReadOp.getShapedType().isa<TensorType>() &&
-           "only tensor types expected");
     Value v = state.lookupBuffer(transferReadOp.source());
     transferReadOp.sourceMutable().assign(v);
     return success();
@@ -2501,6 +2501,8 @@
   LogicalResult bufferize(Operation *op, OpBuilder &b,
                           BufferizationState &state) const {
     auto writeOp = cast<vector::TransferWriteOp>(op);
+    if (!writeOp.getShapedType().isa<TensorType>())
+      return success();
 
     // Take a guard before anything else.
     OpBuilder::InsertionGuard g(b);
@@ -2509,8 +2511,6 @@
     // Create a new transfer_write on buffer that doesn't have a return value.
     // Leave the previous transfer_write to dead code as it still has uses at
     // this point.
-    assert(writeOp.getShapedType().isa<TensorType>() &&
-           "only tensor types expected");
     Value resultBuffer = getResultBuffer(b, op->getResult(0), state);
     if (!resultBuffer)
       return failure();