Transpose using perm attribute.

src/dialect/onnx/onnx_ops.cpp

@@ -407,11 +407,25 @@ void ONNXTransposeOp::inferShapes() {
 
   // Naive transposition which handles the default case of
   // reversing the shape of the tensor (similar to numpy.transpose).
-  // TODO: Once attributes are supported we can handle the case where the
+  auto arrayTy = getOperand()->getType().cast<RankedTensorType>();
-  // transposition uses a permutation vector to interchange the axes.
+  SmallVector<int64_t, 2> dims;
-  auto arrayTy = getOperand().getType().cast<RankedTensorType>();
+
-  SmallVector<int64_t, 2> dims(llvm::reverse(arrayTy.getShape()));
+  if (auto permutation = getAttrOfType<ArrayAttr>(
-  getResult().setType(RankedTensorType::get(dims, arrayTy.getElementType()));
+          ONNXTransposeOp::getPermAttrName())) {
+    // Perform transposition according to perm attribute.
+    for (auto perm : permutation.getValue()) {
+      int32_t index = perm.cast<IntegerAttr>().getInt();
+      if (index < 0)
+        emitError("Cannot tranpose when permutation contains negative index.");
+      dims.emplace_back(arrayTy.getShape()[index]);
+    }
+  } else {
+    // Default
+    for (auto shape : llvm::reverse(arrayTy.getShape()))
+      dims.emplace_back(shape);
+  }
+
+  getResult()->setType(RankedTensorType::get(dims, arrayTy.getElementType()));
 }
 
 //===----------------------------------------------------------------------===//

src/dialect/onnx/onnxop.inc

@@ -3098,6 +3098,10 @@ def ONNXTransposeOp:ONNX_Op<"Transpose",
   }];
   let arguments = (ins AnyTypeOf<[AnyMemRef, AnyTensor]>:$data);
   let results = (outs AnyTypeOf<[AnyMemRef, AnyTensor]>);
+
+  let extraClassDeclaration = [{
+    static StringRef getPermAttrName() { return "perm"; }
+  }];
 }
 
 def ONNXUniqueOp:ONNX_Op<"Unique",