diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td b/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
index 7326192f418..86427932c1e 100644
--- a/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
+++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
@@ -8437,6 +8437,31 @@ output_handle: The list.
   TF_DerivedOperandTypeAttr element_dtype = TF_DerivedOperandTypeAttr<0>;
 }
 
+def TF_TensorListGatherOp : TF_Op<"TensorListGather", [NoSideEffect]> {
+  let summary = "Creates a Tensor by indexing into the TensorList.";
+
+  let description = [{
+Each row in the produced Tensor corresponds to the element in the TensorList
+specified by the given index (see `tf.gather`).
+
+input_handle: The input tensor list.
+indices: The indices used to index into the list.
+values: The tensor.
+  }];
+
+  let arguments = (ins
+    TF_VariantTensor:$input_handle,
+    I32Tensor:$indices,
+    I32Tensor:$element_shape
+  );
+
+  let results = (outs
+    TF_Tensor:$values
+  );
+
+  TF_DerivedResultTypeAttr element_dtype = TF_DerivedResultTypeAttr<0>;
+}
+
 def TF_TensorListGetItemOp : TF_Op<"TensorListGetItem", [NoSideEffect]> {
   let summary = "";
 
diff --git a/tensorflow/compiler/mlir/tensorflow/tests/tensor_list_ops_decomposition.mlir b/tensorflow/compiler/mlir/tensorflow/tests/tensor_list_ops_decomposition.mlir
index 9e43cea1003..682da38fc56 100644
--- a/tensorflow/compiler/mlir/tensorflow/tests/tensor_list_ops_decomposition.mlir
+++ b/tensorflow/compiler/mlir/tensorflow/tests/tensor_list_ops_decomposition.mlir
@@ -94,7 +94,7 @@ func @main(%arg0: tensor<i32>) -> (tensor<f32>, tensor<10xf32>, tensor<i32>) {
 func @main(%arg0: tensor<i32>, %arg1: tensor<10xf32>) -> tensor<f32> {
   // CHECK-NEXT: "tf.Const"() {value = dense<[]> : tensor<0xi32>}
   %elem_shape = "tf.Const"() {value = dense<[]> : tensor<0xi32>} : () -> tensor<0xi32>
-  // CHECK-NEXT: %[[BUFFER:.*]] = "tf.Identity"(%arg1) : (tensor<10xf32>) -> tensor<10xf32>
+  // CHECK-NEXT: %[[BUFFER:.*]] = "tf.Identity"(%[[ARG1]]) : (tensor<10xf32>) -> tensor<10xf32>
   // CHECK-NEXT: %[[SIZE:.*]] = "tf.Const"() {value = dense<10> : tensor<1xi32>} : () -> tensor<1xi32>
   %tl = "tf.TensorListFromTensor"(%arg1, %elem_shape) : (tensor<10xf32>, tensor<0xi32>) -> tensor<!tf.variant<tensor<f32>>>
   // CHECK-NEXT: %[[SIZE_SHAPE:.*]] = "tf.Const"() {value = dense<1> : tensor<1xi32>}
@@ -110,6 +110,37 @@ func @main(%arg0: tensor<i32>, %arg1: tensor<10xf32>) -> tensor<f32> {
 
 // -----
 
+// Test tensor list element shape op.
+
+// CHECK-LABEL: func @main
+func @main(%arg0: tensor<10x8x9xf32>) -> tensor<2xi64> {
+  %elem_shape = "tf.Const"() {value = dense<[8, 9]> : tensor<2xi32>} : () -> tensor<2xi32>
+  %tl = "tf.TensorListFromTensor"(%arg0, %elem_shape) : (tensor<10x8x9xf32>, tensor<2xi32>) -> tensor<!tf.variant<tensor<8x9xf32>>>
+  // CHECK: %[[SHAPE:.*]] = "tf.Const"() {value = dense<[8, 9]> : tensor<2xi64>} : () -> tensor<2xi64>
+  %shape = "tf.TensorListElementShape"(%tl) : (tensor<!tf.variant<tensor<8x9xf32>>>) -> tensor<2xi64>
+  // CHECK-NEXT:  return %[[SHAPE]] : tensor<2xi64>
+  return %shape: tensor<2xi64>
+}
+
+// -----
+
+// Test tensor list gather op.
+
+// CHECK-LABEL: func @main
+// CHECK-SAME: (%[[ARG0:.*]]: tensor<10x8x9xf32>, %[[ARG1:.*]]: tensor<3xi32>) -> tensor<3x8x9xf32>
+func @main(%arg0: tensor<10x8x9xf32>, %arg1: tensor<3xi32>) -> tensor<3x8x9xf32> {
+  %elem_shape = "tf.Const"() {value = dense<[8, 9]> : tensor<2xi32>} : () -> tensor<2xi32>
+  // CHECK: %[[BUFFER:.*]] = "tf.Identity"(%[[ARG0]]) : (tensor<10x8x9xf32>) -> tensor<10x8x9xf32>
+  %tl = "tf.TensorListFromTensor"(%arg0, %elem_shape) : (tensor<10x8x9xf32>, tensor<2xi32>) -> tensor<!tf.variant<tensor<8x9xf32>>>
+  // CHECK: %[[AXIS:.*]] = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
+  // CHECK: %[[GATHER:.*]] = "tf.GatherV2"(%[[BUFFER]], %[[ARG1]], %[[AXIS]]) : (tensor<10x8x9xf32>, tensor<3xi32>, tensor<i32>) -> tensor<3x8x9xf32>
+  %gather = "tf.TensorListGather"(%tl, %arg1, %elem_shape) : (tensor<!tf.variant<tensor<8x9xf32>>>, tensor<3xi32>, tensor<2xi32>) -> tensor<3x8x9xf32>
+  // CHECK-NEXT:  return %[[GATHER]] : tensor<3x8x9xf32>
+  return %gather: tensor<3x8x9xf32>
+}
+
+// -----
+
 // Tests while loop.
 
 // CHECK-LABEL: func @main
diff --git a/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.cc b/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.cc
index 3a645fe9bf6..d9715d11922 100644
--- a/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.cc
+++ b/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.cc
@@ -53,14 +53,16 @@ Value CreateScalarConst(int value, OpBuilder builder, Location loc) {
       loc, tensorflow::ConvertTensor(scalar_tensor, &builder).ValueOrDie());
 }
 
-Value GetR1Const(ArrayRef<int64_t> r1, OpBuilder builder, Location loc) {
-  tensorflow::Tensor shape_tensor(tensorflow::DT_INT32,
-                                  {static_cast<int64_t>(r1.size())});
-  for (int i = 0; i < r1.size(); ++i) {
-    shape_tensor.vec<tensorflow::int32>()(i) = r1[i];
-  }
+Value GetR1Const(ArrayRef<int64_t> r1, OpBuilder builder, Location loc,
+                 int bitwidth) {
+  llvm::SmallVector<APInt, 4> values;
+  int64_t rank = r1.size();
+  values.reserve(rank);
+  for (int i = 0; i < rank; ++i) values.push_back(APInt(bitwidth, r1[i]));
+  auto result_type = RankedTensorType::get(
+      {rank}, IntegerType::get(bitwidth, builder.getContext()));
   return builder.create<TF::ConstOp>(
-      loc, tensorflow::ConvertTensor(shape_tensor, &builder).ValueOrDie());
+      loc, DenseElementsAttr::get(result_type, values));
 }
 
 Value GetIndicesForElement(Value index, Value buffer, OpBuilder builder,
diff --git a/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.h b/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.h
index f0e0eda3b5d..423797279d3 100644
--- a/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.h
+++ b/tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.h
@@ -36,8 +36,9 @@ namespace collection_ops_util {
 // Creates an i32 scalar tf.Const.
 Value CreateScalarConst(int value, OpBuilder builder, Location loc);
 
-// Creates an i32 vector tf.Const.
-Value GetR1Const(ArrayRef<int64_t> r1, OpBuilder builder, Location loc);
+// Creates an integer vector tf.Const.
+Value GetR1Const(ArrayRef<int64_t> r1, OpBuilder builder, Location loc,
+                 int bitwidth = 32);
 
 // Returns the type of the size tensor used to track a data structure's element
 // count. It is a tensor<1xi32>, and we use R1 instead of a scalar because it is
diff --git a/tensorflow/compiler/mlir/tensorflow/transforms/tensor_list_ops_decomposition.cc b/tensorflow/compiler/mlir/tensorflow/transforms/tensor_list_ops_decomposition.cc
index 277146d5c42..d8ae4fb534a 100644
--- a/tensorflow/compiler/mlir/tensorflow/transforms/tensor_list_ops_decomposition.cc
+++ b/tensorflow/compiler/mlir/tensorflow/transforms/tensor_list_ops_decomposition.cc
@@ -574,6 +574,37 @@ LogicalResult HandleTensorListLengthOp(
   return success();
 }
 
+LogicalResult HandleTensorListElementShapeOp(
+    TF::TensorListElementShapeOp elem_shape,
+    const llvm::SmallDenseMap<Value, SizeInfo>& buffer_to_size) {
+  if (buffer_to_size.count(elem_shape.input_handle()) == 0) {
+    return elem_shape.emitOpError("unknown tensor list");
+  }
+  auto buffer = elem_shape.input_handle();
+  auto result = cutil::GetR1Const(
+      buffer.getType().cast<RankedTensorType>().getShape().drop_front(),
+      OpBuilder(elem_shape), elem_shape.getLoc(),
+      elem_shape.shape_type().getIntOrFloatBitWidth());
+  elem_shape.element_shape().replaceAllUsesWith(result);
+  elem_shape.erase();
+  return success();
+}
+
+LogicalResult HandleTensorListGatherOp(
+    TF::TensorListGatherOp gather,
+    const llvm::SmallDenseMap<Value, SizeInfo>& buffer_to_size) {
+  auto it = buffer_to_size.find(gather.input_handle());
+  if (it == buffer_to_size.end()) {
+    return gather.emitOpError("unknown tensor list");
+  }
+  auto buffer = gather.input_handle();
+  auto result = cutil::GatherElements(gather.indices(), buffer,
+                                      OpBuilder(gather), gather.getLoc());
+  gather.values().replaceAllUsesWith(result);
+  gather.erase();
+  return success();
+}
+
 LogicalResult DecomposeTensorListOpsInternal(
     Block* block, ModuleOp module,
     llvm::SmallDenseMap<Value, SizeInfo>* buffer_to_size,
@@ -619,6 +650,15 @@ LogicalResult DecomposeTensorListOpsInternal(
     } else if (auto stack = llvm::dyn_cast<TF::TensorListStackOp>(&op)) {
       stack.tensor().replaceAllUsesWith(stack.input_handle());
       stack.erase();
+    } else if (auto elem_shape =
+                   llvm::dyn_cast<TF::TensorListElementShapeOp>(&op)) {
+      if (failed(HandleTensorListElementShapeOp(elem_shape, *buffer_to_size))) {
+        return failure();
+      }
+    } else if (auto gather = llvm::dyn_cast<TF::TensorListGatherOp>(&op)) {
+      if (failed(HandleTensorListGatherOp(gather, *buffer_to_size))) {
+        return failure();
+      }
     } else if (auto addn = llvm::dyn_cast<TF::AddNOp>(&op)) {
       auto it = buffer_to_size->find(addn.getOperand(0));
       if (it != buffer_to_size->end()) {