diff --git a/mlir/include/mlir/Dialect/Shape/IR/Shape.h b/mlir/include/mlir/Dialect/Shape/IR/Shape.h
--- a/mlir/include/mlir/Dialect/Shape/IR/Shape.h
+++ b/mlir/include/mlir/Dialect/Shape/IR/Shape.h
@@ -16,6 +16,8 @@
 
 #include "mlir/IR/Dialect.h"
 #include "mlir/IR/OpDefinition.h"
+#include "mlir/IR/OpImplementation.h"
+#include "mlir/Interfaces/InferTypeOpInterface.h"
 #include "mlir/Interfaces/SideEffects.h"
 
 namespace mlir {
diff --git a/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td b/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
--- a/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
+++ b/mlir/include/mlir/Dialect/Shape/IR/ShapeOps.td
@@ -14,6 +14,7 @@
 #define SHAPE_OPS
 
 include "mlir/IR/OpBase.td"
+include "mlir/Interfaces/InferTypeOpInterface.td"
 include "mlir/Interfaces/SideEffects.td"
 
 // TODO(jpienaar): Move to base.
@@ -168,17 +169,37 @@
   let parser = [{ return ::parse$cppClass(parser, result); }];
 }
 
-def Shape_CreateShapeOp : Shape_Op<"create_shape", []> {
-  let summary = "Creates a shape descriptor from a tensor";
+def Shape_FromExtentTensorOp : Shape_Op<"from_extent_tensor", []> {
+  let summary = "Creates a shape from a tensor of extents";
   let description = [{
-    Creates a shape from a 1D integral tensor. The rank equals the number of
-    elements in the tensor, and extent matches the values of the elements.
+    Creates a shape from a 1D integral tensor of extents. The rank of the
+    resulting shape equals the number of elements in the tensor, and the
+    extents match the values of the elements.
   }];
 
   let arguments = (ins I32Tensor:$input);
   let results = (outs Shape_ShapeType:$result);
 }
 
+def Shape_ToExtentTensorOp : Shape_Op<"to_tensor", []> {
+  let summary = "Creates a dimension tensor from a shape";
+  // TODO: Think more about the error situation. Perhaps factor out the
+  // error detection into a separate op so downstream consumers can control
+  // their error behavior. Then this op would assume that the input has
+  // been properly checked to not be an error (and could thus be a
+  // NoSideEffect op).
+  let description = [{
+    Converts a shape to a 1D integral tensor of extents. The number of elements
+    in the tensor equals the rank of the shape, and the elements equal the
+    extents of the shape.
+
+    If the shape represents an error, then this op currently aborts the program.
+  }];
+
+  let arguments = (ins Shape_ShapeType:$input);
+  let results = (outs I32Tensor:$result);
+}
+
 def Shape_JoinOp : Shape_Op<"join", []> {
   let summary = "Returns the least general shape.size of its operands";
   let description = [{
@@ -299,4 +320,50 @@
   let results =  (outs Shape_ShapeOrSizeType:$output);
 }
 
+def Shape_SplitAtOp : Shape_Op<"split_at",
+    [DeclareOpInterfaceMethods<InferTypeOpInterface>]> {
+  let summary = "Splits a shape at a given index.";
+  let description = [{
+    Splits a shape at a given dimension `index`, returning two shapes.
+    If `index` is negative, it is treated as indexing from the back of the
+    shape. This negative-handling behavior is important when handling unranked
+    shapes, where the positive index is not necessarily knowable due to a
+    dynamic number of leading dimensions.
+
+    Examples:
+    - split_at([4,5,6], index=0) -> [], [4,5,6]
+    - split_at([4,5,6], index=1) -> [4], [5,6]
+    - split_at([4,5,6], index=2) -> [4,5], [6]
+    - split_at([4,5,6], index=3) -> [4,5,6], []
+    - split_at([4,5,6], index=4) -> error
+    - split_at([4,5,6], index=-1) -> [4,5], [6]
+    - split_at([4,5,6], index=-2) -> [4], [5,6]
+    - split_at([4,5,6], index=-3) -> [], [4,5,6]
+    - split_at([4,5,6], index=-4) -> error
+
+    Requires:
+    - `index` is in the range [-rank(operand),rank(operand)]
+  }];
+
+  let arguments = (ins Shape_ShapeType:$operand, I32:$index);
+  let results = (outs Shape_ShapeType:$head, Shape_ShapeType:$tail);
+}
+
+def Shape_ConcatOp : Shape_Op<"concat",
+    [DeclareOpInterfaceMethods<InferTypeOpInterface>]> {
+  let summary = "Concatenates two shapes.";
+  let description = [{
+    Creates a shape whose dimensions consist of first the dimensions from `lhs`
+    followed by the dimensions of `rhs`.
+
+    Example:
+    concat([2,3], [4,5]) -> [2,3,4,5]
+    concat([], []) -> []
+    concat([], [4,5,6]) -> [4,5,6]
+  }];
+
+  let arguments = (ins Shape_ShapeType:$lhs, Shape_ShapeType:$rhs);
+  let results = (outs Shape_ShapeType:$result);
+}
+
 #endif // SHAPE_OPS
diff --git a/mlir/lib/Dialect/Shape/CMakeLists.txt b/mlir/lib/Dialect/Shape/CMakeLists.txt
--- a/mlir/lib/Dialect/Shape/CMakeLists.txt
+++ b/mlir/lib/Dialect/Shape/CMakeLists.txt
@@ -9,6 +9,7 @@
   )
 target_link_libraries(MLIRShape
   PUBLIC
+  MLIRInferTypeOpInterface
   MLIRIR
   MLIRSideEffects
   LLVMSupport
diff --git a/mlir/lib/Dialect/Shape/IR/Shape.cpp b/mlir/lib/Dialect/Shape/IR/Shape.cpp
--- a/mlir/lib/Dialect/Shape/IR/Shape.cpp
+++ b/mlir/lib/Dialect/Shape/IR/Shape.cpp
@@ -106,6 +106,33 @@
 
 static LogicalResult verify(ConstantOp &op) { return success(); }
 
+//===----------------------------------------------------------------------===//
+// SplitAtOp
+//===----------------------------------------------------------------------===//
+
+LogicalResult SplitAtOp::inferReturnTypes(
+    MLIRContext *context, Optional<Location> location, ValueRange operands,
+    ArrayRef<NamedAttribute> attributes, RegionRange regions,
+    SmallVectorImpl<Type> &inferredReturnTypes) {
+  auto shapeType = ShapeType::get(context);
+  inferredReturnTypes.push_back(shapeType);
+  inferredReturnTypes.push_back(shapeType);
+  return success();
+}
+
+//===----------------------------------------------------------------------===//
+// ConcatOp
+//===----------------------------------------------------------------------===//
+
+LogicalResult ConcatOp::inferReturnTypes(
+    MLIRContext *context, Optional<Location> location, ValueRange operands,
+    ArrayRef<NamedAttribute> attributes, RegionRange regions,
+    SmallVectorImpl<Type> &inferredReturnTypes) {
+  auto shapeType = ShapeType::get(context);
+  inferredReturnTypes.push_back(shapeType);
+  return success();
+}
+
 namespace mlir {
 namespace shape {