// RUN: mlir-hlo-opt -transform-unranked-hlo -split-input-file %s | FileCheck %s // Check the validity of expected IR. // CHECK-LABEL: @sqr_transform_result func @sqr_transform_result(%a: tensor<*xf32>) -> tensor<*xf32> { // Flatten operand shape. %shape = shape.shape_of %a : tensor<*xf32> %num_elements = shape.num_elements %shape %num_elements_as_index = shape.size_to_index %num_elements %flat_shape = tensor_from_elements(%num_elements_as_index) : tensor<1xindex> %flat_a = "xla_hlo.dynamic_reshape"(%a, %flat_shape) : (tensor<*xf32>, tensor<1xindex>) -> tensor // Apply operation. %flat_b = "xla_hlo.sqrt"(%flat_a) : (tensor) -> tensor // Restore original shape. %shape_as_extent_tensor = shape.to_extent_tensor %shape : tensor %b = "xla_hlo.dynamic_reshape"(%flat_b, %shape_as_extent_tensor) : (tensor, tensor) -> tensor<*xf32> return %b : tensor<*xf32> } // ----- // Check transformation of unranked code. // CHECK-LABEL: @sqrt // CHECK-SAME: (%[[A:.*]]: tensor<*xf32>) func @sqrt(%a: tensor<*xf32>) -> tensor<*xf32> { // CHECK-NEXT: %[[SHAPE:.*]] = shape.shape_of %[[A]] : tensor<*xf32> // CHECK-NEXT: %[[NUM_ELEMENTS:.*]] = shape.num_elements %[[SHAPE]] // CHECK-NEXT: %[[NUM_ELEMENTS_AS_INDEX:.*]] = shape.size_to_index %[[NUM_ELEMENTS]] // CHECK-NEXT: %[[FLAT_SHAPE:.*]] = tensor_from_elements(%[[NUM_ELEMENTS_AS_INDEX]]) : tensor<1xindex> // CHECK-NEXT: %[[FLAT_A:.*]] = "xla_hlo.dynamic_reshape"(%[[A]], %[[FLAT_SHAPE]]) : (tensor<*xf32>, tensor<1xindex>) -> tensor // CHECK-NEXT: %[[FLAT_B:.*]] = "xla_hlo.sqrt"(%[[FLAT_A]]) : (tensor) -> tensor // CHECK-NEXT: %[[SHAPE_AS_EXTENT_TENSOR:.*]] = shape.to_extent_tensor %[[SHAPE]] : tensor // CHECK-NEXT: %[[B:.*]] = "xla_hlo.dynamic_reshape"(%[[FLAT_B]], %[[SHAPE_AS_EXTENT_TENSOR]]) : (tensor, tensor) -> tensor<*xf32> // CHECK-NEXT: return %[[B]] : tensor<*xf32> %b = "xla_hlo.sqrt"(%a) : (tensor<*xf32>) -> tensor<*xf32> return %b : tensor<*xf32> } // ----- // Not transformed when ranked. // CHECK-LABEL: @sqrt_ranked // CHECK-SAME: (%[[A:.*]]: tensor<3x?xf32>) func @sqrt_ranked(%a: tensor<3x?xf32>) -> tensor<3x?xf32> { // CHECK-NEXT: %[[B:.*]] = "xla_hlo.sqrt"(%[[A]]) : (tensor<3x?xf32>) -> tensor<3x?xf32> // CHECK-NEXT: return %[[B]] : tensor<3x?xf32> %b = "xla_hlo.sqrt"(%a) : (tensor<3x?xf32>) -> tensor<3x?xf32> return %b : tensor<3x?xf32> } // ----- // Not transformed when statically shaped. // CHECK-LABEL: @sqrt_static // CHECK-SAME: (%[[A:.*]]: tensor<2x3xf32>) func @sqrt_static(%a: tensor<2x3xf32>) -> tensor<2x3xf32> { // CHECK-NEXT: %[[B:.*]] = "xla_hlo.sqrt"(%[[A]]) : (tensor<2x3xf32>) -> tensor<2x3xf32> // CHECK-NEXT: return %[[B]] : tensor<2x3xf32> %b = "xla_hlo.sqrt"(%a) : (tensor<2x3xf32>) -> tensor<2x3xf32> return %b : tensor<2x3xf32> } // ----- // CHECK-LABEL: @add_unranked // CHECK-SAME: (%[[A:.*]]: tensor<*xf32>, %[[B:.*]]: tensor<*xf32>) -> tensor<*xf32> func @add_unranked(%a : tensor<*xf32>, %b : tensor<*xf32>) -> tensor<*xf32> { // CHECK: %[[SHAPE_A:.*]] = shape.shape_of %[[A]] // CHECK: %[[SHAPE_B:.*]] = shape.shape_of %[[B]] // CHECK: %[[SHAPE:.*]] = shape.any %[[SHAPE_A]], %[[SHAPE_B]] // CHECK: %[[NUM_ELEMENTS:.*]] = shape.num_elements %[[SHAPE]] // CHECK: %[[NUM_ELEMENTS_AS_INDEX:.*]] = shape.size_to_index %[[NUM_ELEMENTS]] // CHECK: %[[FLAT_SHAPE:.*]] = tensor_from_elements(%[[NUM_ELEMENTS_AS_INDEX]]) : tensor<1xindex> // CHECK: %[[FLAT_A:.*]] = "xla_hlo.dynamic_reshape"(%[[A]], %[[FLAT_SHAPE]]) : (tensor<*xf32>, tensor<1xindex>) -> tensor // CHECK: %[[FLAT_B:.*]] = "xla_hlo.dynamic_reshape"(%[[B]], %[[FLAT_SHAPE]]) : (tensor<*xf32>, tensor<1xindex>) -> tensor // CHECK: %[[FLAT_RESULT:.*]] = xla_hlo.add %[[FLAT_A]], %[[FLAT_B]] : tensor // CHECK: %[[SHAPE_AS_EXTENT_TENSOR:.*]] = shape.to_extent_tensor %[[SHAPE]] : tensor // CHECK: %[[RESULT:.*]] = "xla_hlo.dynamic_reshape"(%[[FLAT_RESULT]], %[[SHAPE_AS_EXTENT_TENSOR]]) : (tensor, tensor) -> tensor<*xf32> // CHECK: return %[[RESULT]] : tensor<*xf32> %result = xla_hlo.add %a, %b : tensor<*xf32> return %result : tensor<*xf32> }