// Run legalize pass and then optimize pass, and make sure some fusing is applied.
// RUN: tf-opt %s -tfl-legalize-tf -tfl-optimize | FileCheck --check-prefix=Fusing %s
// Run legalize pass and then optimize pass, and make sure some fusing is applied, but no mul->fc.
// RUN: tf-opt %s -tfl-legalize-tf -tfl-optimize='disable-fuse-mul-and-fc=true' | FileCheck --check-prefix=NoFusing %s

//
// For more details on backpropagation for convolution of which `AvgPoolGrad`
// is a special case see `tensorflow/core/kernels/conv_grad_ops.h`.
// `tensorflow/compiler/mlir/xla/tests/legalize-tf.mlir` has more
// examples for different cases.
template <typename OpTy, int num_dims>
class ConvertAvgPoolGradOp : public OpRewritePattern<OpTy> {
  using DimVector = SmallVector<int64_t, num_dims>;

// NOTE: Assertions have been autogenerated by utils/generate-test-checks.py
// RUN: odml-to-stablehlo-opt -tf-legalize-hlo -verify-diagnostics %s | FileCheck %s

// CHECK-LABEL:   func @biasAdd_NHWC(
// CHECK-SAME:                       %[[VAL_0:.*]]: tensor<1x32x10x32xi32>,
// CHECK-SAME:                       %[[VAL_1:.*]]: tensor<32xi32>) -> tensor<1x32x10x32xi32> {