DenseIntElementsAttr perm1);

// Default implementation of `LayoutSensitiveInterface::UpdateDataFormat` for
// layout sensitive operations that do not have any additional layout dependent
// attributes besides `data_format` string.
template <typename Op>
LogicalResult UpdateDataFormat(StringRef data_format, Op *op) {
  auto perm = GetDataFormatPermutation(op->getDataFormat(), data_format);

              "found "
           << feature_dim << " and " << bias_len << ", respectively";
  }
  return success();
}

LogicalResult BiasAddOp::UpdateDataFormat(StringRef data_format) {
  return ::mlir::TF::UpdateDataFormat(data_format, this);
}

StringRef BiasAddOp::GetOptimalLayout(const RuntimeDevices& devices) {
  // Keep current data format if no GPUs are available or if explicit placement

    >,
    InterfaceMethod<
      [{Updates operation attributes and operands to account for the updated
        data format. If data format is not supported, must return failure.}],
      "LogicalResult", "UpdateDataFormat", (ins "StringRef":$data_format)
    >,
  ];

  let verify = [{
    return VerifyLayoutSensitiveInterface($_op);
  }];
}

      return DenseIntElementsAttr::get(perm_ty, permutation);
    };

    // Change operation data format.
    if (failed(layout_sensitive_interface.UpdateDataFormat(target_data_format)))
      return;

    // Permute arguments into the target data format.
    builder.setInsertionPoint(op);
    auto arg_perm = builder.create<ConstOp>(loc, perm_attr(args_permutation));

    SmallVector<unsigned, 4> GetLayoutDependentArgs() { return {0}; }
    SmallVector<unsigned, 4> GetLayoutDependentResults() { return {0}; }
    StringRef GetOptimalLayout(const RuntimeDevices& devices);
    LogicalResult UpdateDataFormat(StringRef data_format);
  }];

  let hasVerifier = 1;
}

def TF_BiasAddGradOp : TF_Op<"BiasAddGrad", [Pure]> {
  let summary = [{
The backward operation for "BiasAdd" on the "bias" tensor.