if (!mlir::cast<ShapedType>(conv_op.getRhs().getType()).hasStaticShape()) {
      return false;
    }
    if (!mlir::cast<ShapedType>(conv_op.getLhs().getType()).hasStaticShape() &&
        !mlir::cast<ShapedType>(conv_op.getType()).hasStaticShape()) {
      auto dnums = conv_op.getDimensionNumbers();
      auto lhs_type = mlir::cast<ShapedType>(conv_op.getLhs().getType());

                           array[i].cast<mlir::StringAttr>().getValue().str());
    } else if (llvm::isa<mlir::vhlo::BooleanV1Attr>(array[i])) {
      flex_builder->Bool(name.c_str(),
                         array[i].cast<mlir::vhlo::BooleanV1Attr>().getValue());
    } else if (llvm::isa<mlir::vhlo::StringV1Attr>(array[i])) {
      flex_builder->String(
          name.c_str(),

  }

  // Get the tensor types.
  const auto input_type = input_tensor.getType().cast<ShapedType>();
  const auto weights_type = weights_tensor.getType().cast<ShapedType>();
  const auto bias_type =
      has_bias ? bias_tensor.getType().cast<ShapedType>() : ShapedType{};

  const auto output_type = getType(0).cast<ShapedType>();

  // Folding only implemented for float tensors.

  }
}

LogicalResult SpaceToBatchNDOp::verify() {
  SpaceToBatchNDOp op = *this;
  const auto input_type = op.getInput().getType().cast<TensorType>();
  const auto block_shape_type = op.getBlockShape().getType().cast<TensorType>();
  const auto paddings_type = op.getPaddings().getType().cast<TensorType>();

  // Check that block_shape has rank 1.
  if (!IsOfRankOrUnranked(op.getBlockShape(), 1)) {

  auto input_args_have_static_shape = [&]() -> bool {
    return mlir::cast<TensorType>(input_tensor.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(kernel_tensor.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(window_strides.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(padding.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(lhs_dilation.getType()).hasStaticShape() &&

          CPred<"$_op.getOperand(0).getType().cast<ShapedType>().getRank() <= 1">,
          CPred<"$_op.getOperand(0).getType().cast<ShapedType>().getRank() == 2 && !$_op.getOperand(0).getType().cast<ShapedType>().hasStaticShape()">,
          CPred<"$_op.getOperand(0).getType().cast<ShapedType>().getRank() == 2 && $_op.getOperand(0).getType().cast<ShapedType>().getShape()[1] <= 4">]>>]> {

// CHECK-LABEL: Tanh
// CHECK:  "tfl.tanh"(%arg0) : (tensor<1xf32>) -> tensor<1xf32>
}

func.func @cast(%arg0: tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32> {
  %0 = "tf.Cast"(%arg0) : (tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32>
  func.return %0 : tensor<1x2x2x5xf32>

  // CHECK-LABEL: cast
  // CHECK: "tfl.cast"(%arg0) : (tensor<1x2x2x5xi32>) -> tensor<1x2x2x5xf32>
}

    // CHECK-SAME: (tensor<*xf32>) -> tensor<*xi8>
    // CHECK: %[[TENSOR_CAST:.*]] = tensor.cast %[[CAST_RESULT_2]] : tensor<*xi8> to tensor<?x?x?x?xi8>
    %2 = tensor.cast %28 : tensor<*xi8> to tensor<?x?x?x?xi8>
    // CHECK: %[[CAST_RESULT_0:.*]] = "tf.Cast"(%arg0)
    // CHECK-SAME: (tensor<16x194x199x4xf32>) -> tensor<16x194x199x4xui8>
    // CHECK: %[[CAST_RESULT_1:.*]] = "tf.Cast"(%arg0)

;border-radius:.5rem;transition:background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out,-webkit-transform .15s ease-in-out;transition:transform .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out;transition:transform .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out,-webkit-transform .15s ease-in-out}@media (prefers-reduced-motion:reduce){.custom-switch...

;border-radius:.5rem;transition:background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out,-webkit-transform .15s ease-in-out;transition:transform .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out;transition:transform .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out,-webkit-transform .15s ease-in-out}@media (prefers-reduced-motion:reduce){.custom-switch...