%output_shape = arith.constant dense<[2, 3, 2, 2048]> : tensor<4xi32>
  %f16_weights = "tfl.pseudo_const"() {value = dense<1.0> : tensor<4x2x2x2048xf16>} : () -> tensor<4x2x2x2048xf16>
  %dq_weights = "tfl.dequantize"(%f16_weights) : (tensor<4x2x2x2048xf16>) -> tensor<4x2x2x2048xf32>
  %bias = "tfl.no_value"() {value} : () -> none

def LegalizeSparseToDense : Pat<
  (TF_SparseToDenseOp $sparse_indices, $output_shape, $sparse_values,
    $default_value, $validate_indices),
  (TFL_SparseToDenseOp $sparse_indices, $output_shape, $sparse_values,
    $default_value)>;

def LegalizeUnique : Pat<(TF_UniqueOp $arg0),(TFL_UniqueOp $arg0)>;

      CompileTimeConstantOperand<TF::SegmentSumV2Op, 2>,   // $num_segments
      CompileTimeConstantOperand<TF::SliceOp, 1, 2>,       // $begin, $size
      CompileTimeConstantOperand<TF::SparseToDenseOp, 1>,  // $output_shape
      CompileTimeConstantOperand<TF::SplitOp, 0>,          // $split_dim
      // $size_splits, $split_dim
      CompileTimeConstantOperand<TF::SplitVOp, 1, 2>,

  Value none = rewriter.create<TFL::NoValueOp>(
      op->getLoc(), rewriter.getNoneType(), rewriter.getUnitAttr());

  Value output_shape =
      CreateCastToInt32(tf_op.getInputSizes(), op->getLoc(), rewriter);

  rewriter.replaceOpWithNewOp<TFL::Conv3DTransposeOp>(
      op, tf_op.getType(), output_shape, tf_op.getFilter(),
      tf_op.getOutBackprop(),
      /*bias=*/none, dilation_depth_factor, dilation_height_factor,

    "tf.Yield"(%1) : (tensor<5xf32>) -> ()
  }) {device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0", metadata = "", operandSegmentSizes = array<i32: 1, 2, 1>, output_shapes = [#tf_type.shape<>], output_types = [!tf_type.string]} : (tensor<4xf32>, tensor<3xf32>, tensor<!tf_type.resource>, tensor<2xf32>) -> tensor<!tf_type.variant>
  return
}

// -----