code: def expected_output_np(self, input_np, weight_np, bias_np, bias):
      ref_np = tvm.topi.testing.dense(
          np.reshape(input_np, (input_np.shape[0], input_np.shape[-1])),
          weight_np.T,  # Function expects [in_dim, out_dim]
          bias_np,
          use_bias=bias,
          out_dtype="float32"
          if "int" in str(input_np.dtype)
          else input_np.dtype,
      )
      return ref_np
  
imports: import pytest
  import numpy
  from tvm import te, topi
  import tvm.testing
  from tvm.topi import testing
  from tvm.contrib.hexagon.build import HexagonLauncher
  from tvm.contrib.hexagon.session import Session
  import tvm.topi.hexagon.qnn
  import tvm.topi.hexagon.slice_ops
  from ...infrastructure import transform_numpy, quantize_np
  from tvm.contrib.hexagon import allocate_hexagon_array
label_desc: Use image node_id 1 for calling the TestDenseSlice obj's underlying member method code with example usage: obj.expected_output_np(input_np, weight_np, bias_np, bias) and returns: ref_np