code: def test__shift_to_the_right():
      # create a sample input tensor with shape [B, C, seq_len]
      B, seq_length, hidden_dim = 2, 3, 4
      x = torch.randn(B, seq_length, hidden_dim)
  
      # shift x to the right and prefix it with zeros
      y = StartSym._shift_to_the_right(x)
      # check shapes
      assert y.shape == x.shape
      # check equality of elements
      assert torch.equal(y[:, 0, :], x.new_zeros(B, hidden_dim))
      assert torch.equal(y[:, 1:, :], x[:, :-1, :])
      # create a sample prefix tensor with shape [B, 1, hidden_dim] and prefix x
      prefix = torch.randn(B, 1, hidden_dim)
      y = StartSym._shift_to_the_right(x, prefix=prefix)
      # check shapes
      assert y.shape == x.shape
      # check equality of elements
      assert torch.equal(y[:, [0], :], prefix)
      assert torch.equal(y[:, 1:, :], x[:, :-1, :])
  
imports: import pytest
  import torch
  from projects.torch_vct.neural.entropy_model_layers import LearnedPosition, StartSym, TransformerBlock
label_desc: Use image node_id 1 for calling a global function with example usage: test__shift_to_the_right() without return types