code: def test_pvt_block():
      # test PVT structure and forward
      block = PVTEncoderLayer(
          embed_dims=64, num_heads=4, feedforward_channels=256
      )
      assert block.ffn.embed_dims == 64
      assert block.attn.num_heads == 4
      assert block.ffn.feedforward_channels == 256
      x = torch.randn(1, 56 * 56, 64)
      x_out = block(x, (56, 56))
      assert x_out.shape == torch.Size([1, 56 * 56, 64])
  
imports: import pytest
  import torch
  from mmdet.models.backbones.pvt import PVTEncoderLayer, PyramidVisionTransformer, PyramidVisionTransformerV2
label_desc: Use image node_id 1 for calling a global function with example usage: test_pvt_block() without return types