code: def test_alpha_share_layer():
      """Test invoking AlphaShareLayer."""
      batch_size = 10
      length = 6
      input1 = np.random.rand(batch_size, length).astype(np.float32)
      input2 = np.random.rand(batch_size, length).astype(np.float32)
      layer = layers.AlphaShareLayer()
      result = layer([input1, input2])
      assert input1.shape == result[0].shape
      assert input2.shape == result[1].shape
  
      # Creating a second layer should produce different results, since it has
      # different random weights.
  
      layer2 = layers.AlphaShareLayer()
      result2 = layer2([input1, input2])
      assert not np.allclose(result[0], result2[0])
      assert not np.allclose(result[1], result2[1])
  
      # But evaluating the first layer again should produce the same result as before.
  
      result3 = layer([input1, input2])
      assert np.allclose(result[0], result3[0])
      assert np.allclose(result[1], result3[1])
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 20 for calling a global function with example usage: test_alpha_share_layer() without return types