def test_baseline_generation(self):
baseline_generator = BaselineGenerator(self.model, self.data_handler,
"cpu")
embedding_list = configure_model_integ_grads_embeddings(self.model)
integrated_gradients_embedding = embedding_list[0]
self.assertTrue(
torch.allclose(
baseline_generator.generate_baseline(
integrated_gradients_embedding, 5)[0],
torch.tensor([[1, 1, 1, 1, 1]]),
))
def test_word_embeddings(self):
embedding_list = configure_model_integ_grads_embeddings(self.model)
integrated_gradients_embedding = embedding_list[0]
input = torch.arange(0, 300).unsqueeze(0).unsqueeze(0)
self.assertEqual(integrated_gradients_embedding.embedding_dim, 300)
self.assertEqual(embedding_list.embedding_dim[0], 300)
self.assertEqual(embedding_list(input).shape[2], input.shape[2])
self.assertTrue(
torch.allclose(
integrated_gradients_embedding.get_attribution_map(input)
["word"], input))