normal_test.py 文件源码

def testNormalLogPDFMultidimensional(self):
    with self.test_session():
      batch_size = 6
      mu = constant_op.constant([[3.0, -3.0]] * batch_size)
      sigma = constant_op.constant([[math.sqrt(10.0), math.sqrt(15.0)]] *
                                   batch_size)
      x = np.array([[-2.5, 2.5, 4.0, 0.0, -1.0, 2.0]], dtype=np.float32).T
      normal = normal_lib.Normal(loc=mu, scale=sigma)
      expected_log_pdf = stats.norm(mu.eval(), sigma.eval()).logpdf(x)

      log_pdf = normal.log_prob(x)
      log_pdf_values = log_pdf.eval()
      self.assertEqual(log_pdf.get_shape(), (6, 2))
      self.assertAllClose(expected_log_pdf, log_pdf_values)
      self.assertAllEqual(normal.batch_shape().eval(), log_pdf.get_shape())
      self.assertAllEqual(normal.batch_shape().eval(), log_pdf.eval().shape)
      self.assertAllEqual(normal.get_batch_shape(), log_pdf.get_shape())
      self.assertAllEqual(normal.get_batch_shape(), log_pdf.eval().shape)

      pdf = normal.prob(x)
      pdf_values = pdf.eval()
      self.assertEqual(pdf.get_shape(), (6, 2))
      self.assertAllClose(np.exp(expected_log_pdf), pdf_values)
      self.assertAllEqual(normal.batch_shape().eval(), pdf.get_shape())
      self.assertAllEqual(normal.batch_shape().eval(), pdf_values.shape)
      self.assertAllEqual(normal.get_batch_shape(), pdf.get_shape())
      self.assertAllEqual(normal.get_batch_shape(), pdf_values.shape)