Added poisson loss, tests and documentation

    return loss

class PoissonLoss(Loss):

  """The Poisson loss function is defined as the mean of the elements of y_pred - (y_true * log(y_pred) for an input of (y_true, y_pred).

  Poisson loss is generally used for regression tasks where the data follows the poisson

  """

  def _compute_tf_loss(self, output, labels):

    import tensorflow as tf

    output, labels = _make_tf_shapes_consistent(output, labels)

    loss = tf.keras.losses.Poisson(reduction='auto')

    return loss(labels, output)

  def _create_pytorch_loss(self):

    import torch

    def loss(output, labels):

      output, labels = _make_pytorch_shapes_consistent(output, labels)

      return torch.mean(output - labels * torch.log(output))

    return loss

class BinaryCrossEntropy(Loss):

  """The cross entropy between pairs of probabilities.

    expected = [np.mean([0.9, 1.8]), np.mean([1.4, 0.4])]

    assert np.allclose(expected, result)

  @unittest.skipIf(not has_tensorflow, 'TensorFlow is not installed')

  def test_poisson_loss_tf(self):

    """Test PoissonLoss."""

    loss = losses.PoissonLoss()

    outputs = tf.constant([[0.1, 0.8], [0.4, 0.6]])

    labels = tf.constant([[0.0, 1.0], [1.0, 0.0]])

    result = loss._compute_tf_loss(outputs, labels).numpy()

    expected = 0.75986

    assert np.allclose(expected, result)

  @unittest.skipIf(not has_pytorch, 'PyTorch is not installed')

  def test_poisson_loss_pytorch(self):

    """Test PoissonLoss."""

    loss = losses.PoissonLoss()

    outputs = torch.tensor([[0.1, 0.8], [0.4, 0.6]])

    labels = torch.tensor([[0.0, 1.0], [1.0, 0.0]])

    result = loss._create_pytorch_loss()(outputs, labels).numpy()

    expected = 0.75986

    assert np.allclose(expected, result)

  @unittest.skipIf(not has_tensorflow, 'TensorFlow is not installed')

  def test_binary_cross_entropy_tf(self):

    """Test BinaryCrossEntropy."""

.. autoclass:: deepchem.models.losses.HingeLoss

  :members:

.. autoclass:: deepchem.models.losses.PoissonLoss

  :members:

.. autoclass:: deepchem.models.losses.BinaryCrossEntropy

  :members: