Removing sequential tests

import tensorflow as tf

import numpy as np

import deepchem as dc

class TestSequential(unittest.TestCase):

  """

  Test API for sequential models 

  """

  def test_model_construct(self):

    """Test that models can be constructed with Sequential."""

    model = dc.models.Sequential()

    model.add_features(dc.nn.Input(shape=(32,)))

    model.add_labels(dc.nn.Input(shape=(1,)))

    model.add(dc.nn.Dense(32, 32))

    model.add(dc.nn.Dense(32, 32))

  def test_model_fit(self):

    """Test that models can be fit"""

    model = dc.models.Sequential()

    model.add_features(dc.nn.Input(shape=(32,)))

    model.add_labels(dc.nn.Input(shape=(1,)))

    model.add(dc.nn.Dense(32, 32))

    model.add(dc.nn.Dense(1, 32))

    model.add_loss(dc.nn.mean_squared_error)

    X = np.zeros((10, 32))

    y = np.zeros((10,))

    dataset = dc.data.NumpyDataset(X, y)

    model.fit(dataset)