fix bugs and yapf

import tensorflow as tf

from deepchem.utils.save import log

<<<<<<< HEAD

from deepchem.models.tensorgraph.tensor_graph import TensorGraph

from deepchem.models.tensorgraph.layers import Layer, SigmoidCrossEntropy, \

    Sigmoid, Feature, Label, Weights, Concat, WeightedError

from deepchem.models.tensorgraph.graph_layers import WeaveLayer, WeaveGather, DTNNEmbedding, DTNNGather, DTNNStep, \

  DTNNExtract, DAGLayer, DAGGather, MessagePassing, SetGather

from deepchem.models.tensorgraph.layers import Feature, Conv1D, Dense, Flatten, Reshape, Squeeze, Transpose, \

  CombineMeanStd, Repeat, Gather, GRU, LSTM, L2Loss, Concat, SoftMax, Sigmoid, SigmoidCrossEntropy\

  CombineMeanStd, Repeat, Gather, GRU, LSTM, L2Loss, Concat, SoftMax, Sigmoid, SigmoidCrossEntropy, \

  Constant, Variable, StopGradient, Add, Multiply, Log, Exp, InteratomicL2Distances, \

  SoftMaxCrossEntropy, ReduceMean, ToFloat, ReduceSquareDifference, Conv2D, MaxPool2D, ReduceSum, GraphConv, GraphPool, \

  GraphGather, BatchNorm, WeightedError, \

  tg.build()

  tg.save()

def test_Sigmoid_pickle():

  tg = TensorGraph()

  feature = Feature(shape=(tg.batch_size, 1))

  tg.build()

  tg.save()

def test_Concat_pickle():

  tg = TensorGraph()

  feature = Feature(shape=(tg.batch_size, 1))

  tg.build()

  tg.save()

def test_SigmoidCrossEntropy_pickle():

  tg = TensorGraph()

  feature = Feature(shape=(tg.batch_size, 1))

  tg.set_loss(out)

  tg.build()

  tg.save()

    scores = model.evaluate(dataset_trans, [classification_metric])

    assert scores[classification_metric.name] > .9

  def test_sklearn_multitask_regression_overfit(self):

    """Test SKLearn singletask-to-multitask overfits tiny regression data."""

    n_tasks = 2