ymnliu

def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

ymnliu

# Keras==1.0.6
from keras.models import Sequential
import numpy as np
from keras.layers.recurrent import LSTM
from keras.layers.core import TimeDistributedDense, Activation
from keras.preprocessing.sequence import pad_sequences
from keras.layers.embeddings import Embedding
from sklearn.cross_validation import train_test_split
from keras.layers import Merge
from keras.backend import tf

ymnliu

class Lambda(Layer):
    '''Used for evaluating an arbitrary Theano / TensorFlow expression
    on the output of the previous layer.

    # Examples

    ```python
        # add a x -> x^2 layer
        model.add(Lambda(lambda x: x ** 2))
    ```

ymnliu

# Keras==2.0.2
import numpy as np
from keras.models import Sequential
from keras.layers.recurrent import LSTM
from keras.layers.core import Activation, Dense
from keras.layers.wrappers import TimeDistributed
from keras.preprocessing.sequence import pad_sequences
from keras.layers.embeddings import Embedding
from sklearn.cross_validation import train_test_split
from sklearn.metrics import confusion_matrix, accuracy_score, precision_recall_fscore_support