rvinas

# StackOverflow question: https://stackoverflow.com/questions/51123481/how-to-build-a-language-model-using-lstm-that-assigns-probability-of-occurence-f
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Embedding, LSTM, Dense
from keras.models import Sequential
import keras
import numpy as np


def prepare_sentence(seq, maxlen):

rvinas

# StackOverflow question: https://stackoverflow.com/questions/53105294/implementing-a-batch-dependent-loss-in-keras
from keras.utils import Sequence
from keras.models import Model
from keras.layers import Input, Dense
import keras.backend as K
import numpy as np

# Constants
input_dim = 64  # digits.data.shape[1]
dataset = np.random.rand(1000, input_dim)  # TODO: replace with digits.data

rvinas

# StackOverflow question: https://stackoverflow.com/questions/51123481/how-to-build-a-language-model-using-lstm-that-assigns-probability-of-occurence-f
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Embedding, LSTM, Dense
from keras.models import Sequential
import numpy as np


def prepare_sentence(seq, maxlen):
    # Pads seq and slides windows