def main():
import problem_unittests as tests
tests.test_get_init_cell(get_init_cell)
tests.test_get_embed(get_embed)
tests.test_build_rnn(build_rnn)
tests.test_build_nn(build_nn)
tests.test_get_batches(get_batches)
tests.test_get_tensors(get_tensors)
tests.test_pick_word(pick_word)
print(get_batches([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20],
batch_size=3,
seq_length=2))
def run_test():
import problem_unittests as t
t.test_create_lookup_tables(create_lookup_tables)
t.test_get_batches(get_batches)
t.test_tokenize(token_lookup)
t.test_get_inputs(get_inputs)
t.test_get_init_cell(get_init_cell)
t.test_get_embed(get_embed)
t.test_build_rnn(build_rnn)
t.test_build_nn(build_nn)
t.test_get_tensors(get_tensors)
t.test_pick_word(pick_word)
Create embedding for <input_data>.
:param input_data: TF placeholder for text input.
:param vocab_size: Number of words in vocabulary.
:param embed_dim: Number of embedding dimensions
:return: Embedded input.
"""
# TODO: Implement Function
embeddings = tf.Variable(tf.random_uniform((vocab_size, embed_dim), -1, 1))
embed = tf.nn.embedding_lookup(embeddings, input_data)
return embed
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_get_embed(get_embed)
# ### Build RNN
# You created a RNN Cell in the `get_init_cell()` function. Time to use the cell to create a RNN.
# - Build the RNN using the [`tf.nn.dynamic_rnn()`](https://www.tensorflow.org/api_docs/python/tf/nn/dynamic_rnn)
# - Apply the name "final_state" to the final state using [`tf.identity()`](https://www.tensorflow.org/api_docs/python/tf/identity)
#
# Return the outputs and final_state state in the following tuple `(Outputs, FinalState)`
# In[50]:
def build_rnn(cell, inputs):
"""
Create a RNN using a RNN Cell
:param cell: RNN Cell
