CODEWITHSUNDEEP
tensorflow
Saeed
Saeed

Reputation: 357

How to initialize the LSTM cell in TensorFlow?

I am trying to run the following code in TF v1.0 and it throws an error. I have created a lstm, and then defined the state variable to pass it to lstm_cell in order to calculate the outputs, but state cannot be initialized:

lstm_cell = tf.contrib.rnn.BasicLSTMCell(10)
# Initial state of the LSTM memory.
state = tf.zeros([20, lstm_cell.state_size])
outputs, states = lstm_cell(x , state)

Here it the traceback:

ValueError                                Traceback (most recent call last)
<ipython-input-82-4a23eee1acf4> in <module>()
      1 lstm_cell = tf.contrib.rnn.BasicLSTMCell(10)
      2 # Initial state of the LSTM memory.
----> 3 state = tf.zeros([20, lstm_cell.state_size])
      4 outputs, states = lstm_cell(x , state)

/Users/Saeed/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.pyc in zeros(shape, dtype, name)
   1370       output = constant(zero, shape=shape, dtype=dtype, name=name)
   1371     except (TypeError, ValueError):
-> 1372       shape = ops.convert_to_tensor(shape, dtype=dtypes.int32, name="shape")
   1373       output = fill(shape, constant(zero, dtype=dtype), name=name)
   1374   assert output.dtype.base_dtype == dtype

/Users/Saeed/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc in convert_to_tensor(value, dtype, name, preferred_dtype)
    649       name=name,
    650       preferred_dtype=preferred_dtype,
--> 651       as_ref=False)
    652 
    653 

/Users/Saeed/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype)
    714 
    715         if ret is None:
--> 716           ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
    717 
    718         if ret is NotImplemented:

/Users/Saeed/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.pyc in _constant_tensor_conversion_function(v, dtype, name, as_ref)
    174                                          as_ref=False):
    175   _ = as_ref
--> 176   return constant(v, dtype=dtype, name=name)
    177 
    178 

/Users/Saeed/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.pyc in constant(value, dtype, shape, name, verify_shape)
    163   tensor_value = attr_value_pb2.AttrValue()
    164   tensor_value.tensor.CopyFrom(
--> 165       tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
    166   dtype_value = attr_value_pb2.AttrValue(type=tensor_value.tensor.dtype)
    167   const_tensor = g.create_op(

/Users/Saeed/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.pyc in make_tensor_proto(values, dtype, shape, verify_shape)
    366     else:
    367       _AssertCompatible(values, dtype)
--> 368       nparray = np.array(values, dtype=np_dt)
    369       # check to them.
    370       # We need to pass in quantized values as tuples, so don't apply the shape

ValueError: setting an array element with a sequence.

Upvotes: 2

Views: 2596

Answers (1)

bertslike
bertslike

Reputation: 101

This is because in the latest versions of Tensorflow, the return of state_size property of a default BasicLSTMCell is a LSTMStateTuple (a Python Tuple).

If you check the source code, you could see that the same number of units is returned in both elements of the tuple (it was concatenated along the same axis in previous versions) and should be considered when initalizing the cell states.

Therefore, this should do the trick:

state = tf.zeros([20, lstm_cell.state_size[0]*2)

Upvotes: 1

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