def __call__(self, inputs, state, k_size=3, scope=None):
"""Convolutional Long short-term memory cell (ConvLSTM)."""
with vs.variable_scope(scope or type(self).__name__): # "ConvLSTMCell"
if self._state_is_tuple:
c, h = state
else:
c, h = array_ops.split(3, 2, state)
# batch_size * height * width * channel
concat = _conv([inputs, h], 4 * self._num_units, k_size, True)
# i = input_gate, j = new_input, f = forget_gate, o = output_gate
i, j, f, o = array_ops.split(3, 4, concat)
new_c = (c * sigmoid(f + self._forget_bias) + sigmoid(i) *
self._activation(j))
new_h = self._activation(new_c) * sigmoid(o)
if self._state_is_tuple:
new_state = LSTMStateTuple(new_c, new_h)
else:
new_state = array_ops.concat(3, [new_c, new_h])
return new_h, new_state
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