3
數。當我讀到TensorFlow的rnn_cell.py
其中LSTMCell
實施後,我看到了下面爲什麼一個LSTMCell輸入的尺寸必須爲單位
def __call__(self, inputs, state, scope=None):
"""Run one step of LSTM.
Args:
inputs: input Tensor, 2D, batch x num_units.
state: if `state_is_tuple` is False, this must be a state Tensor,
`2-D, batch x state_size`. If `state_is_tuple` is True, this must be a
tuple of state Tensors, both `2-D`, with column sizes `c_state` and
`m_state`.
scope: VariableScope for the created subgraph; defaults to "LSTMCell".
Returns:
A tuple containing:
- A `2-D, [batch x output_dim]`, Tensor representing the output of the
LSTM after reading `inputs` when previous state was `state`.
Here output_dim is:
num_proj if num_proj was set,
num_units otherwise.
- Tensor(s) representing the new state of LSTM after reading `inputs` when
the previous state was `state`. Same type and shape(s) as `state`.
Raises:
ValueError: If input size cannot be inferred from inputs via
static shape inference.
"""
num_proj = self._num_units if self._num_proj is None else self._num_proj
if self._state_is_tuple:
(c_prev, m_prev) = state
else:
我想知道爲什麼inputs
尺寸必須匹配一致LSTM的單位數量(num_units
)。我期望他們完全不相關,但不知何故他們不是。
有誰知道爲什麼?