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Document LSTMCell carry as the (c, h) tuple it actually is #5469

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Document LSTMCell carry as the (c, h) tuple it actually is #5469

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8 changes: 5 additions & 3 deletions flax/linen/recurrent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -136,7 +136,8 @@ def __call__(self, carry, inputs):
r"""A long short-term memory (LSTM) cell.

Args:
carry: the hidden state of the LSTM cell,
carry: a tuple ``(c, h)`` of the cell state ``c`` and the hidden
state ``h``, both of shape ``(*batch, features)``. Typically
initialized using ``LSTMCell.initialize_carry``.
inputs: an ndarray with the input for the current time step.
All dimensions except the final are considered batch dimensions.
Expand Down Expand Up @@ -285,8 +286,9 @@ def __call__(
r"""An optimized long short-term memory (LSTM) cell.

Args:
carry: the hidden state of the LSTM cell, initialized using
``LSTMCell.initialize_carry``.
carry: a tuple ``(c, h)`` of the cell state ``c`` and the hidden
state ``h``, both of shape ``(*batch, features)``. Typically
initialized using ``OptimizedLSTMCell.initialize_carry``.
inputs: an ndarray with the input for the current time step. All
dimensions except the final are considered batch dimensions.

Expand Down
8 changes: 5 additions & 3 deletions flax/nnx/nn/recurrent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -201,7 +201,8 @@ def __call__(
r"""A long short-term memory (LSTM) cell.

Args:
carry: the hidden state of the LSTM cell,
carry: a tuple ``(c, h)`` of the cell state ``c`` and the hidden
state ``h``, both of shape ``(*batch, features)``. Typically
initialized using ``LSTMCell.initialize_carry``.
inputs: an ndarray with the input for the current time step.
All dimensions except the final are considered batch dimensions.
Expand Down Expand Up @@ -382,8 +383,9 @@ def __call__(
r"""An optimized long short-term memory (LSTM) cell.

Args:
carry: the hidden state of the LSTM cell, initialized using
``LSTMCell.initialize_carry``.
carry: a tuple ``(c, h)`` of the cell state ``c`` and the hidden
state ``h``, both of shape ``(*batch, features)``. Typically
initialized using ``OptimizedLSTMCell.initialize_carry``.
inputs: an ndarray with the input for the current time step.
All dimensions except the final are considered batch dimensions.

Expand Down