@@ -351,7 +351,6 @@ def dynamic_lstm(input,
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c_0(Variable): The initial cell state is an optional input, default is zero.
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This is a tensor with shape (N x D), where N is the
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batch size. `h_0` and `c_0` can be NULL but only at the same time.
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-
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param_attr(ParamAttr|None): The parameter attribute for the learnable
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hidden-hidden weights.
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@@ -3131,10 +3130,18 @@ def lstm_unit(x_t,
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cell_t_prev (Variable): The cell value of lstm unit, a 2-D tensor with
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shape M x S, M for batch size and S for size of lstm unit.
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forget_bias (float): The forget bias of lstm unit.
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- param_attr (ParamAttr): The attributes of parameter weights, used to set
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- initializer, name etc.
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- bias_attr (ParamAttr): The attributes of bias weights, if not False,
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- bias weights will be created and be set to default value.
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+ param_attr(ParamAttr|None): The parameter attribute for the learnable
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+ hidden-hidden weights.
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+ If it is set to None or one attribute of ParamAttr,
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+ lstm_unit will create ParamAttr as param_attr.
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+ If the Initializer of the param_attr is not set, the
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+ parameter is initialized with Xavier. Default: None.
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+ bias_attr (ParamAttr|None): The bias attribute for the learnable bias
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+ weights. If it is set to False, no bias will be added
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+ to the output units. If it is set to None or one attribute of ParamAttr,
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+ lstm_unit will create ParamAttr as bias_attr.
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+ If the Initializer of the bias_attr is not set,
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+ the bias is initialized zero. Default: None.
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name(str|None): A name for this layer(optional). If set None, the layer
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will be named automatically.
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