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@ -1985,8 +1985,7 @@ def row_conv(input, future_context_size, param_attr=None, act=None):
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In the above equation:
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* :math:`Out_{i}`: The i-th row of output variable with shape [1, D].
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* :math:`\\tau`: Future context size. Please note, the shape of
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convolution kernel is [future_context_size + 1, D].
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* :math:`\\tau`: Future context size.
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* :math:`X_{j}`: The j-th row of input variable with shape [1, D].
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* :math:`W_{i-j}`: The (i-j)-th row of parameters with shape [1, D].
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@ -1997,7 +1996,8 @@ def row_conv(input, future_context_size, param_attr=None, act=None):
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Args:
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input (Variable): Input variable, a 2D LoDTensor with shape [T, D].
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future_context_size (int): Future context size.
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future_context_size (int): Future context size. Please note, the shape
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of convolution kernel is [future_context_size + 1, D].
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param_attr (ParamAttr): Attributes of parameters, including
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name, initializer etc.
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act (str): Non-linear activation to be applied to output variable.
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