提交 9573256f 编写于 作者: Y yangyaming

Remove main_program and startup_program.

上级 2a058b10
......@@ -764,7 +764,7 @@ def conv2d_transpose(input,
return out
def sequence_expand(x, y, main_program=None, startup_program=None):
def sequence_expand(x, y):
"""Sequence Expand Layer. This layer will expand the input variable **x**
according to LoD information of **y**. And the following examples will
explain how sequence_expand works:
......@@ -808,8 +808,6 @@ def sequence_expand(x, y, main_program=None, startup_program=None):
Args:
x (Variable): The input variable which is a Tensor or LoDTensor.
y (Variable): The input variable which is a LoDTensor.
main_program (Program): The main program.
startup_program (Program): The startup program.
Returns:
Variable: The expanded variable which is a LoDTensor.
......@@ -836,9 +834,7 @@ def lstm_unit(x_t,
cell_t_prev,
forget_bias=0.0,
param_attr=None,
bias_attr=None,
main_program=None,
startup_program=None):
bias_attr=None):
"""Lstm unit layer. The equation of a lstm step is:
.. math::
......@@ -881,8 +877,6 @@ def lstm_unit(x_t,
initializer, name etc.
bias_attr (ParamAttr): The attributes of bias weights, if not False,
bias weights will be created and be set to default value.
main_program (Program): The main program.
startup_program (Program): the startup program.
Returns:
tuple: The hidden value and cell value of lstm unit.
......@@ -923,18 +917,11 @@ def lstm_unit(x_t,
bias_attr = ParamAttr()
size = cell_t_prev.shape[1]
concat_out = concat(
input=[x_t, hidden_t_prev],
axis=1,
main_program=main_program,
startup_program=startup_program)
concat_out = concat(input=[x_t, hidden_t_prev], axis=1)
fc_out = fc(input=concat_out,
size=4 * size,
param_attr=param_attr,
bias_attr=bias_attr,
act='linear',
main_program=main_program,
startup_program=startup_program)
bias_attr=bias_attr)
dtype = x_t.dtype
c = helper.create_tmp_variable(dtype)
h = helper.create_tmp_variable(dtype)
......
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