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@ -56,9 +56,28 @@ def concat(input, axis=0):
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def sums(input, out=None):
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"""
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This function takes in the input and performs the sum operation on it
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and returns that as the output.
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"""This function performs the sum operation on the input and returns the
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result as the output.
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Args:
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input (Variable|list): The input tensor that has the elements
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that need to be summed up.
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Returns:
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Variable: The tensor type variable that has the sum of input
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written to it.
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Examples:
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.. code-block::python
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tmp = fluid.layers.zeros(shape=[10], dtype='int32')
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i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
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a0 = layers.array_read(array=tmp, i=i)
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i = layers.increment(x=i)
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a1 = layers.array_read(array=tmp, i=i)
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mean_a0 = layers.mean(x=a0)
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mean_a1 = layers.mean(x=a1)
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a_sum = layers.sums(input=[mean_a0, mean_a1])
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"""
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helper = LayerHelper('sum', **locals())
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if out is None:
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@ -99,9 +118,9 @@ def fill_constant(shape, dtype, value, out=None):
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"""
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**fill_constant**
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This function creates a tensor of specified *shape* and
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This function creates a tensor of specified *shape* and
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*dtype*, and initializes this with a constant supplied in *value*.
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It also sets *stop_gradient* to True.
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Args:
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@ -141,9 +160,9 @@ def fill_constant_batch_size_like(input,
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"""
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**fill_constant_batch_size_like**
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This function creates a tensor of specified *shape*, *dtype* and batch size,
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and initializes this with a constant supplied in *value*. The batch size is
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obtained from the `input` tensor.
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This function creates a tensor of specified *shape*, *dtype* and batch size,
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and initializes this with a constant supplied in *value*. The batch size is
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obtained from the `input` tensor.
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It also sets *stop_gradient* to True.
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