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@ -62,6 +62,8 @@ def split_lod_tensor(input, mask, level=0):
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The output is the true branch and the false branch with the mask applied to
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the input at a certain level in the tensor.
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Mainly used in IfElse to split data into two parts. Related API: IfElse.
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Args:
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input(tuple|list|None): The input tensor that contains complete
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lod information needed to construct the output.
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@ -83,6 +85,7 @@ def split_lod_tensor(input, mask, level=0):
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out_true, out_false = layers.split_lod_tensor(
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input=x, mask=y, level=level)
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"""
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helper = LayerHelper('split_lod_tensor', **locals())
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out_true = helper.create_tmp_variable(dtype=input.dtype)
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@ -887,14 +890,18 @@ def array_write(x, i, array=None):
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def create_array(dtype):
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"""This function creates an array of type :math:`LOD_TENSOR_ARRAY` using the
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LayerHelper.
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"""
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**Create LoDTensor Array**
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This function creates an array of type :math:`LOD_TENSOR_ARRAY` using the
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LayerHelper. It is mainly used to implement RNN with array_write, array_read
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and While.
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Args:
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dtype (int|float): The data type of the elements in the array.
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Returns:
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Variable: The tensor variable storing the elements of data type.
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Variable: The lod_tensor_array variable storing the elements of data type.
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Examples:
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.. code-block:: python
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@ -1020,9 +1027,14 @@ def shrink_memory(x, i, table):
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def array_length(array):
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"""This function performs the operation to find the length of the input
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"""
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**Get the length of Input LoDTensorArray**
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This function performs the operation to find the length of the input
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LOD_TENSOR_ARRAY.
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Related API: array_read, array_write, While.
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Args:
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array (LOD_TENSOR_ARRAY): The input array that will be used
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to compute the length.
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