未验证 提交 71dd8f8f 编写于 作者: G Guo Sheng 提交者: GitHub

Merge pull request #6716 from guoshengCS/add-python-reduceSum

Add python wrapper for reduce_sum
......@@ -312,3 +312,9 @@ sequence_softmax
.. autofunction:: paddle.v2.fluid.layers.sequence_softmax
:noindex:
reduce_sum
---------
.. autofunction:: paddle.v2.fluid.layers.reduce_sum
:noindex:
......@@ -13,7 +13,7 @@ __all__ = [
'crf_decoding', 'cos_sim', 'cross_entropy', 'square_error_cost', 'accuracy',
'chunk_eval', 'sequence_conv', 'conv2d', 'sequence_pool', 'pool2d',
'batch_norm', 'beam_search_decode', 'conv2d_transpose', 'sequence_expand',
'lstm_unit'
'lstm_unit', 'reduce_sum'
]
......@@ -402,8 +402,8 @@ def chunk_eval(input,
},
attrs={
"num_chunk_types": num_chunk_types,
'chunk_scheme': chunk_scheme,
'excluded_chunk_types': excluded_chunk_types or []
"chunk_scheme": chunk_scheme,
"excluded_chunk_types": excluded_chunk_types or []
})
return precision, recall, f1_score, num_infer_chunks, num_label_chunks, num_correct_chunks
......@@ -935,3 +935,47 @@ def lstm_unit(x_t,
attrs={"forget_bias": forget_bias})
return h, c
def reduce_sum(input, dim=None, keep_dim=False):
"""
Computes the sum of tensor elements over the given dimension.
Args:
input (Variable): The input variable which is a Tensor or LoDTensor.
dim (int|None): The dimension along which the sum is performed. If
:attr:`None`, sum all elements of :attr:`input` and return a
Tensor variable with a single element, otherwise must be in the
range :math:`[-rank(input), rank(input))`. If :math:`dim < 0`,
the dimension to reduce is :math:`rank + dim`.
keep_dim (bool): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the :attr:`input` unless :attr:`keep_dim` is true.
Returns:
Variable: The reduced Tensor variable.
Examples:
.. code-block:: python
# x is a Tensor variable with following elements:
# [[0.2, 0.3, 0.5, 0.9]
# [0.1, 0.2, 0.6, 0.7]]
# Each example is followed by the correspending output tensor.
fluid.layers.reduce_sum(x) # [3.5]
fluid.layers.reduce_sum(x, dim=0) # [0.3, 0.5, 1.1, 1.6]
fluid.layers.reduce_sum(x, dim=-1) # [1.9, 1.6]
fluid.layers.reduce_sum(x, dim=1, keep_dim=True) # [[1.9], [1.6]]
"""
helper = LayerHelper('reduce_sum', **locals())
out = helper.create_tmp_variable(dtype=helper.input_dtype())
helper.append_op(
type='reduce_sum',
inputs={'X': input},
outputs={'Out': out},
attrs={
'dim': dim if dim != None else 0,
'keep_dim': keep_dim,
'reduce_all': True if dim == None else False
})
return out
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