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