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improve sequence_conv api doc (#19316)

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* improve sequence_conv api doc test=develop

* add warning for padding param test=develop

modify into deprecated
assert
Aurelius84 6 years ago committed by GitHub
parent 0d7949831b
commit a9cd513680
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3 changed files with 80 additions and 12 deletions
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2
paddle/fluid/API.spec
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@ -122,7 +122,7 @@ paddle.fluid.layers.cross_entropy (ArgSpec(args=['input', 'label', 'soft_label',
paddle.fluid.layers.bpr_loss (ArgSpec(args=['input', 'label', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6263dfdeb6c670fa0922c9cbc8fb1bf4'))
paddle.fluid.layers.square_error_cost (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'bbb9e708bab250359864fefbdf48e9d9'))
paddle.fluid.layers.chunk_eval (ArgSpec(args=['input', 'label', 'chunk_scheme', 'num_chunk_types', 'excluded_chunk_types', 'seq_length'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'b02844e0ad4bd713c5fe6802aa13219c'))
paddle.fluid.layers.sequence_conv (ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'bias_attr', 'param_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(3, 1, None, None, None, None, None)), ('document', '3d8e8f3e0e1cf520156be37605e83ccd'))
paddle.fluid.layers.sequence_conv (ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'padding_start', 'bias_attr', 'param_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(3, 1, True, None, None, None, None, None)), ('document', '2bf23e7884c380c3b27f2709aa322cb9'))
paddle.fluid.layers.conv2d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', '35f5343338e38803c70ed0479965d0b4'))
paddle.fluid.layers.conv3d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', '367293b5bada54136a91621078d38334'))
paddle.fluid.layers.sequence_pool (ArgSpec(args=['input', 'pool_type', 'is_test', 'pad_value'], varargs=None, keywords=None, defaults=(False, 0.0)), ('document', 'e90a93251c52dc4e6fb34fb3991b3f82'))

74
python/paddle/fluid/layers/nn.py
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@ -1919,22 +1919,70 @@ def sequence_conv(input,
num_filters,
filter_size=3,
filter_stride=1,
padding=None,
padding=True,
padding_start=None,
bias_attr=None,
param_attr=None,
act=None,
name=None):
"""
This function creates the op for sequence_conv, using the inputs and
other convolutional configurations for the filters and stride as given
in the input parameters to the function.
The sequence_conv receives input sequences with variable length and other convolutional
configuration parameters for the filter and stride to apply the convolution operation.
It fills all-zero padding data on both sides of the sequence by default to ensure that
the output is the same length as the input. You can customize the padding behavior by
configuring the parameter :attr:`padding\_start`.
**Warning:** the parameter :attr:`padding` take no effect and will be deprecated in the future.
.. code-block:: text
Here we'll illustrate the details of the padding operation:
For a mini-batch of 2 variable lengths sentences, containing 3, and 1 time-steps:
Assumed input (X) is a [4, M, N] float LoDTensor, and X->lod()[0] = [0, 3, 4].
Besides, for the sake of simplicity, we assume M=1 and N=2.
X = [[a1, a2;
b1, b2;
c1, c2]
[d1, d2]]
This is to say that input (X) has 4 words and the dimension of each word
representation is 2.
* Case1:
If padding_start is -1 and filter_size is 3.
The length of padding data is calculated as follows:
up_pad_len = max(0, -padding_start) = 1
down_pad_len = max(0, filter_size + padding_start - 1) = 1
The output of the input sequence after padding is:
data_aftet_padding = [[0, 0, a1, a2, b1, b2;
a1, a2, b1, b2, c1, c2;
b1, b2, c1, c2, 0, 0 ]
[0, 0, d1, d2, 0, 0 ]]
It will be multiplied by the filter weight to get the final output.
Args:
input (Variable): ${x_comment}
num_filters (int): number of filters.
filter_size (int): the filter size (H and W).
filter_stride (int): stride of the filter.
padding (bool): if True, add paddings.
num_filters (int): the number of filters.
filter_size (int): the height of filter, the width is hidden size by default.
filter_stride (int): stride of the filter. Currently only supports :attr:`stride` = 1.
padding (bool): the parameter :attr:`padding` take no effect and will be discarded in the
future. Currently, it will always pad input to make sure the length of the output is
the same as input whether :attr:`padding` is set true or false. Because the length of
input sequence may be shorter than :attr:`filter\_size`, which will cause the convolution
result to not be computed correctly. These padding data will not be trainable or updated
while trainnig.
padding_start (int|None): It is used to indicate the start index for padding the input
sequence, which can be negative. The negative number means to pad
:attr:`|padding_start|` time-steps of all-zero data at the beginning of each instance.
The positive number means to skip :attr:`padding_start` time-steps of each instance,
and it will pad :math:`filter\_size + padding\_start - 1` time-steps of all-zero data
at the end of the sequence to ensure that the output is the same length as the input.
If set None, the same length :math:`\\frac{filter\_size}{2}` of data will be filled
on both sides of the sequence. If set 0, the length of :math:`filter\_size - 1` data
is padded at the end of each input sequence.
bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of sequence_conv.
If it is set to False, no bias will be added to the output units.
If it is set to None or one attribute of ParamAttr, sequence_conv
@ -1953,11 +2001,13 @@ def sequence_conv(input,
Variable: output of sequence_conv
Examples:
.. code-block:: python
import paddle.fluid as fluid
x = fluid.layers.data(name='x', shape=[10,10], append_batch_size=False, dtype='float32')
x_conved = fluid.layers.sequence_conv(x,2)
x_conved = fluid.layers.sequence_conv(input=x, num_filters=2, filter_size=3, padding_start=-1)
"""
assert not in_dygraph_mode(), (
@ -1968,6 +2018,8 @@ def sequence_conv(input,
filter_param = helper.create_parameter(
attr=helper.param_attr, shape=filter_shape, dtype=dtype)
pre_bias = helper.create_variable_for_type_inference(dtype)
if padding_start is None:
padding_start = -int(filter_size // 2)
helper.append_op(
type='sequence_conv',
@ -1978,8 +2030,8 @@ def sequence_conv(input,
outputs={"Out": pre_bias},
attrs={
'contextStride': filter_stride,
'contextStart': -int(filter_size // 2),
'contextLength': filter_size
'contextStart': padding_start,
'contextLength': filter_size,
})
pre_act = helper.append_bias_op(pre_bias)
return helper.append_activation(pre_act)

16
python/paddle/fluid/tests/unittests/test_seq_conv.py
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@ -241,5 +241,21 @@ class TestSeqProjectCase3(TestSeqProject):
self.output_represention = 8 # output feature size
class TestSeqConvApi(unittest.TestCase):
def test_api(self):
import paddle.fluid as fluid
x = fluid.layers.data('x', shape=[32], lod_level=1)
y = fluid.layers.sequence_conv(
input=x, num_filters=2, filter_size=3, padding_start=None)
place = fluid.CPUPlace()
x_tensor = fluid.create_lod_tensor(
np.random.rand(10, 32).astype("float32"), [[2, 3, 1, 4]], place)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
ret = exe.run(feed={'x': x_tensor}, fetch_list=[y], return_numpy=False)
if __name__ == '__main__':
unittest.main()

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