"add sequence conv layer"#5117
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dzhwinter merged 10 commits intoPaddlePaddle:developfrom Oct 30, 2017
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reyoung
reviewed
Oct 26, 2017
python/paddle/v2/framework/layers.py
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| return pool_out | ||
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| def sequence_conv_pool(input, |
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_create_op_func_('sequence_conv_pool')
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Here we need to check validation of input arguments and need to create filter parameter based on two arguments.
JiayiFeng
reviewed
Oct 30, 2017
python/paddle/v2/framework/layers.py
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| attr=helper.param_attr, shape=filter_shape, dtype=dtype) | ||
| pre_bias = helper.create_tmp_variable(dtype) | ||
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| input.set_lod(lod) |
python/paddle/v2/framework/layers.py
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| helper.append_op( | ||
| type='sequence_conv', | ||
| inputs={ | ||
| 'X': input, |
python/paddle/v2/framework/layers.py
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| return square_out | ||
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| def conv1d(input, |
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Maybe sequence_conv is a better name?
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Rename conv1d to sequence_conv after discuss with @Canpio offline, since this function's behavior is different with conv2d, conv3d, fixed.
python/paddle/v2/framework/layers.py
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| # FIXME(dzh) : want to unify the argument of python layer | ||
| # function. So we ignore some unecessary attributes | ||
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| ENUM_POOL_TYPE = ["max", "avg", "sqrt", "last", "first"] |
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Initialize ENUM_POOL_TYPE as a set to make the following if pool_type not in ENUM_POOL_TYPE: faster.
python/paddle/v2/framework/layers.py
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| helper.append_op( | ||
| type="sequence_pool", | ||
| inputs={"X": input}, |
python/paddle/v2/framework/layers.py
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| type="sequence_pool", | ||
| inputs={"X": input}, | ||
| outputs={"Out": pool_out}, | ||
| attrs={"strategy": pool_type, }) |
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Add sequence conv layer. This PR depends on #4814.