fused_seqpool_cvm¶
- paddle.fluid.contrib.layers.nn. fused_seqpool_cvm ( input, pool_type, cvm, pad_value=0.0, use_cvm=True, cvm_offset=2 ) [source]
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- Api_attr
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Static Graph
This OP is the fusion of sequence_pool and continuous_value_model op.
Note: The Op only receives List of LoDTensor as input, only support SUM pooling now.
- Parameters
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input (Variable|list of Variable) – Input is List of LoDTensor.
pool_type (str) – pooling type, only support SUM pooling now.
cvm (Variable) – cvm Variable.
pad_value (float, optional) – padding value of sequence pool. Default: 0.0.
use_cvm (bool, optional) – use cvm or not. Default: True.
cvm_offset (int, optional) – cvm offset. Default: 2, which means cvm contains show, click.
- Returns
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The tensor variable storing sequence pool and cvm of input.
- Return type
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Variable|list of Variable
Examples
import paddle import paddle.fluid as fluid paddle.enable_static() data = paddle.static.data(name='x', shape=[-1, 1], dtype='int64', lod_level=1) data2 = paddle.static.data(name='y', shape=[-1, 1], dtype='int64', lod_level=1) inputs = [data, data2] embs = fluid.layers.nn._pull_box_sparse(input=inputs, size=11, is_distributed=True, is_sparse=True) label = paddle.static.data(name="label", shape=[-1, 1], dtype="int64", lod_level=1) ones = fluid.layers.fill_constant_batch_size_like(input=label, shape=[-1, 1], dtype="int64", value=1) show_clk = paddle.cast(paddle.concat([ones, label], axis=1), dtype='float32') show_clk.stop_gradient = True cvms = fluid.contrib.layers.fused_seqpool_cvm(embs, 'sum', show_clk)