Created by: Aurelius84

• Add pyramid hash embedding op

Example code:

import numpy as np
import paddle.fluid as fluid
num_voc = 128
embed_dim = 64
x_shape, x_lod = [16, 10], [[3, 5, 2, 6]]
x = fluid.data(name='x', shape=x_shape, dtype='int32', lod_level=1)
hash_embd = fluid.contrib.search_pyramid_hash(
    input=x,
    num_emb=embed_dim,
    space_len=num_voc * embed_dim,
    pyramid_layer=4,
    rand_len=16,
    drop_out_percent=0.5,
    is_training=True,
    use_filter=False,
    white_list_len=6400,
    black_list_len=2800,
    seed=3,
    lr=0.002,
    param_attr=fluid.ParamAttr(
        name="PyramidHash_emb_0",
        learning_rate=0, ),
    param_attr_wl=fluid.ParamAttr(
        name="Filter",
        learning_rate=0, ),
    param_attr_bl=None,
    name=None, )

place = fluid.CPUPlace()
x_tensor = fluid.create_lod_tensor(
    np.random.randint(0, num_voc, x_shape).astype('int32'), x_lod,
    place)

exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
ret = exe.run(feed={'x': x_tensor},
              fetch_list=[hash_embd],
              return_numpy=False)