# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function import paddle paddle.enable_static() import unittest import paddle.fluid as fluid from paddle.fluid.framework import default_main_program from paddle.fluid.entry_attr import ProbabilityEntry, CountFilterEntry class EntryAttrChecks(unittest.TestCase): def embedding_layer(self): prog = fluid.Program() scope = fluid.core.Scope() with fluid.scope_guard(scope): with fluid.program_guard(prog): input = fluid.layers.data( name="dnn_data", shape=[-1, 1], dtype="int64", lod_level=1, append_batch_size=False) emb = fluid.layers.embedding( input=input, size=[100, 10], is_sparse=True, is_distributed=True, param_attr=fluid.ParamAttr(name="deep_embedding")) pool = fluid.layers.sequence_pool(input=emb, pool_type="sum") predict = fluid.layers.fc(input=pool, size=2, act='softmax') block = prog.global_block() for op in block.ops: if op.type == "lookup_table": is_sparse = op.attr("is_sparse") is_distributed = op.attr("is_distributed") self.assertFalse(is_distributed) self.assertTrue(is_sparse) class TestEntryAttrs(EntryAttrChecks): def test_embedding_layer(self): self.embedding_layer() if __name__ == '__main__': unittest.main()