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@ -582,57 +582,6 @@ class TestDistLookupTable(TestDistLookupTableBase):
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startup_ops)
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class TestRemoteLookupTable(TestDistLookupTableBase):
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def net_conf(self):
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self.network_with_table(
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is_sparse=True, is_distributed=False, remote_prefetch=True)
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def transpiler_test_impl(self):
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pserver1, startup1 = self.get_pserver(self.pserver1_ep)
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self.assertEqual(len(pserver1.blocks), 6)
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# 0 listen_and_serv
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# 1 optimize for fc_w or fc_b adam
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self.assertEqual([op.type for op in pserver1.blocks[1].ops],
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["sum", "scale", "adam", "scale", "scale"])
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# 4 prefetch -> lookup_sparse_table for data0
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self.assertEqual([op.type for op in pserver1.blocks[2].ops],
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["sum", "scale", "adam", "scale", "scale"])
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# 2 optimize for table sgd
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self.assertEqual([op.type for op in pserver1.blocks[3].ops],
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["sum", "sgd"])
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# 3 prefetch -> lookup_sparse_table for data0
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self.assertEqual([op.type for op in pserver1.blocks[4].ops],
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["lookup_sparse_table"])
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# 5 save table
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self.assertEqual([op.type for op in pserver1.blocks[5].ops], ["save"])
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trainer, trainer_startup = self.get_trainer()
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self.assertEqual(len(trainer.blocks), 1)
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ops = [
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'split_ids', 'prefetch', 'merge_ids', 'sequence_pool',
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'sequence_pool', 'lookup_table', 'sequence_pool', 'concat', 'mul',
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'elementwise_add', 'cross_entropy', 'mean', 'fill_constant',
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'mean_grad', 'cross_entropy_grad', 'elementwise_add_grad', 'send',
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'mul_grad', 'send', 'concat_grad', 'sequence_pool_grad',
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'lookup_table_grad', 'split_selected_rows', 'send',
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'sequence_pool_grad', 'lookup_table_grad', 'sequence_pool_grad',
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'lookup_table_grad', 'sum', 'split_ids', 'send', 'send_barrier',
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'recv', 'recv', 'recv', 'fetch_barrier', 'concat'
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]
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self.assertEqual([op.type for op in trainer.blocks[0].ops], ops)
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startup_ops = [
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'fill_constant', 'fill_constant', 'fill_constant', 'fill_constant',
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'fill_constant', 'fill_constant', 'fill_constant', 'fill_constant',
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'fill_constant', 'fill_constant', 'fill_constant', 'fill_constant',
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'fill_constant', 'fill_constant', 'uniform_random',
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'uniform_random', 'recv', 'recv', 'recv', 'fetch_barrier', 'concat',
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'fake_init'
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]
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self.assertEqual([op.type for op in trainer_startup.blocks[0].ops],
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startup_ops)
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class TestAsyncLocalLookupTable(TestDistLookupTableBase):
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def net_conf(self):
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self.network_with_table(is_sparse=True, is_distributed=False)
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