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35 lines
1.5 KiB
35 lines
1.5 KiB
6 years ago
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import paddle.fluid as fluid
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import pslib_pb2 as pslib
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from .node import DownpourServer
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from .node import DownpourWorker
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from paddle.fluid.distribute_lookup_table import find_distributed_lookup_table
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class DownpourSGD(object):
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def __init__(self, optimizer=opt, learning_rate=0.001, window=1):
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# todo(guru4elephant): if optimizer is not None, will warning here
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self.learning_rate_ = opt.learning_rate
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self.window_ = window
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def minimize(self, loss, startup_program=None,
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parameter_list=None, no_grad_set=None,
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prefetch_slots=None, prefetch_slots_emb=None):
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params_grads = sorted(append_backward(loss), key=lambda x:x[0].name)
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table_name = fluid_distributed_lookup_table(loss.block.program)
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server = DownpourServer()
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worker = DownpourWorker()
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server.add_sparse_table(0, learning_rate,
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prefetch_slots, prefetch_slots_emb)
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server.add_dense_table(1, learning_rate, params, grads)
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worker.add_sparse_table(0, learning_rate,
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prefetch_slots, prefetch_slots_emb)
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worker.add_dense_table(1, learning_rate, params, grads)
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ps_param = pslib.PSParameter()
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ps_param.server_param.CopyFrom(server.get_desc())
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ps_param.worker_param.CopyFrom(worker.get_desc())
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worker_skipped_ops = ["lookup_table", "lookup_table_grad"]
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return [solver_desc, parallel_desc]
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