wehub-resource-sync
45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# The file has been adapted from the file:
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# https://github.com/laekov/fastmoe/blob/master/fmoe/gates/naive_gate.py
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# Git commit hash: 295a615aacce7e54a37e7935274ba15e901c78e4
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# We retain the following license from the original files:
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# Copyright 2021, Jiaao He. All rights reserved.
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# Licensed under the Apache License, Version 2.0 (the "License").
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import paddle
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from paddle import nn
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from .base_gate import BaseGate
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class NaiveGate(BaseGate):
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def __init__(self, d_model, num_expert, world_size, topk=2):
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super().__init__(num_expert, world_size)
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self.gate = nn.Linear(d_model, self.tot_expert)
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self.gate.weight.name = "gate_" + self.gate.weight.name
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self.gate.bias.name = "gate_" + self.gate.bias.name
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self.top_k = topk
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def forward(self, inp, return_all_scores=False):
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gate = self.gate(inp)
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gate_top_k_val, gate_top_k_idx = paddle.topk(
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gate, k=self.top_k, axis=-1, largest=True, sorted=False
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)
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if return_all_scores:
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return gate_top_k_val, gate_top_k_idx, gate
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return gate_top_k_val, gate_top_k_idx
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