wehub-resource-sync
60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
# Copyright (c) 2023 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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from paddle import nn
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from paddle.nn import functional as F
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class Linear(nn.Layer):
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"""
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Same as paddle.layer.Linear, except weight matrix is stored as [out_features, in_features] (same as torch),
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instead of [in_features, out_features]
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"""
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def __init__(
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self,
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in_features,
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out_features,
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weight_attr=None,
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bias_attr=None,
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name=None,
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):
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super(Linear, self).__init__()
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self._dtype = self._helper.get_default_dtype()
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self._weight_attr = weight_attr
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self._bias_attr = bias_attr
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self.weight = self.create_parameter(
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shape=[out_features, in_features], # regular linear has shape [in_features, out_features]
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attr=self._weight_attr,
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dtype=self._dtype,
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is_bias=False,
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)
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self.bias = self.create_parameter(
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shape=[out_features],
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attr=self._bias_attr,
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dtype=self._dtype,
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is_bias=True,
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)
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self.name = name
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def forward(self, input):
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out = F.linear(x=input, weight=self.weight.T, bias=self.bias, name=self.name)
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return out
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def extra_repr(self):
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name_str = ", name={}".format(self.name) if self.name else ""
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return "in_features={}, out_features={}, dtype={}{}".format(
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self.weight.shape[1], self.weight.shape[0], self._dtype, name_str
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)
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