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fix samle,Sovler,Simle
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_typos.toml

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@@ -30,13 +30,10 @@ feeded = "feeded"
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# These words need to be fixed
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Learing = "Learing"
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Setment = "Setment"
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Simle = "Simle"
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Sovler = "Sovler"
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libary = "libary"
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matrics = "matrics"
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metrices = "metrices"
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mutbale = "mutbale"
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samle = "samle"
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schedual = "schedual"
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secenarios = "secenarios"
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sematic = "sematic"

docs/dev_guides/sugon/paddle_c86_fix_guides_cn.md

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@@ -46,7 +46,7 @@ data_type[float]:data_layout[Undefined(AnyLayout)]:place[Place(cpu)]:library_typ
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![图片](../images/sugon_paddle_with_hip.png)
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根据注释,是由于初始适配时 ROCm 下的 rocSolver 库未曾适配导致的,需参考 cuSovler 代码以及 [hipSOLVER](https://github.com/ROCmSoftwarePlatform/hipSOLVER) 中 rocSovler 和 cuSolver 的 API 封装示例修改代码使改算子可以在 HIP 环境下正确运行。
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根据注释,是由于初始适配时 ROCm 下的 rocSolver 库未曾适配导致的,需参考 cuSolver 代码以及 [hipSOLVER](https://github.com/ROCmSoftwarePlatform/hipSOLVER) 中 rocSolver 和 cuSolver 的 API 封装示例修改代码使改算子可以在 HIP 环境下正确运行。
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### 情况 2:算子 GPU Kernel 存在,少了某个 LibraryType 下的 Kernel
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docs/guides/advanced/visualdl_usage_en.md

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@@ -466,7 +466,7 @@ if audio_sample_num == 0:
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audio_path = "test.wav"
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audio_shape, audio_data = read_audio_data(audio_path)
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# Add data through member function set_samle()
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# Add data through member function set_sample()
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input_audio.set_sample(idx, audio_shape, audio_data)
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audio_sample_num += 1
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docs/practices/nlp/seq2seq_with_attention.ipynb

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"source": [
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"### 3.1 Encoder部分\n",
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"\n",
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"在编码器的部分,通过查找完Embedding之后接一个LSTM的方式构建一个对源语言编码的网络。飞桨的RNN系列的API,除了LSTM之外,还提供了SimleRNN, GRU供使用,同时,还可以使用反向RNN,双向RNN,多层RNN等形式。也可以通过`dropout`参数设置是否对多层RNN的中间层进行`dropout`处理,来防止过拟合。\n",
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"在编码器的部分,通过查找完Embedding之后接一个LSTM的方式构建一个对源语言编码的网络。飞桨的RNN系列的API,除了LSTM之外,还提供了SimpleRNN, GRU供使用,同时,还可以使用反向RNN,双向RNN,多层RNN等形式。也可以通过`dropout`参数设置是否对多层RNN的中间层进行`dropout`处理,来防止过拟合。\n",
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"\n",
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"除了使用序列到序列的RNN操作之外,也可以通过SimpleRNN, GRUCell, LSTMCell等API更灵活的创建单步的RNN计算,甚至通过继承RNNCellBase来实现自己的RNN计算单元。"
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]

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