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Fix not working links in Overview (PaddlePaddle#4147)
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* fix vision overview

* fix utils

* fix text

* fix static

* fix nn

* fix paddle

* remove sampled_softmax_with_cross_entropy

* remove alias of paddle.fluid.layers.sampled_softmax_with_cross_entropy
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SigureMo authored Dec 27, 2021
1 parent f54db24 commit 9a9dd8e
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Expand Up @@ -5,12 +5,6 @@ sampled_softmax_with_cross_entropy

.. py:function:: paddle.fluid.layers.sampled_softmax_with_cross_entropy(logits, label, num_samples, num_true=1, remove_accidental_hits=True, use_customized_samples=False, customized_samples=None, customized_probabilities=None, seed=0)
:alias_main: paddle.nn.functional.sampled_softmax_with_cross_entropy
:alias: paddle.nn.functional.sampled_softmax_with_cross_entropy,paddle.nn.functional.loss.sampled_softmax_with_cross_entropy
:old_api: paddle.fluid.layers.sampled_softmax_with_cross_entropy



**Sampled Softmax With Cross Entropy Operator**

对于较大的输出类,采样的交叉熵损失Softmax被广泛地用作输出层。该运算符为所有示例采样若干个样本,并计算每行采样张量的SoftMax标准化值,然后计算交叉熵损失。
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2 changes: 1 addition & 1 deletion docs/api/paddle/Overview_cn.rst
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Expand Up @@ -358,7 +358,7 @@ device相关
:widths: 10, 30

" :ref:`paddle.get_cuda_rng_state <cn_api_paddle_cn_get_cuda_rng_state>` ", "获取cuda随机数生成器的状态信息"
" :ref:`paddle.set_cuda_rng_state <cn_api_paddle_cn_set_cuda_rng_stat>` ", "设置cuda随机数生成器的状态信息"
" :ref:`paddle.set_cuda_rng_state <cn_api_paddle_cn_set_cuda_rng_state>` ", "设置cuda随机数生成器的状态信息"

.. _about_hapi:

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1 change: 0 additions & 1 deletion docs/api/paddle/nn/Overview_cn.rst
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Expand Up @@ -455,7 +455,6 @@ Embedding相关函数
" :ref:`paddle.nn.functional.l1_loss <cn_paddle_nn_functional_loss_l1>` ", "用于计算L1损失"
" :ref:`paddle.nn.functional.kl_div <cn_paddle_nn_functional_loss_kl_div>` ", "用于计算KL散度损失"
" :ref:`paddle.nn.functional.log_loss <cn_api_fluid_layers_log_loss>` ", "用于计算负对数损失"
" :ref:`paddle.nn.functional.sampled_softmax_with_cross_entropy <cn_api_fluid_layers_sampled_softmax_with_cross_entropy>` ", "为所有示例采样若干个样本,并计算每行采样张量的SoftMax标准化值,然后计算交叉熵损失"
" :ref:`paddle.nn.functional.margin_ranking_loss <cn_api_nn_cn_margin_ranking_loss>` ", "用于计算margin rank loss 损失"
" :ref:`paddle.nn.functional.mse_loss <cn_paddle_nn_functional_mse_loss>` ", "用于计算均方差误差"
" :ref:`paddle.nn.functional.nll_loss <cn_api_nn_functional_nll_loss>` ", "用于计算nll损失"
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2 changes: 1 addition & 1 deletion docs/api/paddle/nn/utils/spectral_norm_cn.rst
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@@ -1,4 +1,4 @@
.. __cn_api_nn_cn_spectral_norm:
.. _cn_api_nn_cn_spectral_norm:

spectral_norm
-------------------------------
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2 changes: 1 addition & 1 deletion docs/api/paddle/static/nn/sparse_embedding_cn.rst
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@@ -1,4 +1,4 @@
.. _cn_api_fluid_input_embedding:
.. _cn_api_fluid_contrib_layers_sparse_embedding:

sparse_embedding
-------------------------------
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2 changes: 1 addition & 1 deletion docs/api/paddle/text/Overview_cn.rst
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Expand Up @@ -49,4 +49,4 @@ PaddleNLP 提供了在文本任务上简洁易用的全流程API,旨在为飞
" `paddlenlp.data <https://paddlenlp.readthedocs.io/zh/latest/data_prepare/data_preprocess.html>`_ ", "文本数据处理Pipeline的相关API", "见链接文档"
" `paddlenlp.transformers <https://paddlenlp.readthedocs.io/zh/latest/model_zoo/transformers.html>`_ ", "基于Transformer结构相关的预训练模型API,包含ERNIE, BERT, RoBERTa, Electra等主流经典结构和下游任务", " ``model = paddlenlp.transformers.BertForSequenceClassification.from_pretrained('bert-wwm-chinese', num_classes=2)`` "
" `paddlenlp.metrics <https://paddlenlp.readthedocs.io/zh/latest/metrics/metrics.html>`_", "提供了文本任务上的一些模型评价指标,例如Perplexity、GlLUE中用到的评估器、BLEU、Rouge等,与飞桨高层API兼容", " ``metric = paddlenlp.metrics.AccuracyAndF1()`` "
" `paddlenlp.embeddings <https://github.com/PaddlePaddle/PaddleNLP/blob/develop/docs/embeddings.md>`_", "词向量相关API,支持一键快速加载包预训练的中文词向量,VisualDL高维可视化等功能", " ``token_embedding = paddlenlp.embeddings.TokenEmbedding(embedding_name='fasttext.wiki-news.target.word-word.dim300.en')`` "
" `paddlenlp.embeddings <https://paddlenlp.readthedocs.io/zh/latest/model_zoo/embeddings.html>`_", "词向量相关API,支持一键快速加载包预训练的中文词向量,VisualDL高维可视化等功能", " ``token_embedding = paddlenlp.embeddings.TokenEmbedding(embedding_name='fasttext.wiki-news.target.word-word.dim300.en')`` "
2 changes: 1 addition & 1 deletion docs/api/paddle/utils/Overview_cn.rst
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Expand Up @@ -42,7 +42,7 @@ paddle.utils 目录下包含飞桨框架工具类的API。具体如下:
" :ref:`guard <cn_api_fluid_unique_name_guard>` ", "更改命名空间"
" :ref:`switch <cn_api_fluid_unique_name_switch>` ", "切换命名空间"
" :ref:`cuda_profiler <cn_api_fluid_profiler_cuda_profiler>` ", "CUDA性能分析器"
" :ref:`profiler <cn_api_fluid_profiler_profile>` ", "通用性能分析器"
" :ref:`profiler <cn_api_fluid_profiler_profiler>` ", "通用性能分析器"
" :ref:`reset_profiler <cn_api_fluid_profiler_reset_profiler>` ", "清除之前的性能分析记录"
" :ref:`start_profiler <cn_api_fluid_profiler_start_profiler>` ", "激活使用性能分析器"
" :ref:`stop_profiler <cn_api_fluid_profiler_stop_profiler>` ", "停止使用性能分析器"
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2 changes: 1 addition & 1 deletion docs/api/paddle/utils/deprecated_cn.rst
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.. _cn_api_paddle_utils_deprecated
.. _cn_api_paddle_utils_deprecated:

paddle_utils_deprecated
-------------------------------
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4 changes: 2 additions & 2 deletions docs/api/paddle/vision/Overview_cn.rst
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Expand Up @@ -49,8 +49,8 @@ paddle.vision 目录是飞桨在视觉领域的高层API。具体如下:
" :ref:`resnet50 <cn_api_paddle_vision_models_resnet50>` ", "50层的ResNet模型"
" :ref:`resnet101 <cn_api_paddle_vision_models_resnet101>` ", "101层的ResNet模型"
" :ref:`resnet152 <cn_api_paddle_vision_models_resnet152>` ", "152层的ResNet模型"
" :ref:`wide_resnet50_2 <_cn_api_paddle_vision_models_wide_resnet50_2>` ", "50层的WideResNet模型"
" :ref:`wide_resnet101_2 <_cn_api_paddle_vision_models_wide_resnet101_2>` ", "101层的WideResNet模型"
" :ref:`wide_resnet50_2 <cn_api_paddle_vision_models_wide_resnet50_2>` ", "50层的WideResNet模型"
" :ref:`wide_resnet101_2 <cn_api_paddle_vision_models_wide_resnet101_2>` ", "101层的WideResNet模型"
" :ref:`ResNeXt <cn_api_paddle_vision_models_ResNeXt>` ", "ResNeXt模型"
" :ref:`resnext50_32x4d <cn_api_paddle_vision_models_resnext50_32x4d>` ", "ResNeXt-50 32x4d模型"
" :ref:`resnext50_64x4d <cn_api_paddle_vision_models_resnext50_64x4d>` ", "ResNeXt-50 64x4d模型"
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2 changes: 1 addition & 1 deletion docs/api/paddle/vision/models/desnet264_cn.rst
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@@ -1,4 +1,4 @@
.. _cn_api_paddle_vision_models_resnet264:
.. _cn_api_paddle_vision_models_densenet264:

densenet264
-------------------------------
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