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modify doc
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- [STABLE] Add dataset operations mapping between TensorFlow.data module and MindSpore.dataset module, [check list](https://www.mindspore.cn/docs/en/master/note/api_mapping/tensorflow_api_mapping.html#tf-data).
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- [STABLE] Add dataset operations mapping between TensorFlow.data module and MindSpore.dataset module, [check list](https://www.mindspore.cn/docs/en/master/note/api_mapping/tensorflow_api_mapping.html#tf-data).
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- [STABLE] Python multiprocessing optimization and make processes exit normally.
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- [STABLE] Python multiprocessing optimization and make processes exit normally.
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- [STABLE] Support [Dataset Autotune](https://www.mindspore.cn/tutorials/experts/en/master/debug/dataset_autotune.html) for tuning the speed of dataset pipeline automatically.
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- [STABLE] Support [Dataset Autotune](https://www.mindspore.cn/tutorials/experts/en/master/dataset/dataset_autotune.html) for tuning the speed of dataset pipeline automatically.
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- [BETA] [Dataset Offload](https://www.mindspore.cn/docs/en/master/design/dataset_offload.html) support new data augmentation operations: RandomColorAdjust, RandomSharpness, TypeCast.
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- [BETA] [Dataset Offload](https://www.mindspore.cn/tutorials/experts/en/master/dataset/dataset_offload.html) support new data augmentation operations: RandomColorAdjust, RandomSharpness, TypeCast.
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- Output a single data column when `__getitem__/__next__` methods of GeneratorDataset return a single NumPy object.
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- Output a single data column when `__getitem__/__next__` methods of GeneratorDataset return a single NumPy object.
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- Use `ulimit -u 10240` to increase the number of threads/processes available to the current user when specify too many processes or threads for loading dataset may cause RuntimeError: can't start new thread.
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- Use `ulimit -u 10240` to increase the number of threads/processes available to the current user when specify too many processes or threads for loading dataset may cause RuntimeError: can't start new thread.
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@ -136,7 +136,7 @@ Contributions of any kind are welcome!
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- [STABLE] Support overwrite feature in MindRecord.
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- [STABLE] Support overwrite feature in MindRecord.
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- [STABLE] Log improvement and more friendly to users.
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- [STABLE] Log improvement and more friendly to users.
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- [BETA] Support new feature [Dataset Offload](https://www.mindspore.cn/docs/zh-CN/master/design/dataset_offload.html) to speed up data processing by heterogeneous computing.
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- [BETA] Support new feature [Dataset Offload](https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_offload.html) to speed up data processing by heterogeneous computing.
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- [BETA] Support new feature [Dataset Autotune](https://www.mindspore.cn/tutorials/experts/zh-CN/master/debug/auto_tune.html) to adjust parallelism of dataset pipeline automatically.
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- [BETA] Support new feature [Dataset Autotune](https://www.mindspore.cn/tutorials/experts/zh-CN/master/debug/auto_tune.html) to adjust parallelism of dataset pipeline automatically.
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#### GraphKernel Fusion
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#### GraphKernel Fusion
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- [STABLE] 增加了数据处理API的差异文档,比较TensorFlow.data与MindSpore.dataset部分算子的差异,详见 [对比文档](https://www.mindspore.cn/docs/zh-CN/master/note/api_mapping/tensorflow_api_mapping.html#tf-data)。
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- [STABLE] 增加了数据处理API的差异文档,比较TensorFlow.data与MindSpore.dataset部分算子的差异,详见 [对比文档](https://www.mindspore.cn/docs/zh-CN/master/note/api_mapping/tensorflow_api_mapping.html#tf-data)。
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- [STABLE] Python多进程逻辑优化,保证不同异常场景的正常退出。
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- [STABLE] Python多进程逻辑优化,保证不同异常场景的正常退出。
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- [STABLE] 支持[自动数据加速](https://www.mindspore.cn/tutorials/experts/zh-CN/master/debug/dataset_autotune.html),可以自适应调节数据处理管道的执行速度。
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- [STABLE] 支持[自动数据加速](https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_autotune.html),可以自适应调节数据处理管道的执行速度。
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- [BETA] [数据处理异构加速](https://www.mindspore.cn/docs/zh-CN/master/design/dataset_offload.html) 支持了新的数据增强操作: RandomColorAdjust、RandomSharpness和TypeCast。
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- [BETA] [数据处理异构加速](https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_offload.html) 支持了新的数据增强操作: RandomColorAdjust、RandomSharpness和TypeCast。
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- GeneratorDataset加载自定义数据集时,当`__getitem__/__next__`方法返回单个NumPy对象,对应会输出单个数据列。
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- GeneratorDataset加载自定义数据集时,当`__getitem__/__next__`方法返回单个NumPy对象,对应会输出单个数据列。
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- 用户在数据预处理中使用过多的进程数/线程数情况下,会出现错误RuntimeError: can't start new thread,可以通过 `ulimit -u 10240` 增加当前用户可用的线程/进程数解决。
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- 用户在数据预处理中使用过多的进程数/线程数情况下,会出现错误RuntimeError: can't start new thread,可以通过 `ulimit -u 10240` 增加当前用户可用的线程/进程数解决。
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- **cache** (DatasetCache, 可选) - 单节点数据缓存服务,用于加快数据集处理,详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值:None,不使用缓存。
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- **cache** (DatasetCache, 可选) - 单节点数据缓存服务,用于加快数据集处理,详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值:None,不使用缓存。
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- **callbacks** (DSCallback, list[DSCallback], 可选) - 要调用的Dataset回调函数列表。默认值:None。
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- **callbacks** (DSCallback, list[DSCallback], 可选) - 要调用的Dataset回调函数列表。默认值:None。
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- **max_rowsize** (int, 可选) - 指定在多进程之间复制数据时,共享内存分配的最大空间,仅当 `python_multiprocessing` 为True时,该选项有效。默认值:16,单位为MB。
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- **max_rowsize** (int, 可选) - 指定在多进程之间复制数据时,共享内存分配的最大空间,仅当 `python_multiprocessing` 为True时,该选项有效。默认值:16,单位为MB。
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- **offload** (bool, 可选) - 是否进行异构硬件加速,详情请阅读 `数据准备异构加速 <https://www.mindspore.cn/docs/zh-CN/master/design/dataset_offload.html>`_ 。默认值:None。
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- **offload** (bool, 可选) - 是否进行异构硬件加速,详情请阅读 `数据准备异构加速 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_offload.html>`_ 。默认值:None。
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.. note::
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.. note::
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- `operations` 参数主要接收 `mindspore.dataset` 模块中c_transforms、py_transforms算子,以及用户定义的Python函数(PyFuncs)。
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- `operations` 参数主要接收 `mindspore.dataset` 模块中c_transforms、py_transforms算子,以及用户定义的Python函数(PyFuncs)。
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