diff --git a/_typos.toml b/_typos.toml index 8b281b8f886..b7fd3fdd637 100644 --- a/_typos.toml +++ b/_typos.toml @@ -19,6 +19,7 @@ CANN = "CANN" Clas = "Clas" arange = "arange" unsupport = "unsupport" +Nervana = "Nervana" # These words need to be fixed Accuray = "Accuray" @@ -41,8 +42,6 @@ Interfce = "Interfce" Kernal = "Kernal" Learing = "Learing" Moible = "Moible" -Nervana = "Nervana" -Numberic = "Numberic" Operaton = "Operaton" Optimizaing = "Optimizaing" Optimzier = "Optimzier" @@ -169,9 +168,6 @@ metrices = "metrices" muliply = "muliply" mulitplying = "mulitplying" mutbale = "mutbale" -neeeded = "neeeded" -nessesary = "nessesary" -numberic = "numberic" occurence = "occurence" opeartor = "opeartor" opeartors = "opeartors" diff --git a/docs/design/network/deep_speech_2.md b/docs/design/network/deep_speech_2.md index 10c14746650..5497c022bd4 100644 --- a/docs/design/network/deep_speech_2.md +++ b/docs/design/network/deep_speech_2.md @@ -137,7 +137,7 @@ Key ingredients about the layers: - Bi-direcitional + without row convolution: if we don't care about the inference latency. - **Row convolution**: - For looking only a few steps ahead into the feature, instead of looking into a whole sequence in bi-directional RNNs. - - Not nessesary if with bi-direcitional RNNs. + - Not necessary if with bi-direcitional RNNs. - "**Row**" means convolutions are done within each frequency dimension (row), and no convolution kernels shared across. - **Batch Normalization Layers**: - Added to all above layers (except for data and loss layer). diff --git a/docs/dev_guides/custom_device_docs/memory_api_en.md b/docs/dev_guides/custom_device_docs/memory_api_en.md index 0d6595ae4db..5fe6bcf9c21 100644 --- a/docs/dev_guides/custom_device_docs/memory_api_en.md +++ b/docs/dev_guides/custom_device_docs/memory_api_en.md @@ -232,7 +232,7 @@ dst - the address of destination device memory src - the address of source host memory -size - the size of memory neeeded to be copied (in byte) +size - the size of memory needed to be copied (in byte) ## async_memory_copy_d2h 【optional】 diff --git a/docs/dev_guides/style_guide_and_references/type_annotations_specification_cn.md b/docs/dev_guides/style_guide_and_references/type_annotations_specification_cn.md index 341d02da61e..6bf88ef1e2f 100644 --- a/docs/dev_guides/style_guide_and_references/type_annotations_specification_cn.md +++ b/docs/dev_guides/style_guide_and_references/type_annotations_specification_cn.md @@ -176,7 +176,7 @@ if TYPE_CHECKING: from paddle import Tensor # TensorLike 定义如下 -# TensorLike: TypeAlias = Union[npt.NDArray[Any], "Tensor", Numberic] +# TensorLike: TypeAlias = Union[npt.NDArray[Any], "Tensor", Numeric] def add(a: Tensor, b: TensorLike) -> Tensor: if isinstance(b, np.ndarray): @@ -184,10 +184,10 @@ def add(a: Tensor, b: TensorLike) -> Tensor: elif isinstance(b, paddle.Tensor): return dispatch_paddle_add(a, b) else: - return dispatch_numberic_add(a, b) + return dispatch_numeric_add(a, b) ``` -这里 `TensorLike` 是一个通用类型,包含了 `np.ndarray`、`paddle.Tensor`、`Numberic` 三种类型,因此在实现中也应该考虑到这三种类型的输入。 +这里 `TensorLike` 是一个通用类型,包含了 `np.ndarray`、`paddle.Tensor`、`Numeric` 三种类型,因此在实现中也应该考虑到这三种类型的输入。 ### 使用更加明确的类型以提供更好的提示效果