diff --git a/security/comments_specification_en.md b/security/comments_specification_en.md index 7d1fff4..70048ba 100644 --- a/security/comments_specification_en.md +++ b/security/comments_specification_en.md @@ -103,7 +103,7 @@ Supported Platforms: Args: network (Cell): A training or testing network. - loss_fn (Cell): Objective function, if loss_fn is None, the + loss_fn (Cell): Objective function, if `loss_fn` is None, the network should contain the logic of loss and grads calculation, and the logic of parallel if needed. Default: None. @@ -121,11 +121,11 @@ Supported Platforms: - O0: Do not change. - O2: Cast network to float16, keep batchnorm run in float32, using dynamic loss scale. - O3: Cast network to float16, with additional property 'keep_batchnorm_fp32=False'. - - auto: Set to level to recommended level in different devices. Set level to O2 on GPU, Set - level to O3 Ascend. The recommended level is choose by the export experience, cannot + - auto: Set to level to recommended level in different devices. Set level to "O2" on GPU, set + level to "O3" Ascend. The recommended level is choose by the export experience, cannot always generalize. User should specify the level for special network. - O2 is recommended on GPU, O3 is recommended on Ascend. + "O2" is recommended on GPU, "O3" is recommended on Ascend. ``` - Space requirements: @@ -136,7 +136,7 @@ Supported Platforms: Args: lr_power (float): Learning rate power controls how the learning rate decreases during training, must be less than or equal to zero. Use fixed learning rate if `lr_power` is zero. - use_locking (bool): If `True`, the var and accumulation tensors will be protected from being updated. + use_locking (bool): If True, the var and accumulation tensors will be protected from being updated. Default: False. Raises: @@ -442,7 +442,7 @@ Supported Platforms: class BasicLSTMCell(PrimitiveWithInfer): """ It's similar to operator :class:`DynamicRNN`. BasicLSTMCell will be deprecated in the future. - Please use DynamicRNN instead. + Please use :class:`DynamicRNN` instead. Supported Platforms: Deprecated @@ -503,9 +503,9 @@ def ms_function(fn=None, obj=None, input_signature=None): obj (Object): The Python Object that provides the information for identifying the compiled function. Default: None. input_signature (MetaTensor): The MetaTensor which describes the input arguments. The MetaTensor specifies - the shape and dtype of the Tensor and they will be supplied to this function. If input_signature + the shape and dtype of the Tensor and they will be supplied to this function. If `input_signature` is specified, each input to `fn` must be a `Tensor`. And the input parameters of `fn` cannot accept - `**kwargs`. The shape and dtype of actual inputs should keep the same as input_signature. Otherwise, + `**kwargs`. The shape and dtype of actual inputs should keep the same as `input_signature`. Otherwise, TypeError will be raised. Default: None. Returns: diff --git a/security/comments_specification_zh_cn.md b/security/comments_specification_zh_cn.md index 6d0f537..04e18c5 100644 --- a/security/comments_specification_zh_cn.md +++ b/security/comments_specification_zh_cn.md @@ -103,7 +103,7 @@ Supported Platforms: Args: network (Cell): A training or testing network. - loss_fn (Cell): Objective function, if loss_fn is None, the + loss_fn (Cell): Objective function, if `loss_fn` is None, the network should contain the logic of loss and grads calculation, and the logic of parallel if needed. Default: None. @@ -121,11 +121,11 @@ Supported Platforms: - O0: Do not change. - O2: Cast network to float16, keep batchnorm run in float32, using dynamic loss scale. - O3: Cast network to float16, with additional property 'keep_batchnorm_fp32=False'. - - auto: Set to level to recommended level in different devices. Set level to O2 on GPU, Set - level to O3 Ascend. The recommended level is choose by the export experience, cannot + - auto: Set to level to recommended level in different devices. Set level to "O2" on GPU, set + level to "O3" Ascend. The recommended level is choose by the export experience, cannot always generalize. User should specify the level for special network. - O2 is recommended on GPU, O3 is recommended on Ascend. + "O2" is recommended on GPU, "O3" is recommended on Ascend. ``` - 空格要求： @@ -136,7 +136,7 @@ Supported Platforms: Args: lr_power (float): Learning rate power controls how the learning rate decreases during training, must be less than or equal to zero. Use fixed learning rate if `lr_power` is zero. - use_locking (bool): If `True`, the var and accumulation tensors will be protected from being updated. + use_locking (bool): If True, the var and accumulation tensors will be protected from being updated. Default: False. Raises: @@ -441,7 +441,7 @@ Supported Platforms: class BasicLSTMCell(PrimitiveWithInfer): """ It's similar to operator :class:`DynamicRNN`. BasicLSTMCell will be deprecated in the future. - Please use DynamicRNN instead. + Please use :class:`DynamicRNN` instead. Supported Platforms: Deprecated @@ -502,9 +502,9 @@ def ms_function(fn=None, obj=None, input_signature=None): obj (Object): The Python Object that provides the information for identifying the compiled function. Default: None. input_signature (MetaTensor): The MetaTensor which describes the input arguments. The MetaTensor specifies - the shape and dtype of the Tensor and they will be supplied to this function. If input_signature + the shape and dtype of the Tensor and they will be supplied to this function. If `input_signature` is specified, each input to `fn` must be a `Tensor`. And the input parameters of `fn` cannot accept - `**kwargs`. The shape and dtype of actual inputs should keep the same as input_signature. Otherwise, + `**kwargs`. The shape and dtype of actual inputs should keep the same as `input_signature`. Otherwise, TypeError will be raised. Default: None. Returns: