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typo fixes

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svlandeg 2020-08-17 17:10:15 +02:00
parent da80c18660
commit 4fe4bab1c9
2 changed files with 3 additions and 3 deletions
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website/docs/api/data-formats.md
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@ -161,7 +161,7 @@ run [`spacy pretrain`](/api/cli#pretrain).
| `dropout` | The dropout rate. ~~float~~ | `0.2` | | `dropout` | The dropout rate. ~~float~~ | `0.2` |
| `n_save_every` | Saving frequency. ~~int~~ | `null` | | `n_save_every` | Saving frequency. ~~int~~ | `null` |
| `batch_size` | The batch size or batch size [schedule](https://thinc.ai/docs/api-schedules). ~~Union[int, Sequence[int]]~~ | `3000` | | `batch_size` | The batch size or batch size [schedule](https://thinc.ai/docs/api-schedules). ~~Union[int, Sequence[int]]~~ | `3000` |
| `seed` | The random seed. ~~int~~ | `${system.seed}` | | `seed` | The random seed. ~~int~~ | `${system:seed}` |
| `use_pytorch_for_gpu_memory` | Allocate memory via PyTorch. ~~bool~~ | `${system:use_pytorch_for_gpu_memory}` | | `use_pytorch_for_gpu_memory` | Allocate memory via PyTorch. ~~bool~~ | `${system:use_pytorch_for_gpu_memory}` |
| `tok2vec_model` | tok2vec model section in the config. ~~str~~ | `"components.tok2vec.model"` | | `tok2vec_model` | tok2vec model section in the config. ~~str~~ | `"components.tok2vec.model"` |
| `objective` | The pretraining objective. ~~Dict[str, Any]~~ | `{"type": "characters", "n_characters": 4}` | | `objective` | The pretraining objective. ~~Dict[str, Any]~~ | `{"type": "characters", "n_characters": 4}` |

4
website/docs/usage/training.md
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@ -144,7 +144,7 @@ https://github.com/explosion/spaCy/blob/develop/spacy/default_config.cfg
Under the hood, the config is parsed into a dictionary. It's divided into Under the hood, the config is parsed into a dictionary. It's divided into
sections and subsections, indicated by the square brackets and dot notation. For sections and subsections, indicated by the square brackets and dot notation. For
example, `[training]` is a section and `[training.batch_size]` a subsections. example, `[training]` is a section and `[training.batch_size]` a subsection.
Subsections can define values, just like a dictionary, or use the `@` syntax to Subsections can define values, just like a dictionary, or use the `@` syntax to
refer to [registered functions](#config-functions). This allows the config to refer to [registered functions](#config-functions). This allows the config to
not just define static settings, but also construct objects like architectures, not just define static settings, but also construct objects like architectures,
@ -156,7 +156,7 @@ sections of a config file are:
| `nlp` | Definition of the `nlp` object, its tokenizer and [processing pipeline](/usage/processing-pipelines) component names. | | `nlp` | Definition of the `nlp` object, its tokenizer and [processing pipeline](/usage/processing-pipelines) component names. |
| `components` | Definitions of the [pipeline components](/usage/processing-pipelines) and their models. | | `components` | Definitions of the [pipeline components](/usage/processing-pipelines) and their models. |
| `paths` | Paths to data and other assets. Re-used across the config as variables, e.g. `${paths:train}`, and can be [overwritten](#config-overrides) on the CLI. | | `paths` | Paths to data and other assets. Re-used across the config as variables, e.g. `${paths:train}`, and can be [overwritten](#config-overrides) on the CLI. |
| `system` | Settings related to system and hardware. Re-used across the config as variables, e.g. `${system.seed}`, and can be [overwritten](#config-overrides) on the CLI. | | `system` | Settings related to system and hardware. Re-used across the config as variables, e.g. `${system:seed}`, and can be [overwritten](#config-overrides) on the CLI. |
| `training` | Settings and controls for the training and evaluation process. | | `training` | Settings and controls for the training and evaluation process. |
| `pretraining` | Optional settings and controls for the [language model pretraining](#pretraining). | | `pretraining` | Optional settings and controls for the [language model pretraining](#pretraining). |