From 18468551cec636676a56a9f34fd1861c902296f4 Mon Sep 17 00:00:00 2001 From: Madeesh Kannan Date: Thu, 4 Aug 2022 13:11:07 +0200 Subject: [PATCH] Docs: Fix/update `label_smoothing` description, run prettier (#733) --- website/docs/api-loss.md | 9 ++++----- website/docs/api-util.md | 12 +++++++----- 2 files changed, 11 insertions(+), 10 deletions(-) diff --git a/website/docs/api-loss.md b/website/docs/api-loss.md index 3720a78f5..5ccf84b58 100644 --- a/website/docs/api-loss.md +++ b/website/docs/api-loss.md @@ -70,9 +70,8 @@ are expected to be in the range of `[0, 1]`. They can both represent exclusive classes from multi-class cross-entropy (generally coming from a `softmax` layer) or could be classwise binary decisions for multi-label cross-entropy (`sigmoid` layer). The `truths` are most commonly provided as labels in `Ints1d`, -`List[int]` or `List[str]` format. -Alternatively, users can provide `truths` as a `Floats2d` for -example to encode label-confidences. +`List[int]` or `List[str]` format. Alternatively, users can provide `truths` as +a `Floats2d` for example to encode label-confidences. @@ -98,7 +97,7 @@ normalize = true | `normalize` | bool | Normalize and divide by number of examples given. | | `neg_prefix` | str | Prefix used to indicate that a label is negative e.g. "!sci-fi". | | `missing_value` | Union[str, int] | Specific label that indicates the value is missing and should not be considered for training/evaluation purposes, e.g. empty string `""` or `0`. | -| `label_smoothing` | float | Smoothing-coefficient for label-smoothing in range of [0, 0.5[. | +| `label_smoothing` | float | Smoothing-coefficient for label-smoothing. | ### SequenceCategoricalCrossentropy {#sequence_categorical_crossentropy tag="class"} @@ -138,7 +137,7 @@ normalize = true | `normalize` | bool | Normalize and divide by number of examples given. | | `neg_prefix` | str | Symbol that indicates that a label is negative e.g. "!sci-fi". | | `missing_value` | Union[str, int] | Symbol for "missing value" among the labels. | -| `label_smoothing` | float | Smoothing-coefficient for label-smoothing in range of [0, 0.5]. | +| `label_smoothing` | float | Smoothing-coefficient for label-smoothing. | ### L2Distance {#l2distance tag="class"} diff --git a/website/docs/api-util.md b/website/docs/api-util.md index 158da5446..add7c12e1 100644 --- a/website/docs/api-util.md +++ b/website/docs/api-util.md @@ -133,11 +133,13 @@ element). Converts a class vector (integers) to binary class matrix. Based on [`keras.utils.to_categorical`](https://keras.io/utils/). -| Argument | Type | Description | -| ----------- | ---------------------- | ---------------------------------------------------------------------------------------------- | -| `Y` | IntsXd | Class vector to be converted into a matrix (integers from `0` to `n_classes`). | -| `n_classes` | Optional[int] | Total number of classes. | -| **RETURNS** |  Floats2d | A binary matrix representation of the input. The axis representing the classes is placed last. | +| Argument | Type | Description | +| ----------------- | ---------------------- | ---------------------------------------------------------------------------------------------- | +| `Y` | IntsXd | Class vector to be converted into a matrix (integers from `0` to `n_classes`). | +| `n_classes` | Optional[int] | Total number of classes. | +| _keyword-only_ | | | +| `label_smoothing` | float | Smoothing-coefficient for label-smoothing. | +| **RETURNS** | Floats2d | A binary matrix representation of the input. The axis representing the classes is placed last. | ### xp2torch {#xp2torch tag="function"}