diff --git a/lib/axon.ex b/lib/axon.ex index 8aefafe0..2ddfa204 100644 --- a/lib/axon.ex +++ b/lib/axon.ex @@ -143,7 +143,7 @@ defmodule Axon do parameters and possibly state. To define a custom layer, you just need to define a `defn` implementation: - defn my_layer(x, weight, _opts \\ []) do + defn my_layer(x, weight, _opts \\\\ []) do Nx.atan2(x, weight) end diff --git a/lib/axon/layers.ex b/lib/axon/layers.ex index 66a0bce5..80dd0a0a 100644 --- a/lib/axon/layers.ex +++ b/lib/axon/layers.ex @@ -1457,7 +1457,7 @@ defmodule Axon.Layers do * `:rate` - dropout rate. Used to determine probability a connection will be dropped. Required. - # `:noise_shape` - input noise shape. Shape of `mask` which can be useful + * `:noise_shape` - input noise shape. Shape of `mask` which can be useful for broadcasting `mask` across feature channels or other dimensions. Defaults to shape of input tensor. @@ -1492,7 +1492,7 @@ defmodule Axon.Layers do * `:rate` - dropout rate. Used to determine probability a connection will be dropped. Required. - # `:noise_shape` - input noise shape. Shape of `mask` which can be useful + * `:noise_shape` - input noise shape. Shape of `mask` which can be useful for broadcasting `mask` across feature channels or other dimensions. Defaults to shape of input tensor. @@ -1536,7 +1536,7 @@ defmodule Axon.Layers do * `:rate` - dropout rate. Used to determine probability a connection will be dropped. Required. - # `:noise_shape` - input noise shape. Shape of `mask` which can be useful + * `:noise_shape` - input noise shape. Shape of `mask` which can be useful for broadcasting `mask` across feature channels or other dimensions. Defaults to shape of input tensor. """ diff --git a/lib/axon/loop.ex b/lib/axon/loop.ex index 4f291936..fc277e7a 100644 --- a/lib/axon/loop.ex +++ b/lib/axon/loop.ex @@ -186,13 +186,13 @@ defmodule Axon.Loop do Axon loops are typically created from one of the factory functions provided in this module: - * `Axon.Loop.loop/3` - Creates a loop from step function and optional initialization + * `Axon.Loop.loop/3` - Creates a loop from step function and optional initialization functions and output transform functions. - * `Axon.Loop.trainer/3` - Creates a supervised training loop from model, loss, and + * `Axon.Loop.trainer/3` - Creates a supervised training loop from model, loss, and optimizer. - * `Axon.Loop.evaluator/1` - Creates a supervised evaluator loop from model. + * `Axon.Loop.evaluator/1` - Creates a supervised evaluator loop from model. ## Running loops diff --git a/lib/axon/metrics.ex b/lib/axon/metrics.ex index cf1753e1..31962d51 100644 --- a/lib/axon/metrics.ex +++ b/lib/axon/metrics.ex @@ -38,8 +38,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Examples @@ -96,8 +96,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Options @@ -127,8 +127,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Options @@ -285,8 +285,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Options @@ -314,8 +314,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Options @@ -359,8 +359,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Examples @@ -390,8 +390,8 @@ defmodule Axon.Metrics do ## Argument Shapes - * `y_true` - $\(d_0, d_1, ..., d_n\)$ - * `y_pred` - $\(d_0, d_1, ..., d_n\)$ + * `y_true` - $(d_0, d_1, ..., d_n)$ + * `y_pred` - $(d_0, d_1, ..., d_n)$ ## Examples