callbacks | fastai
fastai1.fast.ai › callbacksJan 05, 2021 · fastai's training loop is highly extensible, with a rich callback system. See the callback docs if you're interested in writing your own callback. See below for a list of callbacks that are provided with fastai, grouped by the module they're defined in.
Learner, Metrics, and Basic Callbacks | fastai
https://docs.fast.ai/learner29.11.2021 · Callback s are used for every tweak of the training loop. Each Callback is registered as an attribute of Learner (with camel case). At creation, all the callbacks in defaults.callbacks ( TrainEvalCallback, Recorder and ProgressCallback) are associated to the Learner. metrics is an optional list of metrics, that can be either functions or Metric ...
callbacks | fastai
https://fastai1.fast.ai/callbacks.html05.01.2021 · Callbacks implemented in the fastai library. fastai's training loop is highly extensible, with a rich callback system. See the callback docs if you're interested in writing your own callback. See below for a list of callbacks that are provided with fastai, grouped by the module they're defined in.
Model hooks | fastai
docs.fast.ai › callbackNov 29, 2021 · hook_outputs ( modules, detach = True, cpu = False, grad = False) Return Hooks that store activations of all modules in self.stored. The activations stored are the gradients if grad=True, otherwise the output of modules. If detach=True they are detached from their history, and if cpu=True, they're put on the CPU.
Callbacks | fastai
docs.fast.ai › callbackNov 07, 2021 · Callbacks can occur at any of these times:: after_create before_fit before_epoch before_train before_batch after_pred after_loss before_backward before_step after_step after_cancel_batch after_batch after_cancel_train after_train before_validate after_cancel_validate after_validate after_cancel_epoch after_epoch after_cancel_fit after_fit.
callbacks.hooks | fastai
fastai1.fast.ai › callbacksJan 05, 2021 · Hook callbacks¶. This provides both a standalone class and a callback for registering and automatically deregistering PyTorch hooks, along with some pre-defined hooks. Hooks can be attached to any nn.Module, for either the forward or the backward pass.
Imports | fastai
https://fastai1.fast.ai/imports.html05.01.2021 · will populate the current namespace with these external modules in addition to fastai-specific functions and variables. This page documents these convenience imports, which are defined in fastai.imports.. Note: since this document was manually created, it could be outdated by the time you read it.
Model hooks | fastai
https://docs.fast.ai/callback.hook.html29.11.2021 · Hooks are functions you can attach to a particular layer in your model and that will be executed in the forward pass (for forward hooks) or backward pass (for backward hooks). Here we begin with an introduction around hooks, but you should jump to HookCallback if you quickly want to implement one (and read the following example ActivationStats).