vision.learner | fastai
fastai1.fast.ai › visionJan 05, 2021 · Computer Vision Learner vision.learner is the module that defines the cnn_learner method, to easily get a model suitable for transfer learning. Transfer learning Transfer learning is a technique where you use a model trained on a very large dataset (usually ImageNet in computer vision) and then adapt it to your own dataset.
vision.learner | fastai
https://fastai1.fast.ai/vision.learner.html05.01.2021 · vision.learner is the module that defines the cnn_learner method, to easily get a model suitable for transfer learning. Transfer learning ¶ Transfer learning is a technique where you use a model trained on a very large dataset (usually ImageNet in computer vision) and then adapt it to your own dataset.
cnn_learner: Cnn_learner in fastai: Interface to 'fastai'
rdrr.io › cran › fastaiOct 25, 2021 · Cbs is one or a list of Callbacks to pass to the Learner. metrics. It is an optional list of metrics, that can be either functions or Metrics. path. The folder where to work. model_dir. Path and model_dir are used to save and/or load models. wd. It is the default weight decay used when training the model.
Learner for the vision applications | fastai
docs.fast.ai › visionNov 07, 2021 · The most important functions of this module are cnn_learner and unet_learner. They will help you define a Learner using a pretrained model. See the vision tutorial for examples of use. Cut a pretrained model By default, the fastai library cuts a pretrained model at the pooling layer. This function helps detecting it. has_pool_type [source]
Learner, Metrics, and Basic Callbacks | fastai
docs.fast.ai › learnerNov 29, 2021 · For instance, fastai's CrossEntropyFlat takes the argmax or predictions in its decodes. Depending on the loss_func attribute of Learner, an activation function will be picked automatically so that the predictions make sense. For instance if the loss is a case of cross-entropy, a softmax will be applied, or if the loss is binary cross entropy ...
Learner, Metrics, and Basic Callbacks | fastai
https://docs.fast.ai/learner29.11.2021 · Warning: load_learner requires all your custom code be in the exact same place as when exporting your Learner (the main script, or the module you imported it from). fastai provides to_detach which by default detachs tensor gradients, and gathers (calling maybe_gather ) tensors from all ranks if running in distributed data parallel (DDP) mode.