fastai_recorderish.py

from fastai.vision import *

def try_detach( o):
    """Try to detach and convert to numpy a tensor"""
    if issubclass(type(o),torch.Tensor): o=  o.detach().cpu().numpy()
    if type(o)==np.ndarray: o = float(o)
    return o
        
class MyRecorder(Callback):
    """Pass it values in 'learner' you want to record at each batch
    When finished, it puts everything in a pandas data from '.df' that you can use to get the data"""
    def __init__(self, things_to_get=None):
        self.things_to_get= ['n_iter', 'epoch']   
        if things_to_get is not None:
            self.things_to_get = things_to_get+self.things_to_get
        print(self.things_to_get)        
   
    def before_fit(self):  self.log=[]
    def after_step(self):          
        values_to_log = {a:try_detach(getattr(self.learn,a, 0)) for a in self.things_to_get}
        self.log.append(values_to_log)
        
    def create_df(self): self.df =pd.DataFrame(self.log)     
    def after_fit(self): self.create_df()