def silent_console(silent:bool=True):
"Turn off console progress bar output."
fastprogress.fastprogress.NO_BAR = silent
mbar, pbar = force_console_behavior()
cls_list = [fastprogress.fastprogress, basic_train, basic_data,
dataclasses.dataclass, text, text.data, core]
for c in cls_list: c.master_bar, c.progress_bar = mbar,pbar
def hide_fastai_progress_bar():
"""Hide fastai progress bar"""
fastprogress.fastprogress.NO_BAR = True
fastprogress.fastprogress.WRITER_FN = str
master_bar, progress_bar = force_console_behavior()
fastai.basic_train.master_bar, fastai.basic_train.progress_bar = (
master_bar,
progress_bar,
)
def __enter__(self):
#silence progress bar
fastprogress.fastprogress.NO_BAR = True
fastai.basic_train.master_bar, fastai.basic_train.progress_bar = force_console_behavior(
)
self.orig_callback_fns = copy(self.learn.callback_fns)
rec_name = [
x for x in self.learn.callback_fns
if hasattr(x, 'func') and x.func == Recorder
]
if len(rec_name):
rec_idx = self.learn.callback_fns.index(rec_name[0])
self.learn.callback_fns[rec_idx] = partial(
Recorder, add_time=True, silent=True) #silence recorder
return self.learn
def silent_console(silent: bool = True):
"Turn off console progress bar output."
import fastai2.torch_core, fastai2.text.learner, fastai2.text.core, fastai2.callback.progress, fastai2.data.external
fastprogress.fastprogress.NO_BAR = silent
mbar, pbar = force_console_behavior()
cls_list = [
fastprogress.fastprogress,
fastai2.torch_core,
fastai2.text.learner,
fastai2.text.core,
fastai2.callback.progress,
fastai2.data.external,
]
for c in cls_list:
c.master_bar, c.progress_bar = mbar, pbar
import numpy as np
import torch
from torch.utils.data import Dataset, TensorDataset, DataLoader
import fastai
from fastai.vision import Image
# For fastai pbar work in notebooks in vscode and pycharm
from fastprogress.fastprogress import force_console_behavior
master_bar, progress_bar = force_console_behavior()
fastai.basic_train.master_bar, fastai.basic_train.progress_bar = master_bar, progress_bar
class ImageArrayDS(Dataset):
def __init__(self, images, labels, tfms=None):
self.images = torch.FloatTensor(images)
self.labels = torch.LongTensor(labels)
self.tfms = tfms
def __getitem__(self, idx):
image = Image(self.images[idx])
if self.tfms is not None:
image = image.apply_tfms(self.tfms)
return image, self.labels[idx]
def __len__(self):
return len(self.images)
class Inferencer:
def __init__(self, model, batch_size=8192):
def __enter__(self):
if self.show:
return
# silence progress bar
fastprogress.fastprogress.NO_BAR = True
fastai.basic_train.master_bar, fastai.basic_train.progress_bar = force_console_behavior()