repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
fastai | fastai-master/fastai/losses.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/01a_losses.ipynb.
# %% ../nbs/01a_losses.ipynb 2
from __future__ import annotations
from .imports import *
from .torch_imports import *
from .torch_core import *
from .layers import *
# %% auto 0
__all__ = ['BaseLoss', 'CrossEntropyLossFlat', 'FocalLoss', 'FocalLossF... | 11,450 | 40.043011 | 130 | py |
fastai | fastai-master/fastai/torch_core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/00_torch_core.ipynb.
# %% ../nbs/00_torch_core.ipynb 2
from __future__ import annotations
from .imports import *
from .torch_imports import *
from packaging.version import parse
# %% auto 0
__all__ = ['norm_types', 'setup_cuda', 'subplots', 'show_image', 'show_titled... | 36,527 | 39.40708 | 168 | py |
fastai | fastai-master/fastai/torch_basics.py | from torch import multiprocessing
import platform,os
if platform.system()=='Darwin':
# Python 3.8 changed to 'spawn' but that doesn't work with PyTorch DataLoader w n_workers>0
multiprocessing.set_start_method('fork', force=True)
# workaround "OMP: Error #15: Initializing libiomp5.dylib, but found libomp.dy... | 516 | 35.928571 | 106 | py |
fastai | fastai-master/fastai/torch_imports.py | import pandas as pd
import torch
from torch import as_tensor,Tensor,ByteTensor,LongTensor,FloatTensor,HalfTensor,DoubleTensor
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import SequentialSampler,RandomSampler,Sampler,BatchSampler
from torch.utils.data import IterableDataset,get_worker_in... | 400 | 39.1 | 92 | py |
fastai | fastai-master/fastai/learner.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/13a_learner.ipynb.
# %% ../nbs/13a_learner.ipynb 2
from __future__ import annotations
from .data.all import *
from .optimizer import *
from .callback.core import *
import pickle,threading
from collections.abc import MutableSequence
# %% auto 0
__all__ = ['replacing_y... | 29,917 | 43.388724 | 155 | py |
fastai | fastai-master/fastai/_modidx.py | # Autogenerated by nbdev
d = { 'settings': { 'branch': 'master',
'doc_baseurl': '/',
'doc_host': 'https://docs.fast.ai',
'git_url': 'https://github.com/fastai/fastai',
'lib_path': 'fastai'},
'syms': { 'fastai.basics': {},
'fastai.callback.al... | 338,820 | 124.118538 | 196 | py |
fastai | fastai-master/fastai/collab.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/45_collab.ipynb.
# %% ../nbs/45_collab.ipynb 2
from __future__ import annotations
from .tabular.all import *
# %% auto 0
__all__ = ['TabularCollab', 'CollabDataLoaders', 'EmbeddingDotBias', 'EmbeddingNN', 'collab_learner']
# %% ../nbs/45_collab.ipynb 7
class Tabular... | 5,199 | 49.485437 | 221 | py |
fastai | fastai-master/fastai/interpret.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/20_interpret.ipynb.
# %% ../nbs/20_interpret.ipynb 2
from __future__ import annotations
from .data.all import *
from .optimizer import *
from .learner import *
from .tabular.core import *
import sklearn.metrics as skm
# %% auto 0
__all__ = ['plot_top_losses', 'Interp... | 7,769 | 43.913295 | 112 | py |
fastai | fastai-master/fastai/layers.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/01_layers.ipynb.
# %% ../nbs/01_layers.ipynb 2
from __future__ import annotations
from .imports import *
from .torch_imports import *
from .torch_core import *
from torch.nn.utils import weight_norm, spectral_norm
# %% auto 0
__all__ = ['NormType', 'inplace_relu', 'm... | 27,282 | 40.526636 | 127 | py |
fastai | fastai-master/fastai/_pytorch_doc.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/99_pytorch_doc.ipynb.
# %% ../nbs/99_pytorch_doc.ipynb 5
from __future__ import annotations
from types import ModuleType
# %% auto 0
__all__ = ['PYTORCH_URL', 'pytorch_doc_link']
# %% ../nbs/99_pytorch_doc.ipynb 6
PYTORCH_URL = 'https://pytorch.org/docs/stable/'
# ... | 1,573 | 32.489362 | 77 | py |
fastai | fastai-master/fastai/distributed.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/20a_distributed.ipynb.
# %% ../nbs/20a_distributed.ipynb 2
from __future__ import annotations
from .basics import *
from .callback.progress import ProgressCallback
from torch.nn.parallel import DistributedDataParallel, DataParallel
from .data.load import _FakeLoader,_... | 9,784 | 42.878924 | 144 | py |
fastai | fastai-master/fastai/metrics.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/13b_metrics.ipynb.
# %% ../nbs/13b_metrics.ipynb 1
from __future__ import annotations
from .data.all import *
from .optimizer import *
from .learner import *
# %% auto 0
__all__ = ['rmse', 'exp_rmspe', 'perplexity', 'AccumMetric', 'skm_to_fastai', 'optim_metric', 'ac... | 22,629 | 48.195652 | 130 | py |
fastai | fastai-master/fastai/_nbdev.py | # AUTOGENERATED BY NBDEV! DO NOT EDIT!
__all__ = ["index", "modules", "custom_doc_links", "git_url"]
index = {"defaults.benchmark": "00_torch_core.ipynb",
"setup_cuda": "00_torch_core.ipynb",
"subplots": "00_torch_core.ipynb",
"show_image": "00_torch_core.ipynb",
"show_titled_image... | 44,456 | 48.396667 | 74 | py |
fastai | fastai-master/fastai/fp16_utils.py | #Code directly taken from NVIDIA apex: https://github.com/NVIDIA/apex
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
class tofp16(nn.Module):
"""
Utility module that implements::
def forward(self, input)... | 6,957 | 37.230769 | 337 | py |
fastai | fastai-master/fastai/optimizer.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/12_optimizer.ipynb.
# %% ../nbs/12_optimizer.ipynb 2
from __future__ import annotations
from .torch_basics import *
# %% auto 0
__all__ = ['pytorch_hp_map', 'Optimizer', 'sgd_step', 'weight_decay', 'l2_reg', 'average_grad', 'average_sqr_grad',
'momentum_st... | 21,187 | 41.717742 | 139 | py |
fastai | fastai-master/fastai/test_utils.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/97_test_utils.ipynb.
# %% ../nbs/97_test_utils.ipynb 0
from __future__ import annotations
from .imports import *
from .data.all import *
from .optimizer import *
from .learner import *
from .callback.core import *
from torch.utils.data import TensorDataset
# %% auto ... | 6,033 | 35.131737 | 151 | py |
fastai | fastai-master/fastai/callback/hook.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/15_callback.hook.ipynb.
# %% ../../nbs/15_callback.hook.ipynb 1
from __future__ import annotations
from ..basics import *
# %% auto 0
__all__ = ['Hook', 'hook_output', 'Hooks', 'hook_outputs', 'dummy_eval', 'model_sizes', 'num_features_model', 'has_params',
... | 11,381 | 39.361702 | 142 | py |
fastai | fastai-master/fastai/callback/tracker.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/17_callback.tracker.ipynb.
# %% ../../nbs/17_callback.tracker.ipynb 2
from __future__ import annotations
from ..basics import *
from .progress import *
from .fp16 import MixedPrecision
# %% auto 0
__all__ = ['TerminateOnNaNCallback', 'TrackerCallback', 'EarlyStopp... | 7,720 | 54.15 | 148 | py |
fastai | fastai-master/fastai/callback/core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/13_callback.core.ipynb.
# %% ../../nbs/13_callback.core.ipynb 2
from __future__ import annotations
from ..data.all import *
from ..optimizer import *
from ..losses import BaseLoss
# %% auto 0
__all__ = ['Callback', 'TrainEvalCallback', 'GatherPredsCallback', 'Fetc... | 9,371 | 48.851064 | 180 | py |
fastai | fastai-master/fastai/callback/channelslast.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/18c_callback.channelslast.ipynb.
# %% ../../nbs/18c_callback.channelslast.ipynb 1
from __future__ import annotations
from ..basics import *
from .fp16 import MixedPrecision
from torch.cuda.amp import GradScaler
# %% auto 0
__all__ = ['ChannelsLast']
# %% ../../n... | 1,614 | 37.452381 | 102 | py |
fastai | fastai-master/fastai/callback/captum.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/70c_callback.captum.ipynb.
# %% ../../nbs/70c_callback.captum.ipynb 3
from __future__ import annotations
import tempfile
from ..basics import *
# %% auto 0
__all__ = ['CaptumInterpretation']
# %% ../../nbs/70c_callback.captum.ipynb 6
from ipykernel import jsonuti... | 5,807 | 49.947368 | 146 | py |
fastai | fastai-master/fastai/callback/tensorboard.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/70a_callback.tensorboard.ipynb.
# %% ../../nbs/70a_callback.tensorboard.ipynb 3
from __future__ import annotations
from ..basics import *
# %% auto 0
__all__ = ['TensorBoardBaseCallback', 'TensorBoardCallback', 'TensorBoardProjectorCallback', 'projector_word_embed... | 7,323 | 41.33526 | 121 | py |
fastai | fastai-master/fastai/callback/mixup.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/19_callback.mixup.ipynb.
# %% ../../nbs/19_callback.mixup.ipynb 2
from __future__ import annotations
from ..basics import *
from torch.distributions.beta import Beta
# %% auto 0
__all__ = ['reduce_loss', 'MixHandler', 'MixUp', 'CutMix']
# %% ../../nbs/19_callback... | 4,833 | 42.160714 | 114 | py |
fastai | fastai-master/fastai/callback/schedule.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/14_callback.schedule.ipynb.
# %% ../../nbs/14_callback.schedule.ipynb 2
from __future__ import annotations
from ..basics import *
from .tracker import SaveModelCallback
# %% auto 0
__all__ = ['annealer', 'sched_lin', 'sched_cos', 'sched_no', 'sched_exp', 'SchedLin... | 14,363 | 44.6 | 136 | py |
fastai | fastai-master/fastai/callback/fp16.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/18_callback.fp16.ipynb.
# %% ../../nbs/18_callback.fp16.ipynb 2
from __future__ import annotations
from ..basics import *
from .progress import *
from torch.cuda.amp import GradScaler,autocast
from torch.cuda.amp.grad_scaler import OptState
# %% auto 0
__all__ = ... | 10,319 | 46.33945 | 139 | py |
fastai | fastai-master/fastai/vision/core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/07_vision.core.ipynb.
# %% ../../nbs/07_vision.core.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
from PIL import Image
try: BILINEAR,NEAREST = Image.Resampling.BILINEAR,Image.Resampling.NEAREST
except AttributeE... | 11,701 | 36.993506 | 124 | py |
fastai | fastai-master/fastai/vision/widgets.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/09c_vision.widgets.ipynb.
# %% ../../nbs/09c_vision.widgets.ipynb 3
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
from .core import *
from fastcore.parallel import *
from ipywidgets import HBox,VBox,widgets,Button,Checkbox... | 5,186 | 40.830645 | 124 | py |
fastai | fastai-master/fastai/vision/augment.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/09_vision.augment.ipynb.
# %% ../../nbs/09_vision.augment.ipynb 3
from __future__ import annotations
from ..data.all import *
from .core import *
from .data import *
# %% auto 0
__all__ = ['TensorTypes', 'RandTransform', 'FlipItem', 'DihedralItem', 'CropPad', 'Ran... | 57,110 | 43.898585 | 134 | py |
fastai | fastai-master/fastai/vision/utils.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/09b_vision.utils.ipynb.
# %% ../../nbs/09b_vision.utils.ipynb 3
from __future__ import annotations
import uuid
from ..torch_basics import *
from ..data.all import *
from .core import *
from fastdownload import download_url
from pathlib import Path
# %% auto 0
__al... | 4,333 | 40.673077 | 128 | py |
fastai | fastai-master/fastai/vision/gan.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/24_vision.gan.ipynb.
# %% ../../nbs/24_vision.gan.ipynb 2
from __future__ import annotations
from ..basics import *
from .all import *
# %% auto 0
__all__ = ['GANModule', 'basic_critic', 'AddChannels', 'basic_generator', 'DenseResBlock', 'gan_critic', 'GANLoss',
... | 19,560 | 45.463183 | 150 | py |
fastai | fastai-master/fastai/vision/data.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/08_vision.data.ipynb.
# %% ../../nbs/08_vision.data.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
from .core import *
import types
# %% auto 0
__all__ = ['PointBlock', 'BBoxBlock', 'get_grid', 'clip_remove_empty',... | 11,758 | 52.45 | 137 | py |
fastai | fastai-master/fastai/vision/models/tvm.py | from torchvision.models import *
import types as _t
_g = globals()
for _k, _v in list(_g.items()):
if (
isinstance(_v, _t.ModuleType) and _v.__name__.startswith("torchvision.models")
) or (callable(_v) and _v.__module__ == "torchvision.models._api"):
del _g[_k]
del _k, _v, _g, _t
| 307 | 24.666667 | 86 | py |
fastai | fastai-master/fastai/vision/models/xresnet.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../../nbs/11_vision.models.xresnet.ipynb.
# %% ../../../nbs/11_vision.models.xresnet.ipynb 2
from __future__ import annotations
from ...torch_basics import *
try: from torchvision.models.utils import load_state_dict_from_url
except ModuleNotFoundError: from torch.hub impo... | 7,766 | 69.609091 | 156 | py |
fastai | fastai-master/fastai/vision/models/unet.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../../nbs/15a_vision.models.unet.ipynb.
# %% ../../../nbs/15a_vision.models.unet.ipynb 1
from __future__ import annotations
from ...torch_basics import *
from ...callback.hook import *
# %% auto 0
__all__ = ['UnetBlock', 'ResizeToOrig', 'DynamicUnet']
# %% ../../../nbs/... | 4,724 | 47.71134 | 118 | py |
fastai | fastai-master/fastai/tabular/core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/40_tabular.core.ipynb.
# %% ../../nbs/40_tabular.core.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
# %% auto 0
__all__ = ['make_date', 'add_datepart', 'add_elapsed_times', 'cont_cat_split', 'df_shrink_dtypes', 'd... | 16,968 | 43.075325 | 133 | py |
fastai | fastai-master/fastai/tabular/model.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/42_tabular.model.ipynb.
# %% ../../nbs/42_tabular.model.ipynb 1
from __future__ import annotations
from ..torch_basics import *
from .core import *
# %% auto 0
__all__ = ['emb_sz_rule', 'get_emb_sz', 'TabularModel', 'tabular_config']
# %% ../../nbs/42_tabular.mod... | 3,750 | 45.8875 | 128 | py |
fastai | fastai-master/fastai/tabular/data.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/41_tabular.data.ipynb.
# %% ../../nbs/41_tabular.data.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
from .core import *
# %% auto 0
__all__ = ['TabularDataLoaders']
# %% ../../nbs/41_tabular.data.ipynb 7
class Ta... | 2,768 | 45.932203 | 104 | py |
fastai | fastai-master/fastai/medical/imaging.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/60_medical.imaging.ipynb.
# %% ../../nbs/60_medical.imaging.ipynb 4
from __future__ import annotations
from ..basics import *
from ..vision.all import *
from ..data.transforms import *
import pydicom,kornia,skimage
from pydicom.dataset import Dataset as DcmDataset... | 15,588 | 36.92944 | 136 | py |
fastai | fastai-master/fastai/data/core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/03_data.core.ipynb.
# %% ../../nbs/03_data.core.ipynb 3
from __future__ import annotations
from ..torch_basics import *
from .load import *
# %% auto 0
__all__ = ['show_batch', 'show_results', 'TfmdDL', 'DataLoaders', 'FilteredBase', 'TfmdLists', 'decode_at', 'sho... | 24,537 | 44.609665 | 172 | py |
fastai | fastai-master/fastai/data/all.py | from ..torch_basics import *
from .core import *
from .load import *
from .external import *
from .transforms import *
from .block import *
| 140 | 19.142857 | 28 | py |
fastai | fastai-master/fastai/data/block.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/06_data.block.ipynb.
# %% ../../nbs/06_data.block.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from .core import *
from .load import *
from .external import *
from .transforms import *
# %% auto 0
__all__ = ['TransformBlock', 'CategoryBl... | 11,106 | 44.150407 | 147 | py |
fastai | fastai-master/fastai/data/external.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/04_data.external.ipynb.
# %% ../../nbs/04_data.external.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from fastdownload import FastDownload
from functools import lru_cache
import fastai.data
# %% auto 0
__all__ = ['fastai_cfg', 'fastai_pa... | 6,020 | 42.948905 | 118 | py |
fastai | fastai-master/fastai/data/load.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/02_data.load.ipynb.
# %% ../../nbs/02_data.load.ipynb 3
from __future__ import annotations
from ..torch_basics import *
from torch.utils.data.dataloader import _MultiProcessingDataLoaderIter,_SingleProcessDataLoaderIter,_DatasetKind
_loaders = (_MultiProcessingData... | 10,928 | 53.919598 | 282 | py |
fastai | fastai-master/fastai/data/transforms.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/05_data.transforms.ipynb.
# %% ../../nbs/05_data.transforms.ipynb 2
from __future__ import annotations
from ..torch_basics import *
from .core import *
from .load import *
from .external import *
from sklearn.model_selection import train_test_split
import posixpa... | 16,883 | 43.083551 | 147 | py |
fastai | fastai-master/fastai/text/core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/30_text.core.ipynb.
# %% ../../nbs/30_text.core.ipynb 1
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
# %% auto 0
__all__ = ['UNK', 'PAD', 'BOS', 'EOS', 'FLD', 'TK_REP', 'TK_WREP', 'TK_UP', 'TK_MAJ', 'WordTokenizer', 'fn_... | 17,521 | 45.110526 | 121 | py |
fastai | fastai-master/fastai/text/learner.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/37_text.learner.ipynb.
# %% ../../nbs/37_text.learner.ipynb 1
from __future__ import annotations
from ..basics import *
from .core import *
from .data import *
from .models.core import *
from .models.awdlstm import *
from ..callback.rnn import *
from ..callback.pro... | 13,867 | 44.618421 | 133 | py |
fastai | fastai-master/fastai/text/data.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../nbs/31_text.data.ipynb.
# %% ../../nbs/31_text.data.ipynb 1
from __future__ import annotations
from ..torch_basics import *
from ..data.all import *
from .core import *
# %% auto 0
__all__ = ['pad_input', 'reverse_text', 'make_vocab', 'TensorText', 'LMTensorText', 'Nu... | 14,582 | 49.811847 | 141 | py |
fastai | fastai-master/fastai/text/models/core.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../../nbs/33_text.models.core.ipynb.
# %% ../../../nbs/33_text.models.core.ipynb 1
from __future__ import annotations
from ...data.all import *
from ..core import *
from .awdlstm import *
# %% auto 0
__all__ = ['LinearDecoder', 'SequentialRNN', 'get_language_model', 'Sen... | 8,308 | 47.30814 | 113 | py |
fastai | fastai-master/fastai/text/models/awdlstm.py | # AUTOGENERATED! DO NOT EDIT! File to edit: ../../../nbs/32_text.models.awdlstm.ipynb.
# %% ../../../nbs/32_text.models.awdlstm.ipynb 1
from __future__ import annotations
from ...data.all import *
from ..core import *
# %% auto 0
__all__ = ['awd_lstm_lm_config', 'awd_lstm_clas_config', 'dropout_mask', 'RNNDropout', '... | 8,529 | 45.868132 | 131 | py |
fastai | fastai-master/dev_nbs/course/crappify.py | from fastai.basics import *
from PIL import Image, ImageDraw, ImageFont
def resize_to(img, targ_sz, use_min=False):
w,h = img.size
min_sz = (min if use_min else max)(w,h)
ratio = targ_sz/min_sz
return int(w*ratio),int(h*ratio)
class crappifier():
def __init__(self, path_lr, path_hr):
self.... | 859 | 33.4 | 109 | py |
fastai | fastai-master/nbs/dltest.py | from fastai.torch_basics import *
from fastai.data.load import *
class RandDL(DataLoader):
def create_item(self, s):
r = random.random()
return r if r<0.95 else stop()
if __name__ == "__main__":
# It can be reproduced in Linux by uncommenting this line
# multiprocessing.set_start_method('s... | 434 | 28 | 61 | py |
fastai | fastai-master/nbs/examples/train_imdbclassifier.py | from fastai.basics import *
from fastai.callback.all import *
from fastai.distributed import *
from fastprogress import fastprogress
from fastai.callback.mixup import *
from fastcore.script import *
from fastai.text.all import *
torch.backends.cudnn.benchmark = True
fastprogress.MAX_COLS = 80
def pr(s):
if rank_di... | 1,574 | 37.414634 | 109 | py |
fastai | fastai-master/nbs/examples/train_wt2.py | from fastai.basics import *
from fastai.text.all import *
from fastai.callback.all import *
from fastcore.script import *
def istitle(line):
return len(re.findall(r'^ = [^=]* = $', line)) != 0
def read_file(filename):
articles = L()
with open(filename, encoding='utf8') as f:
lines = f.readlines()
... | 2,024 | 42.085106 | 127 | py |
fastai | fastai-master/nbs/examples/dataloader_spawn.py | #!/usr/bin/env python
# coding: utf-8
from fastai.vision.all import *
def get_data(url, presize, resize):
path = untar_data(url)
#print(Normalize.from_stats(*imagenet_stats))
return DataBlock(
blocks=(ImageBlock, CategoryBlock), get_items=get_image_files,
splitter=GrandparentSplitter(vali... | 1,124 | 28.605263 | 76 | py |
fastai | fastai-master/nbs/examples/migrating_ignite.py | # The fastai DataLoader is a drop-in replacement for Pytorch's;
# no code changes are required other than changing the import line
from fastai.data.load import DataLoader
import torch
from torch import nn
from torch.optim import SGD
import torch.nn.functional as F
from torchvision.transforms import Compose, ToTensor,... | 3,837 | 39.829787 | 121 | py |
fastai | fastai-master/nbs/examples/migrating_catalyst.py | # The fastai DataLoader is a drop-in replacement for Pytorch's;
# no code changes are required other than changing the import line
from fastai.data.load import DataLoader
import os,torch
from torch.nn import functional as F
from catalyst import dl
from catalyst.data.cv import ToTensor
from catalyst.contrib.datasets i... | 1,319 | 34.675676 | 109 | py |
fastai | fastai-master/nbs/examples/mnist_items.py | from fastai.vision.all import *
items = get_image_files(untar_data(URLs.MNIST))
splits = GrandparentSplitter(train_name='training', valid_name='testing')(items)
tds = Datasets(items, [PILImageBW.create, [parent_label, Categorize()]], splits=splits)
if __name__ == '__main__':
data = tds.dataloaders(bs=256, after_i... | 442 | 35.916667 | 87 | py |
fastai | fastai-master/nbs/examples/migrating_fastai.py | from fastai.vision.all import *
from torchvision import datasets, transforms
class Net(nn.Sequential):
def __init__(self):
super().__init__(
nn.Conv2d(1, 32, 3, 1), nn.ReLU(),
nn.Conv2d(32, 64, 3, 1), nn.MaxPool2d(2), nn.Dropout2d(0.25),
Flatten(), nn.Linear(9216, 128), ... | 1,183 | 38.466667 | 87 | py |
fastai | fastai-master/nbs/examples/train_imagenette.py | from fastai.basics import *
from fastai.vision.all import *
from fastai.callback.all import *
from fastai.distributed import *
from fastprogress import fastprogress
from torchvision.models import *
from fastai.vision.models.xresnet import *
from fastai.callback.mixup import *
from fastcore.script import *
torch.backen... | 4,191 | 46.636364 | 117 | py |
fastai | fastai-master/nbs/examples/migrating_lightning.py | # The fastai DataLoader is a drop-in replacement for Pytorch's;
# no code changes are required other than changing the import line
from fastai.data.load import DataLoader
import os,torch
from torch.nn import functional as F
from torchvision.datasets import MNIST
from torchvision import transforms
from pytorch_lightni... | 1,622 | 35.066667 | 97 | py |
fastai | fastai-master/nbs/examples/distrib.py | from fastai.vision.all import *
from fastai.distributed import *
from fastai.vision.models.xresnet import *
path = rank0_first(untar_data, URLs.IMAGEWOOF_320)
dls = DataBlock(
blocks=(ImageBlock, CategoryBlock),
splitter=GrandparentSplitter(valid_name='val'),
get_items=get_image_files, get_y=parent_label,
... | 625 | 35.823529 | 86 | py |
fastai | fastai-master/nbs/examples/distrib_pytorch.py | from fastai.vision.all import *
from fastai.distributed import *
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
class Net(nn.Sequential):
def __init__(self):
super().__init__(
nn.Conv2d(1, 32, 3, 1), nn.ReLU(),
nn.Conv2d(32, 64, 3, 1), nn.MaxPoo... | 1,275 | 38.875 | 87 | py |
fastai | fastai-master/nbs/examples/migrating_pytorch.py | import torch
from torch import nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
class Flatten(nn.Module):
def forward(self, x): return x.view(x.size(0), -1)
class Net(nn.Sequential):
def __init__(self):
super().__init__(
... | 2,716 | 38.376812 | 81 | py |
fastai | fastai-master/nbs/examples/train_tabular.py | from fastai.basics import *
from fastai.tabular.all import *
from fastai.callback.all import *
from fastai.distributed import *
from fastprogress import fastprogress
from fastai.callback.mixup import *
from fastcore.script import *
torch.backends.cudnn.benchmark = True
fastprogress.MAX_COLS = 80
def pr(s):
if ran... | 1,471 | 32.454545 | 84 | py |
fastai | fastai-master/nbs/examples/mnist_blocks.py | from fastai.vision.all import *
splitter = GrandparentSplitter(train_name='training', valid_name='testing')
mnist = DataBlock(blocks=(ImageBlock(PILImageBW), CategoryBlock),
get_items=get_image_files, splitter=splitter, get_y=parent_label)
if __name__ == '__main__':
data = mnist.dataloaders(unta... | 425 | 34.5 | 83 | py |
FEMNIST_pytorch | FEMNIST_pytorch-master/femnist.py | from torchvision.datasets import MNIST, utils
from PIL import Image
import os.path
import torch
class FEMNIST(MNIST):
"""
This dataset is derived from the Leaf repository
(https://github.com/TalwalkarLab/leaf) pre-processing of the Extended MNIST
dataset, grouping examples by writer. Details about Lea... | 2,438 | 36.523077 | 110 | py |
LITE | LITE-main/src/tf_dataset_reader.py | import tensorflow as tf
import tensorflow_datasets as tfds
import torch
import torchvision.transforms as T
from PIL import Image
import numpy as np
class TfDatasetReader:
def __init__(self, dataset, task, context_batch_size, target_batch_size, path_to_datasets, image_size, device):
self.dataset = dataset
... | 6,764 | 38.104046 | 115 | py |
LITE | LITE-main/src/efficientnet_utils.py | """
The code in this file is substantially based on the code from "A PyTorch implementation of EfficientNet"
by lukemelas that can be found here: https://github.com/lukemelas/EfficientNet-PyTorch
"""
"""Helper functions for building the model and for loading model parameters.
These helper functions are built to mir... | 25,146 | 39.494364 | 130 | py |
LITE | LITE-main/src/set_encoder.py | import torch
import torch.nn as nn
"""
Classes and functions required for Set encoding in adaptation networks. Many of the ideas and classes here are
closely related to DeepSets (https://arxiv.org/abs/1703.06114).
"""
def mean_pooling(x):
return torch.mean(x, dim=0, keepdim=True)
class SetEncoder(nn.M... | 2,669 | 32.797468 | 115 | py |
LITE | LITE-main/src/features.py | import torch
import torch.nn as nn
from efficientnet import film_efficientnet, film_efficientnet_b0_84
def create_feature_extractor(args):
if args.image_size == 84:
feature_extractor = film_efficientnet_b0_84(args.pretrained_model_path)
else:
feature_extractor = film_efficientnet("efficientnet... | 6,618 | 38.634731 | 129 | py |
LITE | LITE-main/src/efficientnet.py | """
The code in this file is substantially based on the code from "A PyTorch implementation of EfficientNet"
by lukemelas that can be found here: https://github.com/lukemelas/EfficientNet-PyTorch
"""
"""Model and module class for EfficientNet.
They are built to mirror those in the official TensorFlow implementation... | 22,768 | 38.736475 | 144 | py |
LITE | LITE-main/src/utils.py | import os
import torch
import torch.nn.functional as F
import numpy as np
from enum import Enum
import sys
import math
class MetaLearningState(Enum):
META_TRAIN = 0
META_TEST = 1
class ValidationAccuracies:
"""
Determines if an evaluation on the validation set is better than the best so far.
In ... | 5,276 | 35.393103 | 136 | py |
LITE | LITE-main/src/model.py | import torch
import numpy as np
import torch.nn as nn
from config_networks import ConfigureNetworks
from mahalanonbis import MahalanobisPredictor
from set_encoder import mean_pooling
class FewShotClassifier(nn.Module):
def __init__(self, args, logger, device):
super(FewShotClassifier, self).__init__()
... | 6,282 | 51.798319 | 122 | py |
LITE | LITE-main/src/run.py | import torch
import numpy as np
import argparse
import os
from utils import Logger, LogFiles, ValidationAccuracies, cross_entropy_loss, compute_accuracy, MetaLearningState,\
shuffle
from model import FewShotClassifier
from dataset import get_dataset_reader
from tf_dataset_reader import TfDatasetReader
from image_fo... | 25,859 | 52.987474 | 126 | py |
LITE | LITE-main/src/mahalanonbis.py | import torch
"""
The code in this file is substantially based on the code for "Improved Few-Shot Visual Classification"
by Peyman Bateni, Raghav Goyal, Vaden Masrani1, Frank Wood, and Leonid Sigal
that can be found here: https://github.com/peymanbateni/simple-cnaps
"""
class MahalanobisPredictor:
def __init__(sel... | 4,701 | 46.02 | 118 | py |
LITE | LITE-main/src/image_folder_reader.py | import torch
from torchvision.datasets import ImageFolder
import torchvision.transforms as T
import numpy as np
class ImageFolderReader:
def __init__(self, path_to_images, context_batch_size, target_batch_size, image_size, device,
train_fraction=0.7, val_fraction=0.1, test=0.2):
self.devi... | 3,305 | 34.170213 | 114 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/main_molecules_graph_regression.py |
"""
IMPORTING LIBS
"""
import dgl
import numpy as np
import os
import socket
import time
import random
import glob
import argparse, json
import pickle
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from tensor... | 19,964 | 41.478723 | 202 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/main_TSP_edge_classification.py |
"""
IMPORTING LIBS
"""
import dgl
import numpy as np
import os
import socket
import time
import random
import glob
import argparse, json
import pickle
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from tensor... | 18,702 | 39.836245 | 202 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/main_TUs_graph_classification.py |
"""
IMPORTING LIBS
"""
import dgl
import numpy as np
import os
import socket
import time
import random
import glob
import argparse, json
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from tensorboardX import ... | 20,561 | 43.029979 | 202 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/main_superpixels_graph_classification.py |
"""
IMPORTING LIBS
"""
import dgl
import numpy as np
import os
import socket
import time
import random
import glob
import argparse, json
import pickle
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from tensor... | 18,866 | 41.113839 | 202 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/main_SBMs_node_classification.py |
"""
IMPORTING LIBS
"""
import dgl
import numpy as np
import os
import socket
import time
import random
import glob
import argparse, json
import pickle
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from tensor... | 19,778 | 40.552521 | 202 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/SBMs_node_classification/bi_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
import numpy as np
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.gcn_layer import ... | 4,566 | 34.96063 | 140 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/SBMs_node_classification/bi_gated_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
import numpy as np
"""
ResGatedGCN: Residual Gated Graph ConvNets
An Experimental Study of Neural Networks for Variable Graphs (Xavier Bresson and Thomas Laurent, ICLR 2018)
https://arxiv.org/pdf/1711.07553v2.pdf
"""
from layers... | 18,704 | 41.319005 | 147 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/SBMs_node_classification/gcn_net_for_Eval.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
import numpy as np
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.gcn_layer import ... | 2,684 | 33.87013 | 109 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/SBMs_node_classification/bi_gcn_net_for_Eval.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
import numpy as np
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.gcn_layer import ... | 4,752 | 35.007576 | 140 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/SBMs_node_classification/bi_graphsage_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GraphSAGE:
William L. Hamilton, Rex Ying, Jure Leskovec, Inductive Representation Learning on Large Graphs (NeurIPS 2017)
https://cs.stanford.edu/people/jure/pubs/graphsage-nips17.pdf
"""
from layers.graphsage_layer import... | 4,819 | 37.56 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/SBMs_node_classification/bi_gat_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GAT: Graph Attention Network
Graph Attention Networks (Veličković et al., ICLR 2018)
https://arxiv.org/abs/1710.10903
"""
from layers.gat_layer import GATLayer
from layers.bi_gat_layer import biGATLayer
from layers.mlp_reado... | 4,771 | 37.796748 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/superpixels_graph_classification/bi_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.gcn_layer import GCNLayer
from layer... | 4,128 | 41.132653 | 140 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/superpixels_graph_classification/bi_gated_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
ResGatedGCN: Residual Gated Graph ConvNets
An Experimental Study of Neural Networks for Variable Graphs (Xavier Bresson and Thomas Laurent, ICLR 2018)
https://arxiv.org/pdf/1711.07553v2.pdf
"""
from layers.gated_gcn_layer im... | 13,454 | 41.850318 | 149 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/superpixels_graph_classification/bi_graphsage_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GraphSAGE:
William L. Hamilton, Rex Ying, Jure Leskovec, Inductive Representation Learning on Large Graphs (NeurIPS 2017)
https://cs.stanford.edu/people/jure/pubs/graphsage-nips17.pdf
"""
from layers.graphsage_layer import... | 4,447 | 40.962264 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/superpixels_graph_classification/bi_gat_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl.function as fn
import dgl
"""
GAT: Graph Attention Network
Graph Attention Networks (Veličković et al., ICLR 2018)
https://arxiv.org/abs/1710.10903
"""
from layers.gat_layer import GATLayer
from layers.bi_gat_layer import biGATL... | 4,422 | 40.726415 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TUs_graph_classification/bi_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.gcn_layer import GCNLayer
from layer... | 4,137 | 40.79798 | 140 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TUs_graph_classification/bi_gated_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
ResGatedGCN: Residual Gated Graph ConvNets
An Experimental Study of Neural Networks for Variable Graphs (Xavier Bresson and Thomas Laurent, ICLR 2018)
https://arxiv.org/pdf/1711.07553v2.pdf
"""
from layers.gated_gcn_layer im... | 4,223 | 39.228571 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TUs_graph_classification/bi_graphsage_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GraphSAGE:
William L. Hamilton, Rex Ying, Jure Leskovec, Inductive Representation Learning on Large Graphs (NeurIPS 2017)
https://cs.stanford.edu/people/jure/pubs/graphsage-nips17.pdf
"""
from layers.graphsage_layer import... | 4,412 | 40.632075 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TUs_graph_classification/bi_gat_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GAT: Graph Attention Network
Graph Attention Networks (Veličković et al., ICLR 2018)
https://arxiv.org/abs/1710.10903
"""
from layers.gat_layer import CustomGATLayer as GATLayer
from layers.bi_gat_layer import biGATLayer
fro... | 4,427 | 41.171429 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TSP_edge_classification/bi_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.gcn_layer import GCNLayer
from layer... | 4,101 | 40.857143 | 140 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TSP_edge_classification/bi_gated_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
ResGatedGCN: Residual Gated Graph ConvNets
An Experimental Study of Neural Networks for Variable Graphs (Xavier Bresson and Thomas Laurent, ICLR 2018)
https://arxiv.org/pdf/1711.07553v2.pdf
"""
from layers.gated_gcn_layer im... | 14,061 | 41.741641 | 149 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TSP_edge_classification/bi_graphsage_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GraphSAGE:
William L. Hamilton, Rex Ying, Jure Leskovec, Inductive Representation Learning on Large Graphs (NeurIPS 2017)
https://cs.stanford.edu/people/jure/pubs/graphsage-nips17.pdf
"""
from layers.graphsage_layer import... | 4,353 | 40.865385 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/TSP_edge_classification/bi_gat_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GAT: Graph Attention Network
Graph Attention Networks (Veličković et al., ICLR 2018)
https://arxiv.org/abs/1710.10903
"""
from layers.gat_layer import CustomGATLayer as GATLayer
from layers.bi_gat_layer import biGATLayer
fro... | 4,856 | 40.161017 | 135 | py |
bi-MP-HyeokjinK | bi-MP-HyeokjinK/nets/molecules_graph_regression/bi_gcn_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import dgl
"""
GCN: Graph Convolutional Networks
Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
http://arxiv.org/abs/1609.02907
"""
from layers.bi_gcn_layer import biGCNLayer
from ... | 4,313 | 41.294118 | 135 | py |
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