Cut-out examples

.readthedocs.yml

@@ -16,4 +16,4 @@ formats: all
 python:
   version: 3.7
   install:
-    - requirements: docs/doc_requirements.txt
+    - requirements: docs/requirements.txt

.travis.yml

@@ -6,11 +6,12 @@ cache: pip
 install:
   - pip install -e .
   - pip install -r requirements.txt
+  - pip install -r tests/requirements.txt
   - pip install -U numpy
 
 # keep build from timing out
 dist: xenial
 
 # command to run tests
 script:
-  - py.test # or py.test for Python versions 3.5 and below
+  - py.test -v # or py.test for Python versions 3.5 and below

docs/doc_requirements.txt → docs/requirements.txt

@@ -1 +1,2 @@
 mkdocs-material==4.4.0
+mkdocs==1.0.4

pytorch_lightning/examples/new_project_templates/multi_node_cluster_template.py → examples/new_project_templates/multi_node_cluster_template.py

@@ -14,17 +14,7 @@
 torch.manual_seed(SEED)
 np.random.seed(SEED)
 
-# ---------------------
-# DEFINE MODEL HERE
-# ---------------------
-from lightning_module_template import LightningTemplateModel
-# ---------------------
-
-"""
-Allows training by using command line arguments
-Run by:
-# TYPE YOUR RUN COMMAND HERE
-"""
+from .lightning_module_template import LightningTemplateModel
 
 
 def main_local(hparams):

pytorch_lightning/examples/new_project_templates/single_cpu_template.py → examples/new_project_templates/single_cpu_template.py

@@ -13,7 +13,7 @@
 torch.manual_seed(SEED)
 np.random.seed(SEED)
 
-from lightning_module_template import LightningTemplateModel
+from .lightning_module_template import LightningTemplateModel
 
 
 def main(hparams):

pytorch_lightning/examples/new_project_templates/single_gpu_node_16bit_template.py → examples/new_project_templates/single_gpu_node_16bit_template.py

@@ -13,7 +13,7 @@
 torch.manual_seed(SEED)
 np.random.seed(SEED)
 
-from lightning_module_template import LightningTemplateModel
+from .lightning_module_template import LightningTemplateModel
 
 
 def main(hparams):

pytorch_lightning/examples/new_project_templates/single_gpu_node_ddp_template.py → examples/new_project_templates/single_gpu_node_ddp_template.py

@@ -13,7 +13,7 @@
 torch.manual_seed(SEED)
 np.random.seed(SEED)
 
-from lightning_module_template import LightningTemplateModel
+from .lightning_module_template import LightningTemplateModel
 
 
 def main(hparams):

pytorch_lightning/examples/new_project_templates/single_gpu_node_dp_template.py → examples/new_project_templates/single_gpu_node_dp_template.py

@@ -13,7 +13,7 @@
 torch.manual_seed(SEED)
 np.random.seed(SEED)
 
-from lightning_module_template import LightningTemplateModel
+from .lightning_module_template import LightningTemplateModel
 
 
 def main(hparams):

pytorch_lightning/examples/new_project_templates/trainer_cpu_template.py → examples/new_project_templates/trainer_cpu_template.py

@@ -3,9 +3,10 @@
 
 from test_tube import HyperOptArgumentParser, Experiment
 from pytorch_lightning.models.trainer import Trainer
-from pytorch_lightning.utils.arg_parse import add_default_args
+from pytorch_lightning.utilities.arg_parse import add_default_args
 from pytorch_lightning.callbacks.pt_callbacks import EarlyStopping, ModelCheckpoint
-from lightning_module_template import LightningTemplateModel
+
+from .lightning_module_template import LightningTemplateModel
 
 
 def main(hparams):

pytorch_lightning/callbacks/pt_callbacks.py

@@ -1,7 +1,9 @@
-import numpy as np
 import os
 import shutil
-from pytorch_lightning.pt_overrides.override_data_parallel import LightningDistributedDataParallel
+
+import numpy as np
+
+from ..pt_overrides.override_data_parallel import LightningDistributedDataParallel
 
 
 class Callback(object):
@@ -261,4 +263,3 @@ def on_epoch_end(self, epoch, logs=None):
         print(loss)
         if should_stop:
             break
-

pytorch_lightning/models/trainer.py

@@ -8,17 +8,17 @@
 import pdb
 import re
 
+import numpy as np
+import tqdm
 import torch
 from torch.utils.data.distributed import DistributedSampler
 import torch.multiprocessing as mp
 import torch.distributed as dist
-import numpy as np
-import tqdm
 
-from pytorch_lightning.root_module.memory import get_gpu_memory_map
-from pytorch_lightning.root_module.model_saving import TrainerIO
-from pytorch_lightning.pt_overrides.override_data_parallel import LightningDistributedDataParallel, LightningDataParallel
-from pytorch_lightning.utils.debugging import MisconfigurationException
+from ..root_module.memory import get_gpu_memory_map
+from ..root_module.model_saving import TrainerIO
+from ..pt_overrides.override_data_parallel import LightningDistributedDataParallel, LightningDataParallel
+from ..utilities.debugging import MisconfigurationException
 
 try:
     from apex import amp

pytorch_lightning/root_module/grads.py

@@ -1,9 +1,8 @@
-from torch import nn
-
 """
 Module to describe gradients
 """
 
+from torch import nn
 
 class GradInformation(nn.Module):
 

pytorch_lightning/root_module/memory.py

@@ -1,15 +1,15 @@
-import torch
+'''
+Generates a summary of a model's layers and dimensionality
+'''
+
 import gc
+
+import torch
 import subprocess
 import numpy as np
 import pandas as pd
 
 
-'''
-Generates a summary of a model's layers and dimensionality
-'''
-
-
 class ModelSummary(object):
 
     def __init__(self, model):

pytorch_lightning/root_module/model_saving.py

@@ -1,7 +1,9 @@
-import torch
 import os
 import re
-from pytorch_lightning.pt_overrides.override_data_parallel import LightningDistributedDataParallel, LightningDataParallel
+
+import torch
+
+from ..pt_overrides.override_data_parallel import LightningDistributedDataParallel, LightningDataParallel
 
 
 class ModelIO(object):

pytorch_lightning/root_module/root_module.py

@@ -1,9 +1,10 @@
 import torch
-from pytorch_lightning.root_module.memory import ModelSummary
-from pytorch_lightning.root_module.grads import GradInformation
-from pytorch_lightning.root_module.model_saving import ModelIO, load_hparams_from_tags_csv
-from pytorch_lightning.root_module.hooks import ModelHooks
-from pytorch_lightning.root_module.decorators import data_loader
+
+from .memory import ModelSummary
+from .grads import GradInformation
+from .model_saving import ModelIO, load_hparams_from_tags_csv
+from .hooks import ModelHooks
+from .decorators import data_loader
 
 
 class LightningModule(GradInformation, ModelIO, ModelHooks):

pytorch_lightning/testing_models/lm_test_module.py → pytorch_lightning/testing/lm_test_module.py

@@ -1,17 +1,18 @@
 import os
 from collections import OrderedDict
-import torch.nn as nn
-from torchvision.datasets import MNIST
-import torchvision.transforms as transforms
+
 import torch
+import torch.nn as nn
 import torch.nn.functional as F
-from test_tube import HyperOptArgumentParser
 from torch import optim
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
+from torchvision.datasets import MNIST
+from torchvision import transforms
+from test_tube import HyperOptArgumentParser
 
-from pytorch_lightning.root_module.root_module import LightningModule
-import pytorch_lightning as ptl
+from ..root_module.root_module import LightningModule
+from pytorch_lightning import data_loader
 
 
 class LightningTestModel(LightningModule):
@@ -214,15 +215,15 @@ def __dataloader(self, train):
 
         return loader
 
-    @ptl.data_loader
+    @data_loader
     def tng_dataloader(self):
         return self.__dataloader(train=True)
 
-    @ptl.data_loader
+    @data_loader
     def val_dataloader(self):
         return self.__dataloader(train=False)
 
-    @ptl.data_loader
+    @data_loader
     def test_dataloader(self):
         return self.__dataloader(train=False)
 

pytorch_lightning/utils/arg_parse.py → pytorch_lightning/utilities/arg_parse.py

@@ -1,4 +1,7 @@
-import pdb
+"""
+List of default args which mught be useful for all the available flags
+Might need to update with the new flags
+"""
 
 def add_default_args(parser, root_dir, rand_seed=None, possible_model_names=None):
 
@@ -73,4 +76,4 @@ def add_default_args(parser, root_dir, rand_seed=None, possible_model_names=None
     parser.add_argument('--local', dest='local', action='store_true', help='enables local tng')
 
     # optimizer
-    parser.add_argument('--lr_scheduler_milestones', default=None, type=str)
+    parser.add_argument('--lr_scheduler_milestones', default=None, type=str)

pytorch_lightning/utils/debugging.py → pytorch_lightning/utilities/debugging.py

@@ -1,5 +1,2 @@
-import pdb
-import sys
-
 class MisconfigurationException(Exception):
-    pass
+    pass

requirements.txt

@@ -1,6 +1,3 @@
-coverage==4.5.3
-mkdocs==1.0.4
-pytest==5.0.1
 scikit-learn==0.20.2
 tqdm==4.32.1
 twine==1.13.0

tests/debug.py

@@ -1,15 +1,10 @@
-import pytest
 from pytorch_lightning import Trainer
-from pytorch_lightning.examples.new_project_templates.lightning_module_template import LightningTemplateModel
+from examples import LightningTemplateModel
 from argparse import Namespace
 from test_tube import Experiment
 from pytorch_lightning.callbacks import ModelCheckpoint
-import numpy as np
-import warnings
-import torch
 import os
 import shutil
-import pdb
 
 import pytorch_lightning as ptl
 import torch

tests/requirements.txt

@@ -0,0 +1,2 @@
+coverage==4.5.3
+pytest==5.0.1

tests/test_models.py

@@ -1,20 +1,20 @@
+import os
+import shutil
+import warnings
+
 import pytest
+import numpy as np
+import torch
 from pytorch_lightning import Trainer
-from pytorch_lightning.examples.new_project_templates.lightning_module_template import LightningTemplateModel
-from pytorch_lightning.testing_models.lm_test_module import LightningTestModel
+from examples import LightningTemplateModel
+from pytorch_lightning.testing.lm_test_module import LightningTestModel
 from argparse import Namespace
 from test_tube import Experiment, SlurmCluster
 from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping
-from pytorch_lightning.utils.debugging import MisconfigurationException
+from pytorch_lightning.utilities.debugging import MisconfigurationException
 from pytorch_lightning.root_module import memory
 from pytorch_lightning.models.trainer import reduce_distributed_output
 from pytorch_lightning.root_module import model_saving
-import numpy as np
-import warnings
-import torch
-import os
-import shutil
-import pdb
 
 SEED = 2334
 torch.manual_seed(SEED)
@@ -232,8 +232,6 @@ def test_model_saving_loading():
     clear_save_dir()
 
 
-
-
 def test_model_freeze_unfreeze():
     hparams = get_hparams()
     model = LightningTestModel(hparams)