lightning/tests/helpers/test_datasets.py

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2020-10-13 11:18:07 +00:00
# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import pickle
import cloudpickle
import pytest
from tests import PATH_DATASETS
from tests.helpers.datasets import AverageDataset, MNIST, TrialMNIST
Add PyTorch 1.8 Profiler 5/5 (#6618) * Refactor profilers * Update PassThrough * WIP - This is broken and will change * Update pytorch_lightning/profiler/pytorch.py Co-authored-by: thomas chaton <thomas@grid.ai> * resolve tests * resolve tests * find output * try something * update * add support for test and predict * update * update * use getattr * test * test * update * tests * update * update * update * update * update * remove file * update * update * update * update * update * test * update# * update * update tests * update * add suport for 1.8 * rename records * add support for 1.8 * update * resolve flake8 * resolve test * Refactor basic profilers * Fixes * Unused import * Introduce setup * Profile on all ranks. Print to stdout on 0 * Introduce dirpath + filename * CHANGELOG * Add tests. Address comments * add `on_run_stage_setup` * add on_run_stage_setup function * update * add test for RegisterRecordFunction * update lightnng flow direction * move variable to private * remove trace * Undo code that should be in 3/4 * Multi-stage multi-rank * 2/5 changes * Pass stage in __del__ * Remove TODOs * Describe on_evaluation_end. Add tests * Typo * Address comments * deepcopy tests * Advanced teardown * Fix teardown test * Fix tests * Minor change * Update CHANGELOG.md * Fix test * Quick fixes * Fix 6522 * resolve ddp tests * resolve tests * resolve some tests * update tests * resolve tests * update * resolve tests * resolve some tests * Missed fixes from 3/5 * Fixes * resolve some tests * resolve test for 1.7.1 * Broken refactor * Missed stage * Minor changes * resolve tests * Update CHANGELOG * resolve bug * remove print * Typo * Cleanup * resolve ddp test * remove barrier * update profiler * update * Smaller model * update * resolve tests * update * Minor changes. CHANGELOG * Minimize diff * update to 1.8.1 * RunIf. Extra code. Check segfault * resolve tests * Typo. Bad merge * Fixing a bad merge * replace for kineto * Update pytorch_lightning/profiler/pytorch.py Co-authored-by: ananthsub <ananth.subramaniam@gmail.com> * Update pytorch_lightning/profiler/pytorch.py Co-authored-by: ananthsub <ananth.subramaniam@gmail.com> * Minor changes * Bad merge * Use lists for flexibility * Use sets * predict_step * Ananth's suggestion * update * Docs * Update pl_examples/basic_examples/profiler_example.py Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * update example * update example Co-authored-by: Carlos Mocholi <carlossmocholi@gmail.com> Co-authored-by: ananthsub <ananth.subramaniam@gmail.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
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@pytest.mark.parametrize(
'dataset_cls,args', [
(MNIST, dict(root=PATH_DATASETS)),
(TrialMNIST, dict(root=PATH_DATASETS)),
(AverageDataset, dict()),
]
)
def test_pickling_dataset_mnist(tmpdir, dataset_cls, args):
mnist = dataset_cls(**args)
mnist_pickled = pickle.dumps(mnist)
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pickle.loads(mnist_pickled)
# assert vars(mnist) == vars(mnist_loaded)
mnist_pickled = cloudpickle.dumps(mnist)
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cloudpickle.loads(mnist_pickled)
# assert vars(mnist) == vars(mnist_loaded)