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https://github.com/zebrajr/pytorch.git
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014d1fe5c4
Summary: These are all essentially no-op changes which allow for nose-style (or pytest-style) test discovery. With this patch, you can use any of these methods to discover and run tests under `caffe2/python`: ``` python -m unittest discover -p '*test*.py' caffe2/python/ python -m nose caffe2/python/ python -m pytest caffe2/python/ ``` Future work: * Get all of the tests to pass * Some seem to be testing operations which don't have GPU implementations * I get a segfault unless I set `CUDA_VISIBLE_DEVICES=0` * Some tests are flaky * Allow test discovery throughout the whole project (e.g. the `experiments/` dir) Closes https://github.com/caffe2/caffe2/pull/199 Reviewed By: pietern Differential Revision: D4704504 Pulled By: Yangqing fbshipit-source-id: 8f5687ec9c8aa873dfaff30dbf44272bc38a206b
28 lines
896 B
Python
28 lines
896 B
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from caffe2.python.optimizer import build_sgd, build_ftrl, build_adagrad, build_adam
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from caffe2.python.optimizer_test_util import OptimizerTestBase
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from caffe2.python.test_util import TestCase
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class TestSgd(OptimizerTestBase, TestCase):
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def build_optimizer(self, model):
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build_sgd(model, base_learning_rate=0.1)
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class TestFtrl(OptimizerTestBase, TestCase):
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def build_optimizer(self, model):
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build_ftrl(
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model, engine=None, alpha=1.0, beta=0.1, lambda1=0.0, lambda2=0.0)
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class TestAdagrad(OptimizerTestBase, TestCase):
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def build_optimizer(self, model):
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build_adagrad(model, base_learning_rate=1.0)
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class TestAdam(OptimizerTestBase, TestCase):
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def build_optimizer(self, model):
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build_adam(model, base_learning_rate=0.1)
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