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f93e0619f3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/20180 Adding ShufflenetV2 (by Ma et. al. 2018) to the caffe2's benchmark suite. To run, use: `buck run mode/opt caffe2/caffe2/python/examples:imagenet_trainer -- --train_data null --batch_size 128 --epoch_size 3200 --num_epochs 2 --num_gpus 2 --model shufflenet` Reviewed By: bddppq, xw285cornell Differential Revision: D15094282 fbshipit-source-id: 0e1ce9c5975868e917b0f179e2c5b15647a76b4e
62 lines
2.0 KiB
Python
62 lines
2.0 KiB
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 __future__ import unicode_literals
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import numpy as np
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import caffe2.python.models.resnet as resnet
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import hypothesis.strategies as st
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from hypothesis import given, settings
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import caffe2.python.hypothesis_test_util as hu
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import caffe2.python.models.imagenet_trainer_test_utils as utils
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class ResnetMemongerTest(hu.HypothesisTestCase):
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@given(with_shapes=st.booleans(), **hu.gcs_cpu_only)
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@settings(max_examples=2, timeout=120)
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def test_resnet_shared_grads(self, with_shapes, gc, dc):
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results = utils.test_shared_grads(
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with_shapes,
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resnet.create_resnet50,
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'gpu_0/conv1_w',
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'gpu_0/last_out_L1000'
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)
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self.assertTrue(results[0][0] < results[0][1])
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np.testing.assert_almost_equal(results[1][0], results[1][1])
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np.testing.assert_almost_equal(results[2][0], results[2][1])
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def test_resnet_forward_only(self):
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results = utils.test_forward_only(
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resnet.create_resnet50,
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'gpu_0/last_out_L1000'
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)
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self.assertTrue(results[0][0] < results[0][1])
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self.assertTrue(results[1] < 7 and results[1] > 0)
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np.testing.assert_almost_equal(results[2][0], results[2][1])
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def test_resnet_forward_only_fast_simplenet(self):
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'''
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Test C++ memonger that is only for simple nets
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'''
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results = utils.test_forward_only_fast_simplenet(
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resnet.create_resnet50,
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'gpu_0/last_out_L1000'
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)
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self.assertTrue(results[0][0] < results[0][1])
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self.assertTrue(results[1] < 4 and results[1] > 0)
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np.testing.assert_almost_equal(results[2][0], results[2][1])
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if __name__ == "__main__":
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import unittest
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import random
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random.seed(2603)
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workspace.GlobalInit([
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'caffe2',
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'--caffe2_log_level=0',
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'--caffe2_print_blob_sizes_at_exit=0',
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'--caffe2_gpu_memory_tracking=1'])
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unittest.main()
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