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https://github.com/zebrajr/pytorch.git
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f0dd96c116
Summary: It turned out that we can not run PackedFC on a machine that does not have avx2 right now, as there is an known issue with MKL 2017.0.098 that produces wrong results on non-avx2 machines. I just moved this test from here because this is not the purpose of this test Reviewed By: salexspb Differential Revision: D4974021 fbshipit-source-id: c5b82a41021defc9946a8219f59b28abb13d3beb
117 lines
3.4 KiB
Python
117 lines
3.4 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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from caffe2.python import workspace, brew
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from caffe2.python.model_helper import ModelHelper
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import unittest
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import numpy as np
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class BrewTest(unittest.TestCase):
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def setUp(self):
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def myhelper(model, val=-1):
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return val
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if not brew.has_helper(myhelper):
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brew.Register(myhelper)
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self.myhelper = myhelper
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def myhelper2(model, val=-1):
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return val
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if not brew.has_helper(myhelper2):
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brew.Register(myhelper2)
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self.myhelper2 = myhelper2
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def test_dropout(self):
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p = 0.2
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X = np.ones((100, 100)).astype(np.float32) - p
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workspace.FeedBlob("x", X)
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model = ModelHelper(name="test_model")
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brew.dropout(model, "x", "out")
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workspace.RunNetOnce(model.param_init_net)
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workspace.RunNetOnce(model.net)
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out = workspace.FetchBlob("out")
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self.assertLess(abs(out.mean() - (1 - p)), 0.05)
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def test_fc(self):
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m, n, k = (15, 15, 15)
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X = np.random.rand(m, k).astype(np.float32) - 0.5
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workspace.FeedBlob("x", X)
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model = ModelHelper(name="test_model")
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brew.fc(model, "x", "out_1", k, n)
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workspace.RunNetOnce(model.param_init_net)
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workspace.RunNetOnce(model.net)
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def test_arg_scope(self):
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myhelper = self.myhelper
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myhelper2 = self.myhelper2
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n = 15
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with brew.arg_scope([myhelper], val=n):
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res = brew.myhelper(None)
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self.assertEqual(n, res)
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with brew.arg_scope([myhelper, myhelper2], val=n):
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res1 = brew.myhelper(None)
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res2 = brew.myhelper2(None)
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self.assertEqual([n, n], [res1, res2])
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def test_arg_scope_single(self):
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X = np.random.rand(64, 3, 32, 32).astype(np.float32) - 0.5
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workspace.FeedBlob("x", X)
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model = ModelHelper(name="test_model")
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with brew.arg_scope(
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brew.conv,
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stride=2,
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pad=2,
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weight_init=('XavierFill', {}),
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bias_init=('ConstantFill', {})
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):
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brew.conv(
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model=model,
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blob_in="x",
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blob_out="out",
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dim_in=3,
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dim_out=64,
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kernel=3,
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)
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workspace.RunNetOnce(model.param_init_net)
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workspace.RunNetOnce(model.net)
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out = workspace.FetchBlob("out")
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self.assertEqual(out.shape, (64, 64, 17, 17))
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def test_arg_scope_nested(self):
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myhelper = self.myhelper
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n = 16
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with brew.arg_scope([myhelper], val=-3), \
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brew.arg_scope([myhelper], val=-2):
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with brew.arg_scope([myhelper], val=n):
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res = brew.myhelper(None)
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self.assertEqual(n, res)
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res = brew.myhelper(None)
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self.assertEqual(res, -2)
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res = brew.myhelper(None, val=15)
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self.assertEqual(res, 15)
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def test_double_register(self):
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myhelper = self.myhelper
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with self.assertRaises(AttributeError):
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brew.Register(myhelper)
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def test_has_helper(self):
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self.assertTrue(brew.has_helper(brew.conv))
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self.assertTrue(brew.has_helper("conv"))
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def myhelper3():
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pass
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self.assertFalse(brew.has_helper(myhelper3))
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