def _make_plan(self): p = plan.EvalPlan() p.compiler = block_compiler.Compiler.create(blocks.Scalar()) temp_dir = self.get_temp_dir() p.logdir = os.path.join(temp_dir, 'eval') p.logdir_restore = os.path.join(temp_dir, 'train') p.examples = [2, 4] p.print_file = six.StringIO() p.losses['loss'] = p.compiler.output_tensors[0] p.metrics['foo'] = tf.constant(42.0) p.finalize_stats() return p
def test_assert_runnable(self):
p = plan.EvalPlan()
self.assertRaisesWithLiteralMatch(
ValueError, 'compiler is required', p.assert_runnable)
p.compiler = block_compiler.Compiler.create(blocks.Scalar())
p.logdir = '/tmp/'
self.assertRaisesWithLiteralMatch(
ValueError, 'examples is required', p.assert_runnable)
p.examples = xrange(5)
self.assertRaisesWithLiteralMatch(
ValueError, 'at least one loss is required', p.assert_runnable)
p.losses['foo'] = tf.constant(42.0)
p.finalize_stats()
self.assertRaisesWithLiteralMatch(
ValueError, 'logdir_restore is required', p.assert_runnable)
p.logdir_restore = '/tmp/foo/'
p.assert_runnable()