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()