diff options
Diffstat (limited to 'tensorflow/python/estimator/estimator_test.py')
| -rw-r--r-- | tensorflow/python/estimator/estimator_test.py | 68 |
1 files changed, 68 insertions, 0 deletions
diff --git a/tensorflow/python/estimator/estimator_test.py b/tensorflow/python/estimator/estimator_test.py index 733c7fb95d..8bc410ba0b 100644 --- a/tensorflow/python/estimator/estimator_test.py +++ b/tensorflow/python/estimator/estimator_test.py @@ -28,6 +28,7 @@ import six from google.protobuf import text_format +from tensorflow.core.protobuf import rewriter_config_pb2 from tensorflow.python.client import session from tensorflow.python.data.ops import dataset_ops from tensorflow.python.estimator import estimator @@ -38,6 +39,7 @@ from tensorflow.python.estimator.export import export_output from tensorflow.python.estimator.inputs import numpy_io from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes +from tensorflow.python.framework import errors from tensorflow.python.framework import ops from tensorflow.python.framework import tensor_util from tensorflow.python.framework import test_util @@ -202,6 +204,10 @@ class EstimatorConstructorTest(test.TestCase): est = estimator.Estimator(model_fn=model_fn) self.assertTrue(isinstance(est.config, run_config.RunConfig)) + self.assertTrue(est._session_config.allow_soft_placement) + rewrite_options = est._session_config.graph_options.rewrite_options + self.assertEqual(rewrite_options.meta_optimizer_iterations, + rewriter_config_pb2.RewriterConfig.ONE) def test_default_model_dir(self): @@ -1296,6 +1302,31 @@ class EstimatorEvaluateTest(test.TestCase): dummy_input_fn, steps=1, checkpoint_path=est1.latest_checkpoint()) self.assertEqual(5, scores['global_step']) + def test_wrong_shape_throws_reasonable_error(self): + """Make sure we are helpful when model_fns change. See b/110263146.""" + def _get_model_fn(val=1): + def _model_fn(features, labels, mode): + del features, labels # unused + variables.Variable(val, name='weight') + return model_fn_lib.EstimatorSpec( + mode=mode, + predictions=constant_op.constant([[1.]]), + loss=constant_op.constant(0.), + train_op=state_ops.assign_add(training.get_global_step(), 1)) + return _model_fn + + model_fn_1 = _get_model_fn() + model_fn_2 = _get_model_fn(val=[1]) + + est1 = estimator.Estimator(model_fn=model_fn_1) + est1.train(dummy_input_fn, steps=5) + est2 = estimator.Estimator( + model_fn=model_fn_2, model_dir=est1.model_dir) + + expected_msg = 'Restoring from checkpoint failed.*a mismatch between' + with self.assertRaisesRegexp(errors.InvalidArgumentError, expected_msg): + est2.train(dummy_input_fn, steps=1,) + def test_scaffold_is_used(self): def _model_fn_scaffold(features, labels, mode): @@ -2278,6 +2309,43 @@ class EstimatorExportTest(test.TestCase): with self.assertRaisesRegexp(ValueError, err_regex): est._export_all_saved_models(export_dir_base, input_receiver_fn_map) + def test_export_all_saved_models_metric_operation(self): + """Ensures metrics ops.Operations can be expoerted (b/109740581).""" + + def _model_fn(features, labels, mode): + del features, labels # Unused + metrics = {'metrics': (constant_op.constant([0]), + control_flow_ops.no_op())} + return model_fn_lib.EstimatorSpec( + mode, + predictions=constant_op.constant(10.), + loss=constant_op.constant(1.), + train_op=state_ops.assign_add(training.get_global_step(), 1), + eval_metric_ops=metrics) + + tmpdir = tempfile.mkdtemp() + est = estimator.Estimator(model_fn=_model_fn) + est.train(input_fn=dummy_input_fn, steps=1) + + # Perform the export. + export_dir_base = os.path.join( + compat.as_bytes(tmpdir), compat.as_bytes('metric_operation_export')) + + input_receiver_fn_map = { + model_fn_lib.ModeKeys.EVAL: _get_supervised_input_receiver_fn()} + + export_dir = est._export_all_saved_models( + export_dir_base, input_receiver_fn_map) + + # Restore, to validate that the export was well-formed. + with ops.Graph().as_default() as graph: + with session.Session(graph=graph) as sess: + meta_graph = loader.load(sess, [tag_constants.EVAL], export_dir) + sig_outputs = meta_graph.signature_def[ + model_fn_lib.ModeKeys.EVAL].outputs + self.assertEqual( + sig_outputs['metrics/update_op'].name, 'metric_op_wrapper:0') + def test_export_savedmodel_with_saveables_proto_roundtrip(self): tmpdir = tempfile.mkdtemp() est = estimator.Estimator( |