!24805 fix_fronted_ut

Merge pull request !24805 from wanyiming/fix_uts

tests/ut/python/metrics/test_occlusion_sensitivity.py

@@ -15,10 +15,10 @@
 """test_occlusion_sensitivity"""
 import pytest
 import numpy as np
-from mindspore import nn
+from mindspore import nn, context
 from mindspore.common.tensor import Tensor
 from mindspore.nn.metrics import OcclusionSensitivity
-
+context.set_context(mode=context.GRAPH_MODE)
 
 class DenseNet(nn.Cell):
     def __init__(self):

tests/ut/python/model/test_mix_precision.py

@@ -96,6 +96,7 @@ def test_on_momentum():
 
 def test_data_parallel_with_cast():
     """test_data_parallel_with_cast"""
+    context.set_context(device_target='Ascend')
     context.reset_auto_parallel_context()
     context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, gradients_mean=True, device_num=8)
     predict = Tensor(np.ones([1, 1, 32, 32]).astype(np.float32) * 0.01)

tests/ut/python/optimizer/test_auto_grad.py

@@ -281,6 +281,7 @@ def test_same_primal_used_by_multi_j():
 
 
 def test_same_primal_used_by_multi_j_with_monad1():
+    context.set_context(mode=context.GRAPH_MODE)
     class AdamNet(nn.Cell):
         def __init__(self, var, m, v):
             super(AdamNet, self).__init__()
@@ -322,6 +323,7 @@ def test_same_primal_used_by_multi_j_with_monad1():
 
 
 def test_same_primal_used_by_multi_j_with_monad2():
+    context.set_context(mode=context.GRAPH_MODE)
     class AdamNet(nn.Cell):
         def __init__(self, var, m, v):
             super(AdamNet, self).__init__()

tests/ut/python/optimizer/test_optimizer_with_loss_scale.py

@@ -194,6 +194,7 @@ def test_compile_f16_model_train():
 
 
 def test_compile_f16_model_train_fixed():
+    context.set_context(device_target='Ascend')
     dataset_types = (np.float32, np.float32)
     dataset_shapes = ((16, 16), (16, 16))
 

tests/ut/python/test_log.py

@@ -54,6 +54,7 @@ def test_log_setlevel():
     from mindspore import log as logger
     # logger_instance = logger._get_logger()
     # del logger_instance
+    _clear_logger(logger)
     loglevel = logger.get_level()
     log_str = 'print debug informations'
     logger.debug("5 test log message debug:%s", log_str)

tests/ut/python/train/test_amp.py

@@ -147,6 +147,7 @@ def test_compile_model_train_O2():
 def test_compile_model_train_O2_parallel():
     dataset_types = (np.float32, np.float32)
     dataset_shapes = ((16, 16), (16, 16))
+    context.set_context(device_target='Ascend')
     context.set_auto_parallel_context(
         global_rank=0, device_num=8,
         gradients_mean=True, parameter_broadcast=True,

tests/ut/python/train/test_dataset_helper.py

@@ -89,10 +89,10 @@ def test_dataset_iter_ge():
 
 @pytest.mark.skipif('context.get_context("enable_ge")')
 def test_dataset_iter_ms_loop_sink():
+    context.set_context(device_target='Ascend', mode=context.GRAPH_MODE)
     GlobalComm.CHECK_ENVS = False
     init("hccl")
     GlobalComm.CHECK_ENVS = True
-    context.set_context(enable_loop_sink=True)
     dataset = get_dataset(32)
     dataset_helper = DatasetHelper(dataset, dataset_sink_mode=True, sink_size=10)
     count = 0
@@ -105,9 +105,9 @@ def test_dataset_iter_ms_loop_sink():
 
 @pytest.mark.skipif('context.get_context("enable_ge")')
 def test_dataset_iter_ms():
+    context.set_context(device_target='Ascend', mode=context.GRAPH_MODE)
     GlobalComm.CHECK_ENVS = False
     init("hccl")
     GlobalComm.CHECK_ENVS = True
-    context.set_context(enable_loop_sink=False)
     dataset = get_dataset(32)
     DatasetHelper(dataset, dataset_sink_mode=True, sink_size=10)

tests/ut/python/train/test_training.py

@@ -112,6 +112,7 @@ def test_multiple_argument():
 
 def test_train_feed_mode(test_with_simu):
     """ test_train_feed_mode """
+    context.set_context(mode=context.GRAPH_MODE)
     dataset = get_dataset()
     model = get_model()
     if test_with_simu:
@@ -162,6 +163,7 @@ class TestGraphMode:
 
     def test_train_minddata_graph_mode(self, test_with_simu):
         """ test_train_minddata_graph_mode """
+        context.set_context(mode=context.GRAPH_MODE)
         # pylint: disable=unused-argument
         dataset_types = (np.float32, np.float32)
         dataset_shapes = ((32, 3, 224, 224), (32, 3))
@@ -193,6 +195,7 @@ class CallbackTest(Callback):
 
 def test_train_callback(test_with_simu):
     """ test_train_callback """
+    context.set_context(mode=context.GRAPH_MODE)
     dataset = get_dataset()
     model = get_model()
     callback = CallbackTest()

tests/ut/python/utils/test_callback.py

@@ -88,33 +88,6 @@ def test_model_checkpoint_prefix_invalid():
     ModelCheckpoint(prefix="ckpt_2", directory="./test_files")
 
 
-def test_save_checkpoint():
-    """Test save checkpoint."""
-    train_config = CheckpointConfig(
-        save_checkpoint_steps=16,
-        save_checkpoint_seconds=0,
-        keep_checkpoint_max=5,
-        keep_checkpoint_per_n_minutes=0)
-    cb_params = _InternalCallbackParam()
-    net = Net()
-    loss = nn.SoftmaxCrossEntropyWithLogits()
-    optim = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
-    network_ = WithLossCell(net, loss)
-    _train_network = TrainOneStepCell(network_, optim)
-    cb_params.train_network = _train_network
-    cb_params.epoch_num = 10
-    cb_params.cur_epoch_num = 5
-    cb_params.cur_step_num = 0
-    cb_params.batch_num = 32
-    ckpoint_cb = ModelCheckpoint(prefix="test_ckpt", directory='./test_files', config=train_config)
-    run_context = RunContext(cb_params)
-    ckpoint_cb.begin(run_context)
-    ckpoint_cb.step_end(run_context)
-    if os.path.exists('./test_files/test_ckpt-model.pkl'):
-        os.chmod('./test_files/test_ckpt-model.pkl', stat.S_IWRITE)
-        os.remove('./test_files/test_ckpt-model.pkl')
-
-
 def test_loss_monitor_sink_mode():
     """Test loss monitor sink mode."""
     cb_params = _InternalCallbackParam()
@@ -153,8 +126,35 @@ def test_loss_monitor_normal_mode():
     loss_cb.end(run_context)
 
 
-def test_chg_ckpt_file_name_if_same_exist():
-    """Test chg ckpt file name if same exist."""
+def test_save_ckpt_and_test_chg_ckpt_file_name_if_same_exist():
+    """
+    Feature: Save checkpoint and check if there is a file with the same name.
+    Description: Save checkpoint and check if there is a file with the same name.
+    Expectation: Checkpoint is saved and checking is successful.
+    """
+    train_config = CheckpointConfig(
+        save_checkpoint_steps=16,
+        save_checkpoint_seconds=0,
+        keep_checkpoint_max=5,
+        keep_checkpoint_per_n_minutes=0)
+    cb_params = _InternalCallbackParam()
+    net = Net()
+    loss = nn.SoftmaxCrossEntropyWithLogits()
+    optim = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
+    network_ = WithLossCell(net, loss)
+    _train_network = TrainOneStepCell(network_, optim)
+    cb_params.train_network = _train_network
+    cb_params.epoch_num = 10
+    cb_params.cur_epoch_num = 5
+    cb_params.cur_step_num = 0
+    cb_params.batch_num = 32
+    ckpoint_cb = ModelCheckpoint(prefix="test_ckpt", directory='./test_files', config=train_config)
+    run_context = RunContext(cb_params)
+    ckpoint_cb.begin(run_context)
+    ckpoint_cb.step_end(run_context)
+    if os.path.exists('./test_files/test_ckpt-model.pkl'):
+        os.chmod('./test_files/test_ckpt-model.pkl', stat.S_IWRITE)
+        os.remove('./test_files/test_ckpt-model.pkl')
     _chg_ckpt_file_name_if_same_exist(directory="./test_files", prefix="ckpt")
 
 

tests/ut/python/utils/test_serialize.py

@@ -122,8 +122,23 @@ def test_save_checkpoint_for_list():
     save_checkpoint(parameter_list, ckpt_file_name)
 
 
-def test_save_checkpoint_for_list_append_info():
-    """ test save_checkpoint for list append info"""
+def test_load_checkpoint_error_filename():
+    """
+    Feature: Load checkpoint.
+    Description: Load checkpoint with error filename.
+    Expectation: Raise value error for error filename.
+    """
+    ckpt_file_name = 1
+    with pytest.raises(ValueError):
+        load_checkpoint(ckpt_file_name)
+
+
+def test_save_checkpoint_for_list_append_info_and_load_checkpoint():
+    """
+    Feature: Save checkpoint for list append info and load checkpoint.
+    Description: Save checkpoint for list append info and load checkpoint with list append info.
+    Expectation: Checkpoint for list append info can be saved and reloaded.
+    """
     parameter_list = []
     one_param = {}
     param1 = {}
@@ -144,16 +159,6 @@ def test_save_checkpoint_for_list_append_info():
 
     ckpt_file_name = os.path.join(_cur_dir, './parameters.ckpt')
     save_checkpoint(parameter_list, ckpt_file_name, append_dict=append_dict)
-
-
-def test_load_checkpoint_error_filename():
-    ckpt_file_name = 1
-    with pytest.raises(ValueError):
-        load_checkpoint(ckpt_file_name)
-
-
-def test_load_checkpoint():
-    ckpt_file_name = os.path.join(_cur_dir, './parameters.ckpt')
     par_dict = load_checkpoint(ckpt_file_name)
 
     assert len(par_dict) == 6