Lint tests

tests/build/test_utils.py

@@ -31,8 +31,8 @@
 
 
 # Note: job_config dict gets modified during process_launch_training_args
-@pytest.fixture(scope="session")
-def job_config():
+@pytest.fixture(name="job_config", scope="session")
+def fixture_job_config():
     with open(HAPPY_PATH_DUMMY_CONFIG_PATH, "r", encoding="utf-8") as f:
         dummy_job_config_dict = json.load(f)
     return dummy_job_config_dict
@@ -50,35 +50,35 @@ def test_process_launch_training_args(job_config):
     assert str(model_args.torch_dtype) == "torch.bfloat16"
     assert data_args.dataset_text_field == "output"
     assert training_args.output_dir == "bloom-twitter"
-    assert tune_config == None
-    assert merge_model == False
+    assert tune_config is None
+    assert merge_model is False
 
 
 def test_process_launch_training_args_defaults(job_config):
     job_config_defaults = copy.deepcopy(job_config)
     assert "torch_dtype" not in job_config_defaults
-    assert job_config_defaults["use_flash_attn"] == False
+    assert job_config_defaults["use_flash_attn"] is False
     assert "save_strategy" not in job_config_defaults
     model_args, _, training_args, _, _ = process_launch_training_args(
         job_config_defaults
     )
     assert str(model_args.torch_dtype) == "torch.bfloat16"
-    assert model_args.use_flash_attn == False
+    assert model_args.use_flash_attn is False
     assert training_args.save_strategy.value == "epoch"
 
 
 def test_process_launch_training_args_peft_method(job_config):
     job_config_pt = copy.deepcopy(job_config)
     job_config_pt["peft_method"] = "pt"
     _, _, _, tune_config, merge_model = process_launch_training_args(job_config_pt)
-    assert type(tune_config) == PromptTuningConfig
-    assert merge_model == False
+    assert isinstance(tune_config, PromptTuningConfig)
+    assert merge_model is False
 
     job_config_lora = copy.deepcopy(job_config)
     job_config_lora["peft_method"] = "lora"
     _, _, _, tune_config, merge_model = process_launch_training_args(job_config_lora)
-    assert type(tune_config) == LoraConfig
-    assert merge_model == True
+    assert isinstance(tune_config, LoraConfig)
+    assert merge_model is True
 
 
 def test_process_accelerate_launch_args(job_config):
@@ -147,8 +147,8 @@ def test_process_accelerate_launch_custom_config_file(patch_path_exists):
     assert args.config_file == dummy_config_path
     assert args.num_processes is None
 
-    # When user passes custom fsdp config file and also `num_processes` as a param, use custom config and
-    # overwrite num_processes from config with param
+    # When user passes custom fsdp config file and also `num_processes` as a param,
+    # use custom config and overwrite num_processes from config with param
     temp_job_config = {"accelerate_launch_args": {"config_file": dummy_config_path}}
     args = process_accelerate_launch_args(temp_job_config)
     assert args.config_file == dummy_config_path

tests/test_sft_trainer.py

@@ -77,7 +77,7 @@ def test_helper_causal_lm_train_kwargs():
     )
 
     assert model_args.model_name_or_path == MODEL_NAME
-    assert model_args.use_flash_attn == False
+    assert model_args.use_flash_attn is False
     assert model_args.torch_dtype == "float32"
 
     assert data_args.training_data_path == TWITTER_COMPLAINTS_DATA
@@ -295,10 +295,10 @@ def _validate_training(tempdir, check_eval=False):
     assert any(x.startswith("checkpoint-") for x in os.listdir(tempdir))
     train_logs_file_path = "{}/training_logs.jsonl".format(tempdir)
     train_log_contents = ""
-    with open(train_logs_file_path) as f:
+    with open(train_logs_file_path, encoding="utf-8") as f:
         train_log_contents = f.read()
 
-    assert os.path.exists(train_logs_file_path) == True
+    assert os.path.exists(train_logs_file_path) is True
     assert os.path.getsize(train_logs_file_path) > 0
     assert "training_loss" in train_log_contents
 
@@ -311,7 +311,7 @@ def _get_checkpoint_path(dir_path):
 
 
 def _get_adapter_config(dir_path):
-    with open(os.path.join(dir_path, "adapter_config.json")) as f:
+    with open(os.path.join(dir_path, "adapter_config.json"), encoding="utf-8") as f:
         return json.load(f)
 
 

tests/utils/test_data_type_utils.py

@@ -32,7 +32,7 @@
 
 
 def test_str_to_torch_dtype():
-    for t in dtype_dict.keys():
+    for t in dtype_dict:
         assert data_type_utils.str_to_torch_dtype(t) == dtype_dict.get(t)
 
 
@@ -42,7 +42,7 @@ def test_str_to_torch_dtype_exit():
 
 
 def test_get_torch_dtype():
-    for t in dtype_dict.keys():
+    for t in dtype_dict:
         # When passed a string, it gets converted to torch.dtype
         assert data_type_utils.get_torch_dtype(t) == dtype_dict.get(t)
         # When passed a torch.dtype, we get the same torch.dtype returned

tox.ini

@@ -17,6 +17,7 @@ allowlist_externals = ./scripts/fmt.sh
 [testenv:lint]
 description = lint with pylint
 deps = pylint>=2.16.2,<=3.1.0
+        pytest
         -r requirements.txt
-commands = pylint tuning scripts/*.py build/*.py
+commands = pylint tuning scripts/*.py build/*.py tests
 allowlist_externals = pylint