fix validation

Author: neph1

tabs/tab.py

@@ -2,7 +2,6 @@
 from typing import OrderedDict
 import gradio as gr
 import yaml
-import editor_factory
 
 class Tab(ABC):
 

test/test_trainer_config_validator.py

@@ -7,7 +7,7 @@
 @pytest.fixture
 def valid_config():
     return {
-        'finetrainers_path': '/path/to/finetrainers',
+        'path_to_finetrainers': '/path/to/finetrainers',
         'accelerate_config': 'config1',
         'batch_size': 32,
         'beta1': 0.9,
@@ -17,7 +17,7 @@ def valid_config():
         'checkpointing_limit': 5,
         'checkpointing_steps': 1000,
         'data_root': '/path/to/data',
-        'dataloader_num_workers': 4,
+        'dataloader_num_workers': 0,
         'epsilon': 1e-8,
         'gpu_ids': '0,1',
         'gradient_accumulation_steps': 2,
@@ -34,7 +34,7 @@ def valid_config():
         'nccl_timeout': 60,
         'optimizer': 'adam',
         'pretrained_model_name_or_path': 'pretrained_model',
-        'rank': 0,
+        'rank': 64,
         'seed': 42,
         'target_modules': 'module1',
         'tracker_name': 'tracker',
@@ -55,56 +55,6 @@ def test_valid_config(valid_config):
     with patch('os.path.isfile', return_value=True), patch('os.path.exists', return_value=True), patch('os.path.isdir', return_value=True):
         trainer_validator.validate()
 
-def test_validate_finetrainers_path_invalid(trainer_validator):
-    trainer_validator.config['finetrainers_path'] = 123
-    with pytest.raises(ValueError, match="finetrainers_path must be a string"):
-        trainer_validator.validate_finetrainers_path()
-
-def test_validate_finetrainers_path_valid(trainer_validator):
-    with patch('os.path.isfile', return_value=True):
-        trainer_validator.config['finetrainers_path'] = '/path/to/finetrainers'
-        trainer_validator.validate_finetrainers_path()
-
-def test_validate_accelerate_config_invalid(trainer_validator):
-    trainer_validator.config['accelerate_config'] = []
-    with pytest.raises(ValueError, match="accelerate_config must be a string"):
-        trainer_validator.validate_accelerate_config()
-
-def test_validate_batch_size_invalid(trainer_validator):
-    trainer_validator.config['batch_size'] = 'not_an_int'
-    with pytest.raises(ValueError, match="batch_size must be an integer"):
-        trainer_validator.validate_batch_size()
-
-def test_validate_beta1_invalid(trainer_validator):
-    trainer_validator.config['beta1'] = 'not_a_float'
-    with pytest.raises(ValueError, match="beta1 must be a float"):
-        trainer_validator.validate_beta1()
-
-def test_validate_beta2_invalid(trainer_validator):
-    trainer_validator.config['beta2'] = 'not_a_float'
-    with pytest.raises(ValueError, match="beta2 must be a float"):
-        trainer_validator.validate_beta2()
-
-def test_validate_caption_column_invalid(trainer_validator):
-    trainer_validator.config['caption_column'] = 123
-    with pytest.raises(ValueError, match="caption_column must be a string"):
-        trainer_validator.validate_caption_column()
-
-def test_validate_caption_dropout_p_invalid(trainer_validator):
-    trainer_validator.config['caption_dropout_p'] = 'not_a_float'
-    with pytest.raises(ValueError, match="caption_dropout_p must be a float"):
-        trainer_validator.validate_caption_dropout_p()
-
-def test_validate_checkpointing_limit_invalid(trainer_validator):
-    trainer_validator.config['checkpointing_limit'] = 'not_an_int'
-    with pytest.raises(ValueError, match="checkpointing_limit must be an integer"):
-        trainer_validator.validate_checkpointing_limit()
-
-def test_validate_checkpointing_steps_invalid(trainer_validator):
-    trainer_validator.config['checkpointing_steps'] = 'not_an_int'
-    with pytest.raises(ValueError, match="checkpointing_steps must be an integer"):
-        trainer_validator.validate_checkpointing_steps()
-
 def test_validate_data_root_invalid(trainer_validator):
     trainer_validator.config['data_root'] = '/invalid/path'
     with pytest.raises(ValueError, match="data_root path /invalid/path does not exist"):
@@ -115,130 +65,7 @@ def test_validate_data_root_valid(trainer_validator):
         trainer_validator.config['data_root'] = '/path/to/data'
         trainer_validator.validate_data_root()
 
-def test_validate_dataloader_num_workers_invalid(trainer_validator):
-    trainer_validator.config['dataloader_num_workers'] = 'not_an_int'
-    with pytest.raises(ValueError, match="dataloader_num_workers must be an integer"):
-        trainer_validator.validate_dataloader_num_workers()
-
-def test_validate_epsilon_invalid(trainer_validator):
-    trainer_validator.config['epsilon'] = 'not_a_float'
-    with pytest.raises(ValueError, match="epsilon must be a float"):
-        trainer_validator.validate_epsilon()
-
-def test_validate_gpu_ids_invalid(trainer_validator):
-    trainer_validator.config['gpu_ids'] = 123
-    with pytest.raises(ValueError, match="gpu_ids must be a string"):
-        trainer_validator.validate_gpu_ids()
-
-def test_validate_gradient_accumulation_steps_invalid(trainer_validator):
-    trainer_validator.config['gradient_accumulation_steps'] = 'not_an_int'
-    with pytest.raises(ValueError, match="gradient_accumulation_steps must be an integer"):
-        trainer_validator.validate_gradient_accumulation_steps()
-
-def test_validate_id_token_invalid(trainer_validator):
-    trainer_validator.config['id_token'] = 123
-    with pytest.raises(ValueError, match="id_token must be a string"):
-        trainer_validator.validate_id_token()
-
-def test_validate_lora_alpha_invalid(trainer_validator):
-    trainer_validator.config['lora_alpha'] = 'not_an_int'
-    with pytest.raises(ValueError, match="lora_alpha must be an integer"):
-        trainer_validator.validate_lora_alpha()
-
-def test_validate_lr_invalid(trainer_validator):
-    trainer_validator.config['lr'] = 'not_a_float'
-    with pytest.raises(ValueError, match="lr must be a float"):
-        trainer_validator.validate_lr()
-
-def test_validate_lr_num_cycles_invalid(trainer_validator):
-    trainer_validator.config['lr_num_cycles'] = 'not_an_int'
-    with pytest.raises(ValueError, match="lr_num_cycles must be an integer"):
-        trainer_validator.validate_lr_num_cycles()
-
-def test_validate_lr_scheduler_invalid(trainer_validator):
-    trainer_validator.config['lr_scheduler'] = ''
-    with pytest.raises(ValueError, match="lr_scheduler must be a string"):
-        trainer_validator.validate_lr_scheduler()
-
-def test_validate_lr_warmup_steps_invalid(trainer_validator):
-    trainer_validator.config['lr_warmup_steps'] = 'not_an_int'
-    with pytest.raises(ValueError, match="lr_warmup_steps must be an integer"):
-        trainer_validator.validate_lr_warmup_steps()
-
-def test_validate_max_grad_norm_invalid(trainer_validator):
-    trainer_validator.config['max_grad_norm'] = 'not_a_float'
-    with pytest.raises(ValueError, match="max_grad_norm must be a float"):
-        trainer_validator.validate_max_grad_norm()
-
-def test_validate_mixed_precision_invalid(trainer_validator):
-    trainer_validator.config['mixed_precision'] = 123
-    with pytest.raises(ValueError, match="mixed_precision must be a string"):
-        trainer_validator.validate_mixed_precision()
-
-def test_validate_model_name_invalid(trainer_validator):
-    trainer_validator.config['model_name'] = 123
-    with pytest.raises(ValueError, match="model_name must be a string"):
-        trainer_validator.validate_model_name()
-
-def test_validate_nccl_timeout_invalid(trainer_validator):
-    trainer_validator.config['nccl_timeout'] = 'not_an_int'
-    with pytest.raises(ValueError, match="nccl_timeout must be an integer"):
-        trainer_validator.validate_nccl_timeout()
-
-def test_validate_optimizer_invalid(trainer_validator):
-    trainer_validator.config['optimizer'] = 123
-    with pytest.raises(ValueError, match="optimizer must be a string"):
-        trainer_validator.validate_optimizer()
-
-def test_validate_pretrained_model_name_or_path_invalid(trainer_validator):
-    trainer_validator.config['pretrained_model_name_or_path'] = 123
-    with pytest.raises(ValueError, match="pretrained_model_name_or_path must be set"):
-        trainer_validator.validate_pretrained_model_name_or_path()
-
-def test_validate_rank_invalid(trainer_validator):
-    trainer_validator.config['rank'] = 'not_an_int'
-    with pytest.raises(ValueError, match="rank must be an integer"):
-        trainer_validator.validate_rank()
-
-def test_validate_seed_invalid(trainer_validator):
-    trainer_validator.config['seed'] = 'not_an_int'
-    with pytest.raises(ValueError, match="seed must be an integer"):
-        trainer_validator.validate_seed()
-
-def test_validate_target_modules_invalid(trainer_validator):
-    trainer_validator.config['target_modules'] = 123
-    with pytest.raises(ValueError, match="target_modules must be a string"):
-        trainer_validator.validate_target_modules()
-
-def test_validate_tracker_name_invalid(trainer_validator):
-    trainer_validator.config['tracker_name'] = 123
-    with pytest.raises(ValueError, match="tracker_name must be a string"):
-        trainer_validator.validate_tracker_name()
-
-def test_validate_train_steps_invalid(trainer_validator):
-    trainer_validator.config['train_steps'] = 'not_an_int'
-    with pytest.raises(ValueError, match="train_steps must be an integer"):
-        trainer_validator.validate_train_steps()
-
-def test_validate_training_type_invalid(trainer_validator):
-    trainer_validator.config['training_type'] = 123
-    with pytest.raises(ValueError, match="training_type must be a string"):
-        trainer_validator.validate_training_type()
-
-def test_validate_validation_steps_invalid(trainer_validator):
-    trainer_validator.config['validation_steps'] = 'not_an_int'
-    with pytest.raises(ValueError, match="validation_steps must be an integer"):
-        trainer_validator.validate_validation_steps()
-
-def test_validate_video_column_invalid(trainer_validator):
-    trainer_validator.config['video_column'] = 123
-    with pytest.raises(ValueError, match="video_column must be a string"):
-        trainer_validator.validate_video_column()
-
 def test_validate_video_resolution_buckets_invalid(trainer_validator):
-    trainer_validator.config['video_resolution_buckets'] = 123
-    with pytest.raises(ValueError, match="video_resolution_buckets must be a string"):
-        trainer_validator.validate_video_resolution_buckets()
     trainer_validator.config['video_resolution_buckets'] = '720p,1080p,4k'
     with pytest.raises(ValueError, match=f"Each bucket must have the format '<frames>x<height>x<width>', but got {trainer_validator.config['video_resolution_buckets']}"):
         trainer_validator.validate_video_resolution_buckets()
@@ -249,8 +76,3 @@ def test_validate_video_resolution_buckets_valid(trainer_validator):
 
     trainer_validator.config['video_resolution_buckets'] = '8x320x512 24x480x720 30x720x1280'
     trainer_validator.validate_video_resolution_buckets()
-
-def test_validate_weight_decay_invalid(trainer_validator):
-    trainer_validator.config['weight_decay'] = 'not_a_float'
-    with pytest.raises(ValueError, match="weight_decay must be a float"):
-        trainer_validator.validate_weight_decay()