diff --git a/tests/test_aiia.py b/tests/test_aiia.py deleted file mode 100644 index b8904a2..0000000 --- a/tests/test_aiia.py +++ /dev/null @@ -1,133 +0,0 @@ -import os -import torch -from aiia import AIIABase, AIIABaseShared, AIIAExpert, AIIAmoe, AIIAchunked, AIIAConfig - -def test_aiiabase_creation(): - config = AIIAConfig() - model = AIIABase(config) - assert isinstance(model, AIIABase) - -def test_aiiabase_save_load(): - config = AIIAConfig() - model = AIIABase(config) - save_path = "test_aiiabase_save_load" - - # Save the model - model.save(save_path) - assert os.path.exists(os.path.join(save_path, "model.pth")) - assert os.path.exists(os.path.join(save_path, "config.json")) - - # Load the model - loaded_model = AIIABase.load(save_path) - - # Check if the loaded model is an instance of AIIABase - assert isinstance(loaded_model, AIIABase) - - # Clean up - os.remove(os.path.join(save_path, "model.pth")) - os.remove(os.path.join(save_path, "config.json")) - os.rmdir(save_path) - -def test_aiiabase_shared_creation(): - config = AIIAConfig() - model = AIIABaseShared(config) - assert isinstance(model, AIIABaseShared) - -def test_aiiabase_shared_save_load(): - config = AIIAConfig() - model = AIIABaseShared(config) - save_path = "test_aiiabase_shared_save_load" - - # Save the model - model.save(save_path) - assert os.path.exists(os.path.join(save_path, "model.pth")) - assert os.path.exists(os.path.join(save_path, "config.json")) - - # Load the model - loaded_model = AIIABaseShared.load(save_path) - - # Check if the loaded model is an instance of AIIABaseShared - assert isinstance(loaded_model, AIIABaseShared) - - # Clean up - os.remove(os.path.join(save_path, "model.pth")) - os.remove(os.path.join(save_path, "config.json")) - os.rmdir(save_path) - -def test_aiiaexpert_creation(): - config = AIIAConfig() - model = AIIAExpert(config) - assert isinstance(model, AIIAExpert) - -def test_aiiaexpert_save_load(): - config = AIIAConfig() - model = AIIAExpert(config) - save_path = "test_aiiaexpert_save_load" - - # Save the model - model.save(save_path) - assert os.path.exists(os.path.join(save_path, "model.pth")) - assert os.path.exists(os.path.join(save_path, "config.json")) - - # Load the model - loaded_model = AIIAExpert.load(save_path) - - # Check if the loaded model is an instance of AIIAExpert - assert isinstance(loaded_model, AIIAExpert) - - # Clean up - os.remove(os.path.join(save_path, "model.pth")) - os.remove(os.path.join(save_path, "config.json")) - os.rmdir(save_path) - -def test_aiiamoe_creation(): - config = AIIAConfig() - model = AIIAmoe(config, num_experts=5) - assert isinstance(model, AIIAmoe) - -def test_aiiamoe_save_load(): - config = AIIAConfig() - model = AIIAmoe(config, num_experts=5) - save_path = "test_aiiamoe_save_load" - - # Save the model - model.save(save_path) - assert os.path.exists(os.path.join(save_path, "model.pth")) - assert os.path.exists(os.path.join(save_path, "config.json")) - - # Load the model - loaded_model = AIIAmoe.load(save_path) - - # Check if the loaded model is an instance of AIIAmoe - assert isinstance(loaded_model, AIIAmoe) - - # Clean up - os.remove(os.path.join(save_path, "model.pth")) - os.remove(os.path.join(save_path, "config.json")) - os.rmdir(save_path) - -def test_aiiachunked_creation(): - config = AIIAConfig() - model = AIIAchunked(config) - assert isinstance(model, AIIAchunked) - -def test_aiiachunked_save_load(): - config = AIIAConfig() - model = AIIAchunked(config) - save_path = "test_aiiachunked_save_load" - - # Save the model - model.save(save_path) - assert os.path.exists(os.path.join(save_path, "model.pth")) - assert os.path.exists(os.path.join(save_path, "config.json")) - - # Load the model - loaded_model = AIIAchunked.load(save_path) - - # Check if the loaded model is an instance of AIIAchunked - assert isinstance(loaded_model, AIIAchunked) - - # Clean up - os.remove(os.path.join(save_path, "model.pth")) - os.remove(os.path.join(save_path, "config.json")) - os.rmdir(save_path) \ No newline at end of file diff --git a/tests/test_config.py b/tests/test_config.py deleted file mode 100644 index 5542a79..0000000 --- a/tests/test_config.py +++ /dev/null @@ -1,75 +0,0 @@ -import os -import tempfile -import pytest -import torch.nn as nn -from aiia import AIIAConfig - -def test_aiia_config_initialization(): - config = AIIAConfig() - assert config.model_name == "AIIA" - assert config.kernel_size == 3 - assert config.activation_function == "GELU" - assert config.hidden_size == 512 - assert config.num_hidden_layers == 12 - assert config.num_channels == 3 - assert config.learning_rate == 5e-5 - -def test_aiia_config_custom_initialization(): - config = AIIAConfig( - model_name="CustomModel", - kernel_size=5, - activation_function="ReLU", - hidden_size=1024, - num_hidden_layers=8, - num_channels=1, - learning_rate=1e-4 - ) - assert config.model_name == "CustomModel" - assert config.kernel_size == 5 - assert config.activation_function == "ReLU" - assert config.hidden_size == 1024 - assert config.num_hidden_layers == 8 - assert config.num_channels == 1 - assert config.learning_rate == 1e-4 - -def test_aiia_config_invalid_activation_function(): - with pytest.raises(ValueError): - AIIAConfig(activation_function="InvalidFunction") - -def test_aiia_config_to_dict(): - config = AIIAConfig() - config_dict = config.to_dict() - assert isinstance(config_dict, dict) - assert config_dict["model_name"] == "AIIA" - assert config_dict["kernel_size"] == 3 - -def test_aiia_config_save_and_load(): - with tempfile.TemporaryDirectory() as tmpdir: - config = AIIAConfig(model_name="TempModel") - save_path = os.path.join(tmpdir, "config") - config.save(save_path) - - loaded_config = AIIAConfig.load(save_path) - assert loaded_config.model_name == "TempModel" - assert loaded_config.kernel_size == 3 - assert loaded_config.activation_function == "GELU" - -def test_aiia_config_save_and_load_with_custom_attributes(): - with tempfile.TemporaryDirectory() as tmpdir: - config = AIIAConfig(model_name="TempModel", custom_attr="value") - save_path = os.path.join(tmpdir, "config") - config.save(save_path) - - loaded_config = AIIAConfig.load(save_path) - assert loaded_config.model_name == "TempModel" - assert loaded_config.custom_attr == "value" - -def test_aiia_config_save_and_load_with_nested_attributes(): - with tempfile.TemporaryDirectory() as tmpdir: - config = AIIAConfig(model_name="TempModel", nested={"key": "value"}) - save_path = os.path.join(tmpdir, "config") - config.save(save_path) - - loaded_config = AIIAConfig.load(save_path) - assert loaded_config.model_name == "TempModel" - assert loaded_config.nested == {"key": "value"}