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92a6fc7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 | import json
import os
import tempfile
import unittest
from unittest.mock import MagicMock, patch
import torch
from transformers import CLIPTextModel, LongformerModel
from diffusers import ConfigMixin
from diffusers.models import AutoModel, UNet2DConditionModel
from diffusers.models.modeling_utils import ModelMixin
class TestAutoModel(unittest.TestCase):
@patch(
"diffusers.models.AutoModel.load_config",
side_effect=[EnvironmentError("File not found"), {"_class_name": "UNet2DConditionModel"}],
)
def test_load_from_config_diffusers_with_subfolder(self, mock_load_config):
model = AutoModel.from_pretrained("hf-internal-testing/tiny-stable-diffusion-torch", subfolder="unet")
assert isinstance(model, UNet2DConditionModel)
@patch(
"diffusers.models.AutoModel.load_config",
side_effect=[EnvironmentError("File not found"), {"model_type": "clip_text_model"}],
)
def test_load_from_config_transformers_with_subfolder(self, mock_load_config):
model = AutoModel.from_pretrained(
"hf-internal-testing/tiny-stable-diffusion-torch", subfolder="text_encoder", use_safetensors=False
)
assert isinstance(model, CLIPTextModel)
def test_load_from_config_without_subfolder(self):
model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-longformer")
assert isinstance(model, LongformerModel)
def test_load_from_model_index(self):
model = AutoModel.from_pretrained(
"hf-internal-testing/tiny-stable-diffusion-torch", subfolder="text_encoder", use_safetensors=False
)
assert isinstance(model, CLIPTextModel)
def test_load_dynamic_module_from_local_path_with_subfolder(self):
CUSTOM_MODEL_CODE = (
"import torch\n"
"from diffusers import ModelMixin, ConfigMixin\n"
"from diffusers.configuration_utils import register_to_config\n"
"\n"
"class CustomModel(ModelMixin, ConfigMixin):\n"
" @register_to_config\n"
" def __init__(self, hidden_size=8):\n"
" super().__init__()\n"
" self.linear = torch.nn.Linear(hidden_size, hidden_size)\n"
"\n"
" def forward(self, x):\n"
" return self.linear(x)\n"
)
with tempfile.TemporaryDirectory() as tmpdir:
subfolder = "custom_model"
model_dir = os.path.join(tmpdir, subfolder)
os.makedirs(model_dir)
with open(os.path.join(model_dir, "modeling.py"), "w") as f:
f.write(CUSTOM_MODEL_CODE)
config = {
"_class_name": "CustomModel",
"_diffusers_version": "0.0.0",
"auto_map": {"AutoModel": "modeling.CustomModel"},
"hidden_size": 8,
}
with open(os.path.join(model_dir, "config.json"), "w") as f:
json.dump(config, f)
torch.save({}, os.path.join(model_dir, "diffusion_pytorch_model.bin"))
model = AutoModel.from_pretrained(tmpdir, subfolder=subfolder, trust_remote_code=True)
assert model.__class__.__name__ == "CustomModel"
assert model.config["hidden_size"] == 8
class TestAutoModelFromConfig(unittest.TestCase):
@patch(
"diffusers.pipelines.pipeline_loading_utils.get_class_obj_and_candidates",
return_value=(MagicMock(), None),
)
def test_from_config_with_dict_diffusers_class(self, mock_get_class):
config = {"_class_name": "UNet2DConditionModel", "sample_size": 64}
mock_model = MagicMock()
mock_get_class.return_value[0].from_config.return_value = mock_model
result = AutoModel.from_config(config)
mock_get_class.assert_called_once_with(
library_name="diffusers",
class_name="UNet2DConditionModel",
importable_classes=unittest.mock.ANY,
pipelines=None,
is_pipeline_module=False,
trust_remote_code=False,
)
mock_get_class.return_value[0].from_config.assert_called_once_with(config)
assert result is mock_model
@patch(
"diffusers.pipelines.pipeline_loading_utils.get_class_obj_and_candidates",
return_value=(MagicMock(), None),
)
@patch("diffusers.models.AutoModel.load_config", return_value={"_class_name": "UNet2DConditionModel"})
def test_from_config_with_string_path(self, mock_load_config, mock_get_class):
mock_model = MagicMock()
mock_get_class.return_value[0].from_config.return_value = mock_model
result = AutoModel.from_config("hf-internal-testing/tiny-stable-diffusion-torch", subfolder="unet")
mock_load_config.assert_called_once()
assert result is mock_model
def test_from_config_raises_on_missing_class_info(self):
config = {"some_key": "some_value"}
with self.assertRaises(ValueError, msg="Couldn't find a model class"):
AutoModel.from_config(config)
@patch(
"diffusers.pipelines.pipeline_loading_utils.get_class_obj_and_candidates",
return_value=(MagicMock(), None),
)
def test_from_config_with_model_type_routes_to_transformers(self, mock_get_class):
config = {"model_type": "clip_text_model"}
mock_model = MagicMock()
mock_get_class.return_value[0].from_config.return_value = mock_model
result = AutoModel.from_config(config)
mock_get_class.assert_called_once_with(
library_name="transformers",
class_name="AutoModel",
importable_classes=unittest.mock.ANY,
pipelines=None,
is_pipeline_module=False,
trust_remote_code=False,
)
assert result is mock_model
def test_from_config_raises_on_none(self):
with self.assertRaises(ValueError, msg="Please provide a `pretrained_model_name_or_path_or_dict`"):
AutoModel.from_config(None)
class TestRegisterForAutoClass(unittest.TestCase):
def test_register_for_auto_class_sets_attribute(self):
class DummyModel(ModelMixin, ConfigMixin):
config_name = "config.json"
DummyModel.register_for_auto_class("AutoModel")
self.assertEqual(DummyModel._auto_class, "AutoModel")
def test_register_for_auto_class_rejects_unsupported(self):
class DummyModel(ModelMixin, ConfigMixin):
config_name = "config.json"
with self.assertRaises(ValueError, msg="Only 'AutoModel' is supported"):
DummyModel.register_for_auto_class("AutoPipeline")
def test_auto_map_in_saved_config(self):
class DummyModel(ModelMixin, ConfigMixin):
config_name = "config.json"
DummyModel.register_for_auto_class("AutoModel")
model = DummyModel()
with tempfile.TemporaryDirectory() as tmpdir:
model.save_config(tmpdir)
config_path = os.path.join(tmpdir, "config.json")
with open(config_path, "r") as f:
config = json.load(f)
self.assertIn("auto_map", config)
self.assertIn("AutoModel", config["auto_map"])
module_name = DummyModel.__module__.split(".")[-1]
self.assertEqual(config["auto_map"]["AutoModel"], f"{module_name}.DummyModel")
def test_no_auto_map_without_register(self):
class DummyModel(ModelMixin, ConfigMixin):
config_name = "config.json"
model = DummyModel()
with tempfile.TemporaryDirectory() as tmpdir:
model.save_config(tmpdir)
config_path = os.path.join(tmpdir, "config.json")
with open(config_path, "r") as f:
config = json.load(f)
self.assertNotIn("auto_map", config)
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