Support for text-to-image

CHANGELOGS.rst

@@ -4,6 +4,7 @@ Change Logs
 0.7.2
 +++++
 
+* :pr:`165`: support for task text-to-image
 * :pr:`162`: improves graphs rendering for historical data
 
 0.7.1

_doc/api/tasks/index.rst

@@ -46,6 +46,7 @@ Or:
     summarization
     text_classification
     text_generation
+    text_to_image
     text2text_generation
     zero_shot_image_classification
 

_doc/api/tasks/text_to_image.rst

@@ -0,0 +1,7 @@
+
+onnx_diagnostic.tasks.text_to_image
+===================================
+
+.. automodule:: onnx_diagnostic.tasks.text_to_image
+    :members:
+    :no-undoc-members:

_doc/api/torch_export_patches/index.rst

@@ -8,6 +8,7 @@ onnx_diagnostic.torch_export_patches
     eval/index
     onnx_export_errors
     onnx_export_serialization
+    onnx_export_serialization_impl
     patches/index
     patch_expressions
     patch_inputs

_doc/api/torch_export_patches/onnx_export_serialization_impl.rst

@@ -0,0 +1,7 @@
+
+onnx_diagnostic.torch_export_patches.onnx_export_serialization_impl
+===================================================================
+
+.. automodule:: onnx_diagnostic.torch_export_patches.onnx_export_serialization_impl
+    :members:
+    :no-undoc-members:

_doc/conf.py

@@ -90,6 +90,8 @@ def linkcode_resolve(domain, info):
         "https://sdpython.github.io/doc/experimental-experiment/dev/",
         None,
     ),
+    # Not a sphinx documentation
+    # "diffusers": ("https://huggingface.co/docs/diffusers/index", None),
     "matplotlib": ("https://matplotlib.org/stable/", None),
     "numpy": ("https://numpy.org/doc/stable", None),
     "onnx": ("https://onnx.ai/onnx/", None),
@@ -104,6 +106,8 @@ def linkcode_resolve(domain, info):
     "sklearn": ("https://scikit-learn.org/stable/", None),
     "skl2onnx": ("https://onnx.ai/sklearn-onnx/", None),
     "torch": ("https://pytorch.org/docs/main/", None),
+    # Not a sphinx documentation
+    # "transformers": ("https://huggingface.co/docs/transformers/index", None),
 }
 
 # Check intersphinx reference targets exist
@@ -116,6 +120,7 @@ def linkcode_resolve(domain, info):
     ("py:class", "True"),
     ("py:class", "Argument"),
     ("py:class", "default=sklearn.utils.metadata_routing.UNCHANGED"),
+    ("py:class", "diffusers.models.unets.unet_2d_condition.UNet2DConditionOutput"),
     ("py:class", "ModelProto"),
     ("py:class", "Model"),
     ("py:class", "Module"),

_doc/patches.rst

@@ -113,7 +113,7 @@ Here is the list of supported caches:
 
     import onnx_diagnostic.torch_export_patches.onnx_export_serialization as p
 
-    print("\n".join(sorted(p.serialization_functions())))
+    print("\n".join(sorted(t.__name__ for t in p.serialization_functions())))
 
 .. _l-control-flow-rewriting:
 

_doc/status/patches_coverage.rst

@@ -14,7 +14,7 @@ The following code shows the list of serialized classes in transformers.
 
     import onnx_diagnostic.torch_export_patches.onnx_export_serialization as p
 
-    print('\n'.join(sorted(p.serialization_functions())))
+    print('\n'.join(sorted(t.__name__ for t in p.serialization_functions())))
 
 Patched Classes
 ===============

_unittests/ut_tasks/test_tasks_image_classification.py

@@ -6,7 +6,7 @@
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
-class TestTasks(ExtTestCase):
+class TestTasksImageClassification(ExtTestCase):
     @hide_stdout()
     def test_image_classification(self):
         mid = "hf-internal-testing/tiny-random-BeitForImageClassification"

_unittests/ut_tasks/test_tasks_image_text_to_text.py

@@ -11,7 +11,7 @@
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
-class TestTasks(ExtTestCase):
+class TestTasksImageTextToText(ExtTestCase):
     @hide_stdout()
     @requires_transformers("4.52")
     @requires_torch("2.7.99")

_unittests/ut_tasks/test_tasks_object_detection.py

@@ -6,7 +6,7 @@
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
-class TestTasks(ExtTestCase):
+class TestTasksObjectDetection(ExtTestCase):
     @hide_stdout()
     def test_object_detection(self):
         mid = "hustvl/yolos-tiny"

_unittests/ut_tasks/test_tasks_text_to_image.py

@@ -0,0 +1,35 @@
+import unittest
+import torch
+from onnx_diagnostic.ext_test_case import (
+    ExtTestCase,
+    hide_stdout,
+    requires_transformers,
+    requires_torch,
+)
+from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
+from onnx_diagnostic.torch_export_patches import torch_export_patches
+from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
+
+
+class TestTasksTextToTimage(ExtTestCase):
+    @hide_stdout()
+    @requires_transformers("4.52")
+    @requires_torch("2.7.99")
+    def test_text_to_image(self):
+        mid = "diffusers/tiny-torch-full-checker"
+        data = get_untrained_model_with_inputs(
+            mid, verbose=1, add_second_input=True, subfolder="unet"
+        )
+        self.assertEqual(data["task"], "text-to-image")
+        self.assertIn((data["size"], data["n_weights"]), [(5708048, 1427012)])
+        model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
+        model(**inputs)
+        model(**data["inputs2"])
+        with torch_export_patches(patch_transformers=True, verbose=10, stop_if_static=1):
+            torch.export.export(
+                model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
+            )
+
+
+if __name__ == "__main__":
+    unittest.main(verbosity=2)

_unittests/ut_tasks/test_tasks_zero_shot_image_classification.py

@@ -6,7 +6,7 @@
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
-class TestTasks(ExtTestCase):
+class TestTasksZeroShotImageClassification(ExtTestCase):
     @requires_torch("2.7.99")
     @hide_stdout()
     def test_zero_shot_image_classification(self):

_unittests/ut_tasks/try_tasks.py

@@ -569,6 +569,27 @@ def test_object_detection(self):
                 f"{round(score.item(), 3)} at location {box}"
             )
 
+    @never_test()
+    def test_text_to_image(self):
+        # clear&&NEVERTEST=1 python _unittests/ut_tasks/try_tasks.py -k test_text_to_image
+        import torch
+        from diffusers import StableDiffusionPipeline
+
+        model_id = "diffusers/tiny-torch-full-checker"  # "stabilityai/stable-diffusion-2"
+        pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(
+            "cuda"
+        )
+
+        prompt = "a photo of an astronaut riding a horse on mars and on jupyter"
+        print()
+        with steal_forward(pipe.unet, with_min_max=True):
+            image = pipe(prompt).images[0]
+        print("-- output", self.string_type(image, with_shape=True, with_min_max=True))
+        # stolen forward for class UNet2DConditionModel -- iteration 44
+        # sample=T10s2x4x96x96[-3.7734375,4.359375:A-0.043463995395642184]
+        # time_step=T7s=101
+        # encoder_hidden_states:T10s2x77x1024[-6.58203125,13.0234375:A-0.16780663634440257]
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=2)

_unittests/ut_torch_export_patches/test_patch_serialization.py

@@ -1,7 +1,12 @@
 import unittest
 import torch
 from transformers.modeling_outputs import BaseModelOutput
-from onnx_diagnostic.ext_test_case import ExtTestCase, ignore_warnings, requires_torch
+from onnx_diagnostic.ext_test_case import (
+    ExtTestCase,
+    ignore_warnings,
+    requires_torch,
+    requires_diffusers,
+)
 from onnx_diagnostic.helpers.cache_helper import (
     make_encoder_decoder_cache,
     make_dynamic_cache,
@@ -212,6 +217,63 @@ def test_sliding_window_cache_flatten(self):
                 self.string_type(cache2, with_shape=True, with_min_max=True),
             )
 
+    @ignore_warnings(UserWarning)
+    @requires_diffusers("0.30")
+    def test_unet_2d_condition_output(self):
+        from diffusers.models.unets.unet_2d_condition import UNet2DConditionOutput
+
+        bo = UNet2DConditionOutput(sample=torch.rand((4, 4, 4)))
+        self.assertEqual(bo.__class__.__name__, "UNet2DConditionOutput")
+        bo2 = torch_deepcopy([bo])
+        self.assertIsInstance(bo2, list)
+        self.assertEqual(
+            "UNet2DConditionOutput(sample:T1s4x4x4)",
+            self.string_type(bo, with_shape=True),
+        )
+
+        with torch_export_patches():
+            # internal function
+            bo2 = torch_deepcopy([bo])
+            self.assertIsInstance(bo2, list)
+            self.assertEqual(bo2[0].__class__.__name__, "UNet2DConditionOutput")
+            self.assertEqualAny([bo], bo2)
+            self.assertEqual(
+                "UNet2DConditionOutput(sample:T1s4x4x4)",
+                self.string_type(bo, with_shape=True),
+            )
+
+            # serialization
+            flat, _spec = torch.utils._pytree.tree_flatten(bo)
+            self.assertEqual(
+                "#1[T1s4x4x4]",
+                self.string_type(flat, with_shape=True),
+            )
+            bo2 = torch.utils._pytree.tree_unflatten(flat, _spec)
+            self.assertEqual(
+                self.string_type(bo, with_shape=True, with_min_max=True),
+                self.string_type(bo2, with_shape=True, with_min_max=True),
+            )
+
+            # flatten_unflatten
+            flat, _spec = torch.utils._pytree.tree_flatten(bo)
+            unflat = flatten_unflatten_for_dynamic_shapes(bo, use_dict=True)
+            self.assertIsInstance(unflat, dict)
+            self.assertEqual(list(unflat), ["sample"])
+
+        # export
+        class Model(torch.nn.Module):
+            def forward(self, cache):
+                return cache.sample[0]
+
+        bo = UNet2DConditionOutput(sample=torch.rand((4, 4, 4)))
+        model = Model()
+        model(bo)
+        DYN = torch.export.Dim.DYNAMIC
+        ds = [{0: DYN}]
+
+        with torch_export_patches():
+            torch.export.export(model, (bo,), dynamic_shapes=(ds,))
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=2)

onnx_diagnostic/helpers/config_helper.py

@@ -43,7 +43,10 @@ def update_config(config: Any, mkwargs: Dict[str, Any]):
             else:
                 update_config(getattr(config, k), v)
             continue
-        setattr(config, k, v)
+        if type(config) is dict:
+            config[k] = v
+        else:
+            setattr(config, k, v)
 
 
 def _pick(config, *atts, exceptions: Optional[Dict[str, Callable]] = None):
@@ -66,6 +69,18 @@ def _pick(config, *atts, exceptions: Optional[Dict[str, Callable]] = None):
     raise AssertionError(f"Unable to find any of these {atts!r} in {config}")
 
 
+def pick(config, name: str, default_value: Any) -> Any:
+    """
+    Returns the value of a attribute if config has it
+    otherwise the default value.
+    """
+    if not config:
+        return default_value
+    if type(config) is dict:
+        return config.get(name, default_value)
+    return getattr(config, name, default_value)
+
+
 @functools.cache
 def config_class_from_architecture(arch: str, exc: bool = False) -> Optional[type]:
     """

onnx_diagnostic/tasks/__init__.py

@@ -11,6 +11,7 @@
     summarization,
     text_classification,
     text_generation,
+    text_to_image,
     text2text_generation,
     zero_shot_image_classification,
 )
@@ -27,6 +28,7 @@
     summarization,
     text_classification,
     text_generation,
+    text_to_image,
     text2text_generation,
     zero_shot_image_classification,
 ]