Merge remote-tracking branch 'upstream/master' into validate-preset-assets

Author: anthony-etim

keras_hub/src/models/basnet/basnet_test.py

@@ -54,7 +54,6 @@ def test_saved_model(self):
             input_data=self.images,
         )
 
-    @pytest.mark.skip(reason="TODO: Bug with BASNet liteRT export")
     def test_litert_export(self):
         self.run_litert_export_test(
             cls=BASNetImageSegmenter,

keras_hub/src/models/d_fine/d_fine_object_detector_test.py

@@ -174,6 +174,10 @@ def test_saved_model(self):
             input_data=self.images,
         )
 
+    @pytest.mark.xfail(
+        condition=keras.backend.backend() == "torch",
+        reason="D-FINE's multi-scale features hit a torch.export shape guard.",
+    )
     def test_litert_export(self):
         backbone = DFineBackbone(**self.base_backbone_kwargs)
         init_kwargs = {

keras_hub/src/models/deeplab_v3/deeplab_v3_segmenter_test.py

@@ -72,7 +72,8 @@ def test_saved_model(self):
         )
 
     @pytest.mark.skip(
-        reason="TODO: Bug with DeepLabV3ImageSegmenter liteRT export"
+        reason="TODO: DeepLabV3ImageSegmenter LiteRT export fails with "
+        "'symbolic tf.Tensor used as a Python bool' while tracing for export."
     )
     def test_litert_export(self):
         self.run_litert_export_test(

keras_hub/src/models/f_net/f_net_text_classifier_test.py

@@ -1,6 +1,7 @@
 import os
 
 import pytest
+from keras import backend
 
 from keras_hub.src.models.f_net.f_net_backbone import FNetBackbone
 from keras_hub.src.models.f_net.f_net_text_classifier import FNetTextClassifier
@@ -57,6 +58,10 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
+    @pytest.mark.xfail(
+        condition=backend.backend() == "torch",
+        reason="litert-torch has no lowering for aten.complex (from ops.fft2).",
+    )
     def test_litert_export(self):
         # F-Net does NOT use padding_mask - it only uses token_ids and
         # segment_ids. Don't add padding_mask to input_data.

keras_hub/src/models/flux/flux_backbone_test.py

@@ -1,4 +1,5 @@
 import pytest
+from keras import backend
 from keras import ops
 
 from keras_hub.src.models.clip.clip_text_encoder import CLIPTextEncoder
@@ -84,6 +85,10 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
+    @pytest.mark.xfail(
+        condition=backend.backend() == "torch",
+        reason="torch.export guard from Flux's dynamic num_heads reshape.",
+    )
     def test_litert_export(self):
         self.run_litert_export_test(
             cls=FluxBackbone,

keras_hub/src/models/gpt_neo_x/gpt_neo_x_causal_lm_test.py

@@ -112,13 +112,9 @@ def test_saved_model(self):
         )
 
     def test_litert_export(self):
-        pytest.skip(reason="TODO: Fix TFLite export bug for GPTNeoX")
         self.run_litert_export_test(
             cls=GPTNeoXCausalLM,
             init_kwargs=self.init_kwargs,
             input_data=self.input_data,
-            output_thresholds={
-                "max": 1e-3,
-                "mean": 1e-4,
-            },  # More lenient thresholds for numerical differences
+            output_thresholds={"*": {"max": 1e-3, "mean": 1e-4}},
         )

keras_hub/src/models/gpt_oss/gpt_oss_causal_lm_test.py

@@ -1,6 +1,7 @@
 from unittest.mock import patch
 
 import pytest
+from keras import backend
 from keras import ops
 
 from keras_hub.src.models.gpt_oss.gpt_oss_backbone import GptOssBackbone
@@ -113,6 +114,10 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
+    @pytest.mark.xfail(
+        condition=backend.backend() == "torch",
+        reason="litert-torch NHWC rewriter has no lowering for aten.amax.",
+    )
     def test_litert_export(self):
         self.run_litert_export_test(
             cls=GptOssCausalLM,

keras_hub/src/models/mixtral/mixtral_causal_lm_test.py

@@ -1,6 +1,7 @@
 import os
 from unittest.mock import patch
 
+import keras
 import pytest
 from keras import ops
 
@@ -107,6 +108,10 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
+    @pytest.mark.xfail(
+        condition=keras.backend.backend() == "torch",
+        reason="litert-torch cannot lower aten._assert_async from MoE routing.",
+    )
     def test_litert_export(self):
         self.run_litert_export_test(
             cls=MixtralCausalLM,

keras_hub/src/models/moonshine/moonshine_audio_to_text_test.py

@@ -145,9 +145,6 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
-    @pytest.mark.skip(
-        reason="TODO: Bug with MoonshineAudioToText liteRT export"
-    )
     def test_litert_export(self):
         self.run_litert_export_test(
             cls=MoonshineAudioToText,

keras_hub/src/models/qwen3_moe/qwen3_moe_causal_lm_test.py

@@ -3,6 +3,7 @@
 
 os.environ["KERAS_BACKEND"] = "jax"
 
+import keras
 import pytest
 from keras import ops
 
@@ -124,6 +125,10 @@ def test_saved_model(self):
             input_data=self.input_data,
         )
 
+    @pytest.mark.xfail(
+        condition=keras.backend.backend() == "torch",
+        reason="litert-torch cannot lower aten._assert_async from MoE routing.",
+    )
     def test_litert_export(self):
         self.run_litert_export_test(
             cls=Qwen3MoeCausalLM,