Upload 2025-11-27/runs/24101-19731275109/ci_results_run_models_gpu/model_results.json with huggingface_hub

2025-11-27/runs/24101-19731275109/ci_results_run_models_gpu/model_results.json

@@ -0,0 +1,1248 @@
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+                    "trace": "(line 1964)  AttributeError: 'Emu3ForConditionalGeneration' object has no attribute 'vocabulary_mapping'"
+                },
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generation",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 112.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 50.69 MiB is free. Process 17709 has 22.25 GiB memory in use. Of the allocated memory 21.84 GiB is allocated by PyTorch, and 21.46 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generation_batched",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.41 GiB. GPU 0 has a total capacity of 22.30 GiB of which 14.69 MiB is free. Process 17709 has 22.28 GiB memory in use. Of the allocated memory 21.90 GiB is allocated by PyTorch, and 424.00 KiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generation_multi_image",
+                    "trace": "(line 417)  AssertionError: Lists differ: ['USER: 64*6464*64What do these two images[82 chars]ng.'] != [\"USER: 64*6464*64What do these two images[104 chars]' '\"]"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generate_images",
+                    "trace": "(line 1964)  AttributeError: 'Emu3ForConditionalGeneration' object has no attribute 'vocabulary_mapping'"
+                },
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generation",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 112.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 86.69 MiB is free. Process 22254 has 22.21 GiB memory in use. Of the allocated memory 21.70 GiB is allocated by PyTorch, and 10.59 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generation_batched",
+                    "trace": "(line 388)  AssertionError: Lists differ: ['USE[44 chars]TANT: 1.Filed with 1.Computing theComputing.Co[114 chars]ng.'] != ['USE[44 chars]TANT:是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是是'[95 chars]是是是']"
+                },
+                {
+                    "line": "tests/models/emu3/test_modeling_emu3.py::Emu3IntegrationTest::test_model_generation_multi_image",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 704.00 KiB is free. Process 22254 has 22.29 GiB memory in use. Of the allocated memory 21.78 GiB is allocated by PyTorch, and 18.01 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                }
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+                {
+                    "line": "tests/models/idefics2/test_modeling_idefics2.py::Idefics2ModelTest::test_multi_gpu_data_parallel_forward",
+                    "trace": "(line 769)  StopIteration: Caught StopIteration in replica 1 on device 1."
+                },
+                {
+                    "line": "tests/models/idefics2/test_modeling_idefics2.py::Idefics2ForConditionalGenerationModelTest::test_multi_gpu_data_parallel_forward",
+                    "trace": "(line 769)  StopIteration: Caught StopIteration in replica 1 on device 1."
+                },
+                {
+                    "line": "tests/models/idefics2/test_modeling_idefics2.py::Idefics2ForConditionalGenerationIntegrationTest::test_integration_test",
+                    "trace": "(line 584)  AssertionError: 'In this image, we see the Statue of Liberty in New York City.' != 'In this image, we see the Statue of Liberty, the New York City'"
+                },
+                {
+                    "line": "tests/models/idefics2/test_modeling_idefics2.py::Idefics2ForConditionalGenerationIntegrationTest::test_integration_test_4bit",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 4.69 MiB is free. Process 22477 has 22.29 GiB memory in use. Of the allocated memory 21.78 GiB is allocated by PyTorch, and 16.31 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/idefics2/test_modeling_idefics2.py::Idefics2ForConditionalGenerationIntegrationTest::test_integration_test_4bit_batch2",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 704.00 KiB is free. Process 22477 has 22.29 GiB memory in use. Of the allocated memory 21.78 GiB is allocated by PyTorch, and 12.96 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                }
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+                    "line": "tests/models/idefics3/test_modeling_idefics3.py::Idefics3ModelTest::test_multi_gpu_data_parallel_forward",
+                    "trace": "(line 769)  StopIteration: Caught StopIteration in replica 1 on device 1."
+                },
+                {
+                    "line": "tests/models/idefics3/test_modeling_idefics3.py::Idefics3ForConditionalGenerationModelTest::test_multi_gpu_data_parallel_forward",
+                    "trace": "(line 769)  StopIteration: Caught StopIteration in replica 1 on device 1."
+                }
+            ]
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+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_generate_images",
+                    "trace": "(line 107)  ValueError: Only returning PyTorch tensors is currently supported."
+                },
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation",
+                    "trace": "(line 427)  AssertionError: 'You [253 chars]d it? deliber deliberocampocamp吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃[13 chars]吃喝吃喝' != 'You [253 chars]d it?\\n\\nThe image depicts the constellation o[43 chars]ion\"'"
+                },
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation_batched",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 14.69 MiB is free. Process 17638 has 22.28 GiB memory in use. Of the allocated memory 21.86 GiB is allocated by PyTorch, and 42.67 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation_with_multi_image",
+                    "trace": "(line 480)  AssertionError: Lists differ: ['You[228 chars]mmon?\\n\\nThe two images you provided are of th[158 chars] of'] != ['You[228 chars]mmon?吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃[36 chars]喝吃喝']"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_generate_images",
+                    "trace": "(line 107)  ValueError: Only returning PyTorch tensors is currently supported."
+                },
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation",
+                    "trace": "(line 427)  AssertionError: 'You [253 chars]d it? deliber deliberocampocamp吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃[13 chars]吃喝吃喝' != 'You [253 chars]d it?\\n\\nThe image depicts the constellation o[43 chars]ion\"'"
+                },
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation_batched",
+                    "trace": "(line 458)  AssertionError: Lists differ: ['You[254 chars]d it?\\n\\nThe image depicts the constellation o[375 chars]his'] != ['You[254 chars]d it? deliber deliberocampocamp吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃[297 chars]喝吃喝']"
+                },
+                {
+                    "line": "tests/models/janus/test_modeling_janus.py::JanusIntegrationTest::test_model_text_generation_with_multi_image",
+                    "trace": "(line 480)  AssertionError: Lists differ: ['You[228 chars]mmon?\\n\\nThe two images you provided are of th[158 chars] of'] != ['You[228 chars]mmon?吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃喝吃[36 chars]喝吃喝']"
+                }
+            ]
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+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202135"
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+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202135#step:16:1"
+        }
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+    "models_kosmos2": {
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+                {
+                    "line": "tests/models/kosmos2/test_modeling_kosmos2.py::Kosmos2ModelIntegrationTest::test_inference_interpolate_pos_encoding",
+                    "trace": "(line 772)  AttributeError: 'NoneType' object has no attribute 'last_hidden_state'"
+                },
+                {
+                    "line": "tests/models/kosmos2/test_modeling_kosmos2.py::Kosmos2ModelIntegrationTest::test_snowman_image_captioning",
+                    "trace": "(line 79)  AssertionError:"
+                },
+                {
+                    "line": "tests/models/kosmos2/test_modeling_kosmos2.py::Kosmos2ModelIntegrationTest::test_snowman_image_captioning_batch",
+                    "trace": "(line 707)  AssertionError: Lists differ: ['<gr[35 chars]ail: A snowman is sitting in front of a fire, [575 chars]t>.'] != ['<gr[35 chars]ail: The image features a snowman sitting by<p[836 chars]t>.']"
+                }
+            ],
+            "single": [
+                {
+                    "line": "tests/models/kosmos2/test_modeling_kosmos2.py::Kosmos2ModelIntegrationTest::test_inference_interpolate_pos_encoding",
+                    "trace": "(line 772)  AttributeError: 'NoneType' object has no attribute 'last_hidden_state'"
+                },
+                {
+                    "line": "tests/models/kosmos2/test_modeling_kosmos2.py::Kosmos2ModelIntegrationTest::test_snowman_image_captioning",
+                    "trace": "(line 79)  AssertionError:"
+                },
+                {
+                    "line": "tests/models/kosmos2/test_modeling_kosmos2.py::Kosmos2ModelIntegrationTest::test_snowman_image_captioning_batch",
+                    "trace": "(line 707)  AssertionError: Lists differ: ['<gr[35 chars]ail: A snowman is sitting in front of a fire, [575 chars]t>.'] != ['<gr[35 chars]ail: The image features a snowman sitting by<p[836 chars]t>.']"
+                }
+            ]
+        },
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+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202046"
+        },
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+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202046#step:16:1"
+        }
+    },
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+                "single": 2,
+                "multi": 2
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+            "Tokenizers": {
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+            "ONNX": {
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+                "single": 0,
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+            "Auto": {
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+                "multi": 0
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+            "Quantization": {
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+                "single": 0,
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+            "Unclassified": {
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+                "multi": 0
+            }
+        },
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+        "success": 300,
+        "skipped": 322,
+        "time_spent": [
+            154.32,
+            161.51
+        ],
+        "error": false,
+        "failures": {
+            "multi": [
+                {
+                    "line": "tests/models/kosmos2_5/test_modeling_kosmos2_5.py::Kosmos2_5ModelTest::test_sdpa_can_compile_dynamic",
+                    "trace": "(line 1677)  torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function scaled_dot_product_attention>(*(FakeTensor(..., device='cuda:0', size=(s10, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s10, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s10, 4, s27, 8), dtype=torch.float16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s10, 1, s27, s27 + 1),"
+                },
+                {
+                    "line": "tests/models/kosmos2_5/test_modeling_kosmos2_5.py::Kosmos2_5ModelIntegrationTest::test_eager",
+                    "trace": "(line 577)  AssertionError: Lists differ: ['<bb[216 chars]<y_651></bbox>COOKIE DOH SAUCES\\n<bbox><x_788>[452 chars]0\\n'] != ['<bb[216 chars]<y_650></bbox>COOKIE DOH SAUCES\\n<bbox><x_788>[452 chars]0\\n']"
+                }
+            ],
+            "single": [
+                {
+                    "line": "tests/models/kosmos2_5/test_modeling_kosmos2_5.py::Kosmos2_5ModelTest::test_sdpa_can_compile_dynamic",
+                    "trace": "(line 1677)  torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function scaled_dot_product_attention>(*(FakeTensor(..., device='cuda:0', size=(s10, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s10, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s10, 4, s27, 8), dtype=torch.float16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s10, 1, s27, s27 + 1),"
+                },
+                {
+                    "line": "tests/models/kosmos2_5/test_modeling_kosmos2_5.py::Kosmos2_5ModelIntegrationTest::test_eager",
+                    "trace": "(line 577)  AssertionError: Lists differ: ['<bb[216 chars]<y_651></bbox>COOKIE DOH SAUCES\\n<bbox><x_788>[452 chars]0\\n'] != ['<bb[216 chars]<y_650></bbox>COOKIE DOH SAUCES\\n<bbox><x_788>[452 chars]0\\n']"
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202150",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202041"
+        },
+        "captured_info": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202150#step:16:1",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202041#step:16:1"
+        }
+    },
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+            "ONNX": {
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+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
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+                "single": 0,
+                "multi": 0
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+            "Unclassified": {
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+                "single": 0,
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+        "errors": 0,
+        "success": 200,
+        "skipped": 128,
+        "time_spent": [
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+        "failures": {},
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+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202247"
+        },
+        "captured_info": {}
+    },
+    "models_lightglue": {
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+            "PyTorch": {
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+                "single": 0,
+                "multi": 1
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+            "Tokenizers": {
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+            "Pipelines": {
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+                "multi": 0
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+            "Trainer": {
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+            "ONNX": {
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+                "multi": 0
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+            "Auto": {
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+            "Quantization": {
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+                "multi": 0
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+            "Unclassified": {
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+        },
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+        "success": 285,
+        "skipped": 100,
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+            41.72,
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+        "error": false,
+        "failures": {
+            "multi": [
+                {
+                    "line": "tests/models/lightglue/test_modeling_lightglue.py::LightGlueModelTest::test_multi_gpu_data_parallel_forward",
+                    "trace": "(line 769)  StopIteration: Caught StopIteration in replica 1 on device 1."
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202209",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202033"
+        },
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+                "single": 8,
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+            "Pipelines": {
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+            "ONNX": {
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+                "single": 0,
+                "multi": 0
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+            "Quantization": {
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+        },
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+        "success": 385,
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+            258.94,
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+        "error": false,
+        "failures": {
+            "multi": [
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test",
+                    "trace": "(line 346)  AssertionError: 'user[42 chars]ant\\nса POW.nb.AppendLine深刻cores邬_fpsرُAktcrea[450 chars]できて烂' != 'user[42 chars]ant\\nThe image is a radar chart that compares [396 chars]hows'"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch",
+                    "trace": "(line 367)  AssertionError: Lists differ: ['use[43 chars]ant\\n ))-campus史上最 NormprzedsiStampedÁ happies[207 chars]sst'] != ['use[43 chars]ant\\nThe image is a radar chart that compares [210 chars]eng']"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_different_resolutions",
+                    "trace": "(line 526)  AssertionError: Lists differ: ['use[43 chars]ant\\n Moo nop inhabited掭وشIpv_backup bert_back[567 chars]狱监狱'] != ['use[43 chars]ant\\nThe image shows a scene of two deer in a [481 chars]Its']"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_matches_single",
+                    "trace": "(line 560)  AssertionError: 'user[122 chars]debutincinnnice\\\\\",\\\\ inclus aslı\\\\\",\\\\\\'REhyp[95 chars]SSдж' != 'user[122 chars]debut[inputules undone前几天ragen\\\\\",\\\\OUCH play [148 chars]nput'"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_multi_image",
+                    "trace": "(line 427)  AssertionError: 'user\\n\\nWhat is the difference between t[228 chars]ntly' != \"user\\n\\nWhat is the difference between t[239 chars] The\""
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_multi_image_nested",
+                    "trace": "(line 475)  AssertionError: Lists differ: ['user\\nTell me about the french revolutio[772 chars]是—\"'] != [\"user\\nTell me about the french revolutio[765 chars]ent']"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_multi_video",
+                    "trace": "(line 496)  AssertionError: 'user\\n\\nAre these videos identical?\\nass[192 chars]ptoظ' != \"user\\n\\nAre these videos identical?\\nass[105 chars]und.\""
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_video",
+                    "trace": "(line 390)  AssertionError: \"user\\n\\nWhat do you see in this video?\\n[179 chars]ment\" != 'user\\n\\nWhat do you see in this video?\\n[120 chars]ook.'"
+                }
+            ],
+            "single": [
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test",
+                    "trace": "(line 346)  AssertionError: 'user[42 chars]ant\\nса POW.nb.AppendLine深刻cores邬_fpsرُAktcrea[450 chars]できて烂' != 'user[42 chars]ant\\nThe image is a radar chart that compares [396 chars]hows'"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch",
+                    "trace": "(line 367)  AssertionError: Lists differ: ['use[43 chars]ant\\n ))-campus史上最 NormprzedsiStampedÁ happies[207 chars]sst'] != ['use[43 chars]ant\\nThe image is a radar chart that compares [210 chars]eng']"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_different_resolutions",
+                    "trace": "(line 526)  AssertionError: Lists differ: ['use[43 chars]ant\\n Moo nop inhabited掭وشIpv_backup bert_back[567 chars]狱监狱'] != ['use[43 chars]ant\\nThe image shows a scene of two deer in a [481 chars]Its']"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_batch_matches_single",
+                    "trace": "(line 560)  AssertionError: 'user[122 chars]debutincinnnice\\\\\",\\\\ inclus aslı\\\\\",\\\\\\'REhyp[95 chars]SSдж' != 'user[122 chars]debut[inputules undone前几��ragen\\\\\",\\\\OUCH play [148 chars]nput'"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_multi_image",
+                    "trace": "(line 427)  AssertionError: 'user\\n\\nWhat is the difference between t[228 chars]ntly' != \"user\\n\\nWhat is the difference between t[239 chars] The\""
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_multi_image_nested",
+                    "trace": "(line 475)  AssertionError: Lists differ: ['user\\nTell me about the french revolutio[772 chars]是—\"'] != [\"user\\nTell me about the french revolutio[765 chars]ent']"
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_multi_video",
+                    "trace": "(line 496)  AssertionError: 'user\\n\\nAre these videos identical?\\nass[192 chars]ptoظ' != \"user\\n\\nAre these videos identical?\\nass[105 chars]und.\""
+                },
+                {
+                    "line": "tests/models/llava_onevision/test_modeling_llava_onevision.py::LlavaOnevisionForConditionalGenerationIntegrationTest::test_small_model_integration_test_video",
+                    "trace": "(line 390)  AssertionError: \"user\\n\\nWhat do you see in this video?\\n[179 chars]ment\" != 'user\\n\\nWhat do you see in this video?\\n[120 chars]ook.'"
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202154",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202024"
+        },
+        "captured_info": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202154#step:16:1",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202024#step:16:1"
+        }
+    },
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+                "single": 6,
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+                "unclassified": 0,
+                "single": 1,
+                "multi": 1
+            }
+        },
+        "errors": 0,
+        "success": 502,
+        "skipped": 262,
+        "time_spent": [
+            208.81,
+            216.48
+        ],
+        "error": false,
+        "failures": {
+            "single": [
+                {
+                    "line": "tests/models/mllama/test_image_processing_mllama.py::MllamaImageProcessingTest::test_can_compile_fast_image_processor",
+                    "trace": "(line 175)  AssertionError: The values for attribute 'device' do not match: cpu != cuda:0."
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForCausalLMModelTest::test_sdpa_can_compile_dynamic",
+                    "trace": "(line 1677)  torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function scaled_dot_product_attention>(*(FakeTensor(..., device='cuda:0', size=(s52, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s52, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s52, 4, s27, 8), dtype=torch.float16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s52, 1, s27, s27 + 1),"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_batched_generate",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 112.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 80.69 MiB is free. Process 30639 has 22.22 GiB memory in use. Of the allocated memory 21.82 GiB is allocated by PyTorch, and 18.38 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_forward",
+                    "trace": "(line 212)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 704.00 KiB is free. Process 30639 has 22.29 GiB memory in use. Of the allocated memory 21.90 GiB is allocated by PyTorch, and 15.76 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_generate",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 112.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 2.69 MiB is free. Process 30639 has 22.29 GiB memory in use. Of the allocated memory 21.90 GiB is allocated by PyTorch, and 9.24 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_generate_text_only",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 2.69 MiB is free. Process 30639 has 22.29 GiB memory in use. Of the allocated memory 21.91 GiB is allocated by PyTorch, and 6.64 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_multi_image_generate",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 112.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 78.69 MiB is free. Process 30639 has 22.22 GiB memory in use. Of the allocated memory 21.68 GiB is allocated by PyTorch, and 160.21 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                }
+            ],
+            "multi": [
+                {
+                    "line": "tests/models/mllama/test_image_processing_mllama.py::MllamaImageProcessingTest::test_can_compile_fast_image_processor",
+                    "trace": "(line 175)  AssertionError: The values for attribute 'device' do not match: cpu != cuda:0."
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForCausalLMModelTest::test_eager_padding_matches_padding_free_with_position_ids",
+                    "trace": "(line 2059)  AssertionError: Tensor-likes are not close!"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForCausalLMModelTest::test_sdpa_can_compile_dynamic",
+                    "trace": "(line 1677)  torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function scaled_dot_product_attention>(*(FakeTensor(..., device='cuda:0', size=(s52, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s52, 4, s27, 8), dtype=torch.float16), FakeTensor(..., device='cuda:0', size=(s52, 4, s27, 8), dtype=torch.float16)), **{'attn_mask': FakeTensor(..., device='cuda:0', size=(s52, 1, s27, s27 + 1),"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationModelTest::test_multi_gpu_data_parallel_forward",
+                    "trace": "(line 769)  StopIteration: Caught StopIteration in replica 1 on device 1."
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_batched_generate",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 18.69 MiB is free. Process 36943 has 22.28 GiB memory in use. Of the allocated memory 21.75 GiB is allocated by PyTorch, and 33.64 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_forward",
+                    "trace": "(line 212)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 2.69 MiB is free. Process 36943 has 22.29 GiB memory in use. Of the allocated memory 21.78 GiB is allocated by PyTorch, and 23.76 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_generate",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 112.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 38.69 MiB is free. Process 36943 has 22.26 GiB memory in use. Of the allocated memory 21.75 GiB is allocated by PyTorch, and 16.88 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_generate_text_only",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 704.00 KiB is free. Process 36943 has 22.29 GiB memory in use. Of the allocated memory 21.78 GiB is allocated by PyTorch, and 18.01 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                },
+                {
+                    "line": "tests/models/mllama/test_modeling_mllama.py::MllamaForConditionalGenerationIntegrationTest::test_11b_model_integration_multi_image_generate",
+                    "trace": "(line 401)  torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 22.30 GiB of which 704.00 KiB is free. Process 36943 has 22.29 GiB memory in use. Of the allocated memory 21.79 GiB is allocated by PyTorch, and 10.51 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"
+                }
+            ]
+        },
+        "job_link": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202047",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202143"
+        },
+        "captured_info": {
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202047#step:16:1",
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202143#step:16:1"
+        }
+    },
+    "models_oneformer": {
+        "failed": {
+            "PyTorch": {
+                "unclassified": 0,
+                "single": 2,
+                "multi": 2
+            },
+            "Tokenizers": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Pipelines": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Trainer": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "ONNX": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Auto": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Quantization": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            },
+            "Unclassified": {
+                "unclassified": 0,
+                "single": 0,
+                "multi": 0
+            }
+        },
+        "errors": 0,
+        "success": 183,
+        "skipped": 247,
+        "time_spent": [
+            64.65,
+            57.35
+        ],
+        "error": false,
+        "failures": {
+            "multi": [
+                {
+                    "line": "tests/models/oneformer/test_modeling_oneformer.py::OneFormerModelIntegrationTest::test_inference_no_head",
+                    "trace": "(line 530)  AssertionError: Tensor-likes are not close!"
+                },
+                {
+                    "line": "tests/models/oneformer/test_modeling_oneformer.py::OneFormerModelIntegrationTest::test_inference_universal_segmentation_head",
+                    "trace": "(line 572)  AssertionError: Tensor-likes are not close!"
+                }
+            ],
+            "single": [
+                {
+                    "line": "tests/models/oneformer/test_modeling_oneformer.py::OneFormerModelIntegrationTest::test_inference_no_head",
+                    "trace": "(line 530)  AssertionError: Tensor-likes are not close!"
+                },
+                {
+                    "line": "tests/models/oneformer/test_modeling_oneformer.py::OneFormerModelIntegrationTest::test_inference_universal_segmentation_head",
+                    "trace": "(line 572)  AssertionError: Tensor-likes are not close!"
+                }
+            ]
+        },
+        "job_link": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202205",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202048"
+        },
+        "captured_info": {
+            "multi": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202205#step:16:1",
+            "single": "https://github.com/huggingface/transformers/actions/runs/19731275109/job/56533202048#step:16:1"
+        }
+    }
+}