lint

titaiwangms · titaiwangms · commit c84d3f70b791 · 2025-07-18T18:11:14.000Z
diff --git a/_doc/examples/plot_export_tiny_phi2.py b/_doc/examples/plot_export_tiny_phi2.py
@@ -89,7 +89,6 @@
 
 
 with torch_export_patches(patch_transformers=True):
-
     # Two unnecessary steps but useful in case of an error
     # We check the cache is registered.
     assert is_cache_dynamic_registered()
diff --git a/_unittests/ut_export/test_shape_helper.py b/_unittests/ut_export/test_shape_helper.py
@@ -16,7 +16,6 @@
 
 
 class TestShapeHelper(ExtTestCase):
-
     @requires_transformers("4.52")
     @requires_torch("2.7.99")
     def test_all_dynamic_shape_from_cache(self):
diff --git a/_unittests/ut_helpers/test_onnx_helper.py b/_unittests/ut_helpers/test_onnx_helper.py
@@ -26,7 +26,6 @@
 
 
 class TestOnnxHelper(ExtTestCase):
-
     def _get_model(self):
         model = oh.make_model(
             oh.make_graph(
diff --git a/_unittests/ut_helpers/test_ort_session.py b/_unittests/ut_helpers/test_ort_session.py
@@ -24,7 +24,6 @@
 
 
 class TestOrtSession(ExtTestCase):
-
     @classmethod
     def _range(cls, *shape, bias: Optional[float] = None):
         n = np.prod(shape)
diff --git a/_unittests/ut_helpers/test_ort_session_tinyllm.py b/_unittests/ut_helpers/test_ort_session_tinyllm.py
@@ -19,7 +19,6 @@
 
 
 class TestOrtSessionTinyLLM(ExtTestCase):
-
     def test_ort_value(self):
         val = np.array([30, 31, 32], dtype=np.int64)
         ort = ORTC.OrtValue.ortvalue_from_numpy_with_onnx_type(val, onnx.TensorProto.INT64)
diff --git a/_unittests/ut_helpers/test_torch_helper.py b/_unittests/ut_helpers/test_torch_helper.py
@@ -32,7 +32,6 @@
 
 
 class TestTorchTestHelper(ExtTestCase):
-
     def test_is_torchdynamo_exporting(self):
         self.assertFalse(is_torchdynamo_exporting())
 
diff --git a/_unittests/ut_reference/test_onnxruntime_evaluator.py b/_unittests/ut_reference/test_onnxruntime_evaluator.py
@@ -23,7 +23,6 @@
 
 class TestOnnxruntimeEvaluator(ExtTestCase):
     def test_ort_eval_scan_cdist_add(self):
-
         def dist(unused: torch.Tensor, x: torch.Tensor, samex: torch.Tensor):
             sub = samex - x.reshape((1, -1))
             sq = sub * sub
diff --git a/_unittests/ut_torch_export_patches/test_dynamic_class.py b/_unittests/ut_torch_export_patches/test_dynamic_class.py
@@ -227,7 +227,6 @@ def unflatten_my_cache_78(values, context: TreeContext, output_type=None) -> MyC
 
     @ignore_warnings(UserWarning)
     def test_export_dynamic_cache_cat(self):
-
         class ModelDynamicCache(torch.nn.Module):
             def forward(self, x, dc):
                 y = (
diff --git a/_unittests/ut_torch_export_patches/test_patch_expressions.py b/_unittests/ut_torch_export_patches/test_patch_expressions.py
@@ -11,7 +11,6 @@
 
 
 class TestOnnxExportErrors(ExtTestCase):
-
     @classmethod
     def setUp(cls):
         register_patched_expressions()
diff --git a/_unittests/ut_torch_export_patches/test_patch_loops.py b/_unittests/ut_torch_export_patches/test_patch_loops.py
@@ -14,15 +14,13 @@
 
 
 class TestOnnxExportErrors(ExtTestCase):
-
     def test_patched_expressions(self):
         res = list(_iterate_patched_expressions())
         names = {_[0] for _ in res}
         self.assertIn("float_arange", names)
 
     @requires_torch("2.8")
     def test_filter_position_ids(self):
-
         def filter_position_ids(
             patch_attention_mask: torch.Tensor,
             position_ids: torch.Tensor,
@@ -57,7 +55,6 @@ def scan_filter_position_ids(
             boundaries: torch.Tensor,
             num_patches_per_side: int,
         ):
-
             def body(p_attn_mask, position_ids_row):
                 h_len = torch.tensor(1) / p_attn_mask[:, 0].sum()
                 w_len = torch.tensor(1) / p_attn_mask[0].sum()
diff --git a/_unittests/ut_torch_export_patches/test_patch_module.py b/_unittests/ut_torch_export_patches/test_patch_module.py
@@ -48,7 +48,6 @@ def forward(self, x, y):
         ), f"Missing parent in {ast.dump(tree, indent=2)}"
 
     def test_rewrite_test_in_forward_return1(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -75,7 +74,6 @@ def forward(self, x, y):
 
     @hide_stdout()
     def test_rewrite_test_in_forward_return2(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -101,7 +99,6 @@ def forward(self, x, y):
         self.assertEqualAny(expected_, ep.module()(-x, y))
 
     def test_rewrite_test_in_forward_assign1(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -128,7 +125,6 @@ def forward(self, x, y):
         self.assertEqualArray(expected_, ep.module()(-x, y))
 
     def test_rewrite_test_in_forward_assign2(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -155,10 +151,8 @@ def forward(self, x, y):
         self.assertEqualAny(expected_, ep.module()(-x, y))
 
     def test_check_syntax_assign_noelse(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
-
                 def branch_cond_then_1(x):
                     x = torch.abs(x) + 1
                     return x
@@ -179,7 +173,6 @@ def branch_cond_else_1(x):
         self.assertEqualAny(expected_, ep.module()(-x, y))
 
     def test_rewrite_test_in_forward_assign_noelse(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -204,7 +197,6 @@ def forward(self, x, y):
         self.assertEqualAny(expected_, ep.module()(-x, y))
 
     def test_rewrite_test_in_forward_return_noelse(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -216,7 +208,6 @@ def forward(self, x, y):
         )
 
     def test_rewrite_test_in_forward_assign2_in_2(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -245,7 +236,6 @@ def forward(self, x, y):
         self.assertEqualAny(expected_, ep.module()(-x, y))
 
     def test_rewrite_test_in_forward_assign2_in_3(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -277,13 +267,11 @@ def forward(self, x, y):
         self.assertEqualAny(expected_, ep.module()(-x, y))
 
     def test_assign_nested_check(self):
-
         torch_cond = torch.cond
 
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 def torch_cond_then_3(y, x):
-
                     def torch_cond_then_1(y, x):
                         w = x + y
                         z = x - y
@@ -301,7 +289,6 @@ def torch_cond_else_1(y, x):
                     return (w, z)
 
                 def torch_cond_else_3(y, x):
-
                     def torch_cond_then_2(y):
                         u = y + 1
                         return u
@@ -322,7 +309,6 @@ def torch_cond_else_2(y):
         Model()(x, y)
 
     def test_rewrite_test_in_forward_assign_nested(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x.sum() > 0:
@@ -371,7 +357,6 @@ def forward(self, x, y):
         self.assertEqualAny(expected_1, ep.module()(-x, -y))
 
     def test_rewrite_test_in_forward_none(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 if x is None:
@@ -513,7 +498,6 @@ def test__find_loop_vars(self):
 
     @requires_torch("2.8")
     def test_rewrite_loop(self):
-
         class Model(torch.nn.Module):
             def forward(self, x, y):
                 z = torch.empty((x.shape[0], y.shape[0]))
diff --git a/_unittests/ut_torch_models/test_hghub_api.py b/_unittests/ut_torch_models/test_hghub_api.py
@@ -27,7 +27,6 @@
 
 
 class TestHuggingFaceHubApi(ExtTestCase):
-
     @requires_transformers("4.50")  # we limit to some versions of the CI
     @requires_torch("2.7")
     @ignore_errors(OSError)  # connectivity issues
diff --git a/_unittests/ut_torch_models/test_hghub_mode_rewrite.py b/_unittests/ut_torch_models/test_hghub_mode_rewrite.py
@@ -13,7 +13,6 @@
 
 
 class TestHuggingFaceHubModelRewrite(ExtTestCase):
-
     def test_code_needing_rewriting(self):
         self.assertEqual(2, len(code_needing_rewriting("BartForConditionalGeneration")))
 
diff --git a/_unittests/ut_torch_models/test_tiny_llms_bypassed.py b/_unittests/ut_torch_models/test_tiny_llms_bypassed.py
@@ -28,7 +28,6 @@ def test_export_tiny_llm_2_bypassed(self):
         with torch_export_patches(
             patch_torch=False, patch_transformers=True, catch_constraints=False, verbose=10
         ) as modificator:
-
             for k in patched_DynamicCache._PATCHES_:
                 self.assertEqual(getattr(patched_DynamicCache, k), getattr(DynamicCache, k))
 
diff --git a/_unittests/ut_torch_onnx/test_sbs.py b/_unittests/ut_torch_onnx/test_sbs.py
@@ -15,7 +15,6 @@
 
 
 class TestSideBySide(ExtTestCase):
-
     @hide_stdout()
     @unittest.skipIf(to_onnx is None, "to_onnx not installed")
     @ignore_errors(OSError)  # connectivity issues
diff --git a/_unittests/ut_xrun_doc/test_doc_doc.py b/_unittests/ut_xrun_doc/test_doc_doc.py
@@ -4,7 +4,6 @@
 
 
 class TestDocDoc(ExtTestCase):
-
     def test_reset(self):
         reset_torch_transformers(None, None)
 
diff --git a/onnx_diagnostic/helpers/ort_session.py b/onnx_diagnostic/helpers/ort_session.py
@@ -19,7 +19,6 @@
 
 
 class _InferenceSession:
-
     @classmethod
     def has_onnxruntime_training(cls):
         """Tells if onnxruntime_training is installed."""
diff --git a/onnx_diagnostic/helpers/rt_helper.py b/onnx_diagnostic/helpers/rt_helper.py
@@ -79,7 +79,6 @@ def make_feeds(
     if len(names) < len(flat) and (
         isinstance(proto, onnx.ModelProto) or hasattr(proto, "get_inputs")
     ):
-
         typed_names = (
             [(i.name, i.type.tensor_type.elem_type) for i in proto.graph.input]
             if isinstance(proto, onnx.ModelProto)
diff --git a/onnx_diagnostic/helpers/torch_helper.py b/onnx_diagnostic/helpers/torch_helper.py
@@ -526,7 +526,6 @@ def forward(self, x):
             return word_emb + word_pe
 
     class AttentionBlock(torch.nn.Module):
-
         def __init__(self, embedding_dim: int = 16, context_size: int = 256):
             super().__init__()
             self.query = torch.nn.Linear(embedding_dim, embedding_dim, bias=False)
@@ -555,7 +554,6 @@ def forward(self, x):
             return out
 
     class MultiAttentionBlock(torch.nn.Module):
-
         def __init__(
             self, embedding_dim: int = 16, num_heads: int = 2, context_size: int = 256
         ):
@@ -573,7 +571,6 @@ def forward(self, x):
             return x
 
     class FeedForward(torch.nn.Module):
-
         def __init__(self, embedding_dim: int = 16, ff_dim: int = 128):
             super().__init__()
             self.linear_1 = torch.nn.Linear(embedding_dim, ff_dim)
@@ -587,7 +584,6 @@ def forward(self, x):
             return x
 
     class DecoderLayer(torch.nn.Module):
-
         def __init__(
             self,
             embedding_dim: int = 16,
@@ -613,7 +609,6 @@ def forward(self, x):
             return ff
 
     class LLM(torch.nn.Module):
-
         def __init__(
             self,
             vocab_size: int = 1024,
diff --git a/onnx_diagnostic/reference/ops/op_scan.py b/onnx_diagnostic/reference/ops/op_scan.py
@@ -3,7 +3,6 @@
 
 
 class Scan(_Scan):
-
     def need_context(self) -> bool:
         """Tells the runtime if this node needs the context
         (all the results produced so far) as it may silently access
diff --git a/onnx_diagnostic/torch_export_patches/eval/model_cases.py b/onnx_diagnostic/torch_export_patches/eval/model_cases.py
@@ -358,7 +358,6 @@ class ControlFlowCondIdentity_153832(torch.nn.Module):
     """
 
     def forward(self, x, y):
-
         def branch_cond_then_1(x):
             x = torch.abs(x) + 1
             return x
@@ -789,7 +788,6 @@ def forward(self, x):
 
 
 class CropLastDimensionWithTensorShape(torch.nn.Module):
-
     def forward(self, x, y):
         return x[..., : y.shape[0]]
 
diff --git a/onnx_diagnostic/torch_export_patches/patch_module_helper.py b/onnx_diagnostic/torch_export_patches/patch_module_helper.py
@@ -22,7 +22,6 @@ def ast_or_into_bitor(node: "ast.Node") -> "ast.Node":
 
 @functools.lru_cache
 def _rewrite_forward_clamp_float16() -> Dict[str, List[type]]:
-
     import transformers
 
     _known = {
diff --git a/onnx_diagnostic/torch_export_patches/patches/patch_torch.py b/onnx_diagnostic/torch_export_patches/patches/patch_torch.py
@@ -166,7 +166,6 @@ def patched__broadcast_shapes(*_shapes):
 
 
 class patched_ShapeEnv:
-
     def _check_frozen(
         self, expr: "sympy.Basic", concrete_val: "sympy.Basic"  # noqa: F821
     ) -> None:
diff --git a/onnx_diagnostic/torch_export_patches/patches/patch_transformers.py b/onnx_diagnostic/torch_export_patches/patches/patch_transformers.py
@@ -1103,9 +1103,11 @@ def forward(
                 .transpose(1, 2)
             )
         else:
-            _, kv_len, _ = (
-                key_value_states.size()
-            )  # Note that, in this case, `kv_len` == `kv_seq_len`
+            (
+                _,
+                kv_len,
+                _,
+            ) = key_value_states.size()  # Note that, in this case, `kv_len` == `kv_seq_len`
             key_states = (
                 self.k_proj(key_value_states)
                 .view(bsz, kv_len, self.num_heads, self.head_dim)
@@ -1127,10 +1129,11 @@ def forward(
                 torch.tensor(q_len, dtype=torch.int64),
             )
             cos, sin = self.rotary_emb(value_states, seq_len=rotary_length)
-            query_states, key_states = (
-                transformers.models.idefics.modeling_idefics.apply_rotary_pos_emb(
-                    query_states, key_states, cos, sin, position_ids
-                )
+            (
+                query_states,
+                key_states,
+            ) = transformers.models.idefics.modeling_idefics.apply_rotary_pos_emb(
+                query_states, key_states, cos, sin, position_ids
             )
         # [bsz, nh, t, hd]
 
diff --git a/onnx_diagnostic/torch_export_patches/serialization/transformers_impl.py b/onnx_diagnostic/torch_export_patches/serialization/transformers_impl.py
diff --git a/onnx_diagnostic/torch_models/hghub/model_inputs.py b/onnx_diagnostic/torch_models/hghub/model_inputs.py
diff --git a/onnx_diagnostic/torch_models/validate.py b/onnx_diagnostic/torch_models/validate.py
