update black

_doc/examples/plot_dump_intermediate_results.py

@@ -32,7 +32,6 @@
 from onnx_diagnostic.helpers.mini_onnx_builder import create_input_tensors_from_onnx_model
 from onnx_diagnostic.reference import OnnxruntimeEvaluator, ReportResultComparison
 
-
 model, inputs, ds = dummy_llm(dynamic_shapes=True)
 
 # %%

_doc/examples/plot_export_tiny_llm.py

@@ -35,7 +35,6 @@
 from onnx_diagnostic.torch_models.llms import get_tiny_llm
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
-
 MODEL_NAME = "arnir0/Tiny-LLM"
 tokenizer = transformers.AutoTokenizer.from_pretrained(MODEL_NAME)
 model = transformers.AutoModelForCausalLM.from_pretrained(MODEL_NAME)

_doc/examples/plot_export_tiny_llm_dim01.py

@@ -30,7 +30,6 @@
     register_additional_serialization_functions,
 )
 
-
 data = get_untrained_model_with_inputs("arnir0/Tiny-LLM", add_second_input=True)
 model, dynamic_shapes = data["model"], data["dynamic_shapes"]
 

_doc/examples/plot_export_tiny_llm_dim01_onnx.py

@@ -30,7 +30,6 @@
     register_additional_serialization_functions,
 )
 
-
 data = get_untrained_model_with_inputs("arnir0/Tiny-LLM", add_second_input=True)
 model, dynamic_shapes = data["model"], data["dynamic_shapes"]
 

_doc/examples/plot_export_tiny_llm_dim01_onnx_custom.py

@@ -29,7 +29,6 @@
 )
 from experimental_experiment.torch_interpreter import to_onnx, ExportOptions
 
-
 data = get_untrained_model_with_inputs("arnir0/Tiny-LLM", add_second_input=True)
 model, dynamic_shapes = data["model"], data["dynamic_shapes"]
 

_doc/examples/plot_export_tiny_llm_method_generate.py

@@ -22,7 +22,6 @@
 from onnx_diagnostic import doc
 from onnx_diagnostic.export.api import method_to_onnx
 
-
 MODEL_NAME = "arnir0/Tiny-LLM"
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)

_doc/examples/plot_export_tiny_llm_patched.py

@@ -73,7 +73,6 @@
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 from onnx_diagnostic.torch_models.llms import get_tiny_llm
 
-
 experiment = get_tiny_llm()
 untrained_model, inputs, dynamic_shapes = (
     experiment["model"],

_doc/recipes/plot_export_cond.py

@@ -16,7 +16,6 @@
 from onnx_diagnostic import doc
 from onnx_diagnostic.torch_export_patches import torch_export_rewrite
 
-
 # %%
 # We define a model with a control flow (-> graph break)
 

_doc/technical/plot_generate.py

@@ -32,7 +32,6 @@
 from onnx_diagnostic.tasks import random_input_kwargs
 from onnx_diagnostic.export.api import to_onnx
 
-
 device = "cuda" if torch.cuda.is_available() else "cpu"
 data = []
 

_unittests/ut_helpers/test_dot_helper.py

@@ -38,8 +38,7 @@ def test_custom_doc_kernels_layer_normalization(self):
             opset_imports=[oh.make_opsetid("", 18)],
         )
         dot = to_dot(model)
-        expected = textwrap.dedent(
-            """
+        expected = textwrap.dedent("""
             digraph {
               graph [rankdir=TB, splines=true, overlap=false, nodesep=0.2, ranksep=0.2, fontsize=8];
               node [style="rounded,filled", color="#888888", fontcolor="#222222", shape=box];
@@ -57,8 +56,7 @@ def test_custom_doc_kernels_layer_normalization(self):
               O_5 [label="Z\\nFLOAT16(b,c,d)", fillcolor="#aaaaee"];
               Add_4 -> O_5;
             }
-            """
-        )
+            """)
         self.maxDiff = None
         self.assertEqual(expected.strip("\n "), dot.strip("\n "))
 
@@ -90,9 +88,7 @@ def test_custom_doc_kernels_layer_normalization_constant(self):
             opset_imports=[oh.make_opsetid("", 18)],
         )
         dot = to_dot(model)
-        expected = (
-            textwrap.dedent(
-                """
+        expected = textwrap.dedent("""
                 digraph {
                 graph [rankdir=TB, splines=true, overlap=false, nodesep=0.2, ranksep=0.2, fontsize=8];
                 node [style="rounded,filled", color="#888888", fontcolor="#222222", shape=box];
@@ -111,11 +107,7 @@ def test_custom_doc_kernels_layer_normalization_constant(self):
                 O_6 [label="Z\\nFLOAT16(b,c,d)", fillcolor="#aaaaee"];
                 Add_5 -> O_6;
                 }
-                """
-            )
-            .strip("\n")
-            .replace(" ", "")
-        )
+                """).strip("\n").replace(" ", "")
         self.maxDiff = None
         self.assertEqual(expected, dot.strip("\n").replace(" ", ""))
 

_unittests/ut_helpers/test_helper.py

@@ -51,7 +51,6 @@
 )
 from onnx_diagnostic.torch_models.hghub.hub_api import get_pretrained_config
 
-
 TFLOAT = onnx.TensorProto.FLOAT
 
 

_unittests/ut_helpers/test_log_helper.py

@@ -24,19 +24,13 @@
 class TestLogHelper(ExtTestCase):
     @classmethod
     def df1(cls):
-        return pandas.read_csv(
-            io.StringIO(
-                textwrap.dedent(
-                    """
+        return pandas.read_csv(io.StringIO(textwrap.dedent("""
                     date,version_python,version_transformers,model_name,model_exporter,time_load,time_latency,time_baseline,disc_ort,disc_ort2
                     2025/01/01,3.13.3,4.52.4,phi3,export,0.51,0.1,0.1,1e-5,1e-5
                     2025/01/02,3.13.3,4.52.4,phi3,export,0.62,0.11,0.11,1e-5,1e-5
                     2025/01/01,3.13.3,4.52.4,phi4,export,0.53,0.1,0.105,1e-5,1e-5
                     2025/01/01,3.12.3,4.52.4,phi4,onnx-dynamo,0.54,0.14,0.999,1e-5,1e-5
-                    """
-                )
-            )
-        )
+                    """)))
 
     @classmethod
     def cube1(cls, verbose=0):

_unittests/ut_helpers/test_onnx_helper.py

@@ -33,7 +33,6 @@
     _enumerate_model_node_outputs,
 )
 
-
 TFLOAT = TensorProto.FLOAT
 TINT64 = TensorProto.INT64
 

_unittests/ut_reference/test_torch_onnx_evaluator.py

@@ -16,7 +16,6 @@
 from onnx_diagnostic.reference.torch_ops import OpRunKernel, OpRunTensor
 from onnx_diagnostic.reference.torch_evaluator import get_kernels
 
-
 TFLOAT = onnx.TensorProto.FLOAT
 TFLOAT16 = onnx.TensorProto.FLOAT16
 TINT64 = onnx.TensorProto.INT64

_unittests/ut_torch_export_patches/test_patch_module.py

@@ -508,12 +508,10 @@ def test_shape_finder(self):
         self.assertEqual({"x"}, sh.found_shape)
 
     def test__find_loop_vars(self):
-        code = textwrap.dedent(
-            """
+        code = textwrap.dedent("""
             for i in range(x.shape[0]):
                 z[i, :] = ((x[i : i + 1, :] - y) ** 2).sum(dim=-1)
-            """
-        )
+            """)
         node = ast.parse(code)
         tr = RewriteControlFlow()
         vars = tr._find_loop_vars(node.body[0])

_unittests/ut_xrun_doc/test_documentation_examples.py

@@ -14,7 +14,6 @@
     ignore_errors,
 )
 
-
 VERBOSE = 0
 ROOT = os.path.realpath(os.path.abspath(os.path.join(onnx_diagnostic_file, "..", "..")))
 

_unittests/ut_xrun_doc/test_documentation_recipes.py

@@ -12,7 +12,6 @@
     ignore_errors,
 )
 
-
 VERBOSE = 0
 ROOT = os.path.realpath(os.path.abspath(os.path.join(onnx_diagnostic_file, "..", "..")))
 

_unittests/ut_xrun_doc/test_documentation_technical.py

@@ -13,7 +13,6 @@
     has_transformers,
 )
 
-
 VERBOSE = 0
 ROOT = os.path.realpath(os.path.abspath(os.path.join(onnx_diagnostic_file, "..", "..")))