Lint & Format fixed II

Signed-off-by: Abukhoyer Shaik <[email protected]>

tests/qnn_tests/test_causal_lm_models_qnn.py

@@ -88,9 +88,9 @@ def check_causal_lm_pytorch_vs_kv_vs_ort_vs_ai100(
 
     pytorch_kv_tokens = api_runner.run_kv_model_on_pytorch(qeff_model.model)
 
-    assert (
-        pytorch_hf_tokens == pytorch_kv_tokens
-    ).all(), "Tokens don't match for HF PyTorch model output and KV PyTorch model output"
+    assert (pytorch_hf_tokens == pytorch_kv_tokens).all(), (
+        "Tokens don't match for HF PyTorch model output and KV PyTorch model output"
+    )
 
     onnx_model_path = qeff_model.export()
     ort_tokens = api_runner.run_kv_model_on_ort(onnx_model_path)
@@ -112,9 +112,9 @@ def check_causal_lm_pytorch_vs_kv_vs_ort_vs_ai100(
     exec_info = qeff_model.generate(tokenizer, prompts=Constants.INPUT_STR)
     cloud_ai_100_tokens = exec_info.generated_ids[0]  # Because we always run for single input and single batch size
     gen_len = ort_tokens.shape[-1]
-    assert (
-        ort_tokens == cloud_ai_100_tokens[:, :gen_len]
-    ).all(), "Tokens don't match for ONNXRT output and Cloud AI 100 output."
+    assert (ort_tokens == cloud_ai_100_tokens[:, :gen_len]).all(), (
+        "Tokens don't match for ONNXRT output and Cloud AI 100 output."
+    )
 
     # testing for CB models
     model_hf, _ = load_causal_lm_model(model_config)

tests/transformers/models/test_causal_lm_models.py

@@ -111,9 +111,9 @@ def check_causal_lm_pytorch_vs_kv_vs_ort_vs_ai100(
 
     pytorch_kv_tokens = api_runner.run_kv_model_on_pytorch(qeff_model.model)
 
-    assert (
-        pytorch_hf_tokens == pytorch_kv_tokens
-    ).all(), "Tokens don't match for HF PyTorch model output and KV PyTorch model output"
+    assert (pytorch_hf_tokens == pytorch_kv_tokens).all(), (
+        "Tokens don't match for HF PyTorch model output and KV PyTorch model output"
+    )
 
     onnx_model_path = qeff_model.export()
     ort_tokens = api_runner.run_kv_model_on_ort(onnx_model_path, is_tlm=is_tlm)
@@ -135,9 +135,9 @@ def check_causal_lm_pytorch_vs_kv_vs_ort_vs_ai100(
     exec_info = qeff_model.generate(tokenizer, prompts=Constants.INPUT_STR)
     cloud_ai_100_tokens = exec_info.generated_ids[0]  # Because we always run for single input and single batch size
     gen_len = ort_tokens.shape[-1]
-    assert (
-        ort_tokens == cloud_ai_100_tokens[:, :gen_len]
-    ).all(), "Tokens don't match for ONNXRT output and Cloud AI 100 output."
+    assert (ort_tokens == cloud_ai_100_tokens[:, :gen_len]).all(), (
+        "Tokens don't match for ONNXRT output and Cloud AI 100 output."
+    )
 
     # testing for CB models
     model_hf, _ = load_causal_lm_model(model_config)
@@ -206,9 +206,9 @@ def test_causal_lm_export_with_deprecated_api(model_name):
     new_api_ort_tokens = api_runner.run_kv_model_on_ort(new_api_onnx_model_path)
     old_api_ort_tokens = api_runner.run_kv_model_on_ort(old_api_onnx_model_path)
 
-    assert (
-        new_api_ort_tokens == old_api_ort_tokens
-    ).all(), "New API output does not match old API output for ONNX export function"
+    assert (new_api_ort_tokens == old_api_ort_tokens).all(), (
+        "New API output does not match old API output for ONNX export function"
+    )
 
 
 @pytest.mark.on_qaic