adding markers

Signed-off-by: Onkar Chougule <[email protected]>

tests/finetune/test_finetune.py

@@ -26,6 +26,7 @@ def clean_up(path):
 
 
 # TODO:enable this once docker is available
+@pytest.mark.on_qaic
 @pytest.mark.skip(reason="eager docker not available in sdk")
 @pytest.mark.parametrize(
     "model_name,max_eval_step,max_train_step,intermediate_step_save,context_length,run_validation,use_peft,device",

tests/peft/lora/test_lora_model.py

@@ -229,6 +229,5 @@ def test_auto_lora_model_for_causal_lm_export_compile_generate(base_model_name,
     qeff_model.generate(
         tokenizer=load_hf_tokenizer(pretrained_model_name_or_path=base_model_name),
         prompts=prompts,
-        device_id=[0],
         prompt_to_adapter_mapping=["adapter_0", "adapter_1", "adapter_0", "base"],
     )

tests/text_generation/test_text_generation.py

@@ -44,6 +44,7 @@ def load_causal_lm_model(model_config):
 
 
 # Use @pytest.mark.parametrize to apply the configurations
+@pytest.mark.on_qaic
 @pytest.mark.parametrize("model_name, n_layer, full_batch_size, max_gen_len", configs)
 def test_generate_text_stream(
     model_name: str,

tests/transformers/spd/test_spd_inference.py

@@ -92,6 +92,7 @@ def split_dlm_bonus_token_inputs(dlm_decode_inputs):
     return bonus_token_inputs, dlm_decode_inputs
 
 
+@pytest.mark.on_qaic
 @pytest.mark.parametrize(
     "prompt, num_speculative_tokens, prefill_seq_len, ctx_len, prefill_bsz, draft_model_name, target_model_name, full_batch_size",
     configs,