[CI-test_torch] skip test_tf_from_pt_safetensors and `test_assisted…

…_decoding_sample` (huggingface#27508)

* skip 4 tests

* nits

* style

* wow it's not my day

* skip new failing tests

* style

* skip for NLLB MoE as well

tests/models/nllb_moe/test_modeling_nllb_moe.py

@@ -348,6 +348,10 @@ def test_get_loss(self):
         self.assertIsNotNone(model(**input_dict)["encoder_router_logits"][1])
         self.assertIsNotNone(model(**input_dict)["decoder_router_logits"][0])
 
+    @unittest.skip("Test does not fail individually but fails on the CI @ArthurZucker looking into it")
+    def test_assisted_decoding_sample(self):
+        pass
+
 
 @require_torch
 @require_sentencepiece

tests/models/speech_to_text/test_modeling_speech_to_text.py

@@ -759,6 +759,10 @@ def test_pt_tf_model_equivalence(self, allow_missing_keys=True):
         # Allow missing keys since TF doesn't cache the sinusoidal embeddings in an attribute
         super().test_pt_tf_model_equivalence(allow_missing_keys=allow_missing_keys)
 
+    @unittest.skip("Test failing,  @RocketNight is looking into it")
+    def test_tf_from_pt_safetensors(self):
+        pass
+
 
 @require_torch
 @require_torchaudio

tests/models/switch_transformers/test_modeling_switch_transformers.py

@@ -726,6 +726,10 @@ def test_generate_with_head_masking(self):
     def test_disk_offload(self):
         pass
 
+    @unittest.skip("Test does not fail individually but fails on the CI @ArthurZucker looking into it")
+    def test_assisted_decoding_sample(self):
+        pass
+
 
 class SwitchTransformersEncoderOnlyModelTester:
     def __init__(

tests/models/t5/test_modeling_t5.py

@@ -1036,6 +1036,10 @@ def test_model_fp16_forward(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model_fp16_forward(*config_and_inputs)
 
+    @unittest.skip("Test does not fail individually but fails on the CI @ArthurZucker looking into it")
+    def test_assisted_decoding_sample(self):
+        pass
+
 
 def use_task_specific_params(model, task):
     model.config.update(model.config.task_specific_params[task])