Tests: move generate tests to the right mixin and delete redundant tests (#34464)

* tmp commit

* tmp commit

* cull overwrites of deleted tests

* typo

* more specific docstring

* make fixup

* parameterize at the top?

* correction

* more deletions :D

* tmp commit

* for VLMs too

* fix _check_outputs

* test nit

* make fixup

* fix another flaky

* test_generate_from_inputs_embeds -- handle missing attention mask

tests/models/glm/test_modeling_glm.py

@@ -28,7 +28,6 @@ from transformers.testing_utils import (
     require_flash_attn,
     require_torch,
     require_torch_accelerator,
-    require_torch_gpu,
     require_torch_sdpa,
     slow,
     torch_device,
@@ -306,10 +305,6 @@ class GlmModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
     test_headmasking = False
     test_pruning = False
 
-    # used in `test_torch_compile`
-    _torch_compile_test_ckpt = "THUDM/glm-4-9b"
-    _torch_compile_test_revision = "refs/pr/15"
-
     def setUp(self):
         self.model_tester = GlmModelTester(self)
         self.config_tester = ConfigTester(self, config_class=GlmConfig, hidden_size=37)
@@ -426,41 +421,6 @@ class GlmModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
 
             torch.testing.assert_close(normalized_0, normalized_1, rtol=1e-3, atol=1e-3)
 
-    @require_flash_attn
-    @require_torch_gpu
-    @pytest.mark.flash_attn_test
-    @slow
-    def test_flash_attn_2_generate_padding_right(self):
-        """Overwrite the common test as the test is flaky on tiny models."""
-        model = GlmForCausalLM.from_pretrained(
-            "THUDM/glm-4-9b",
-            device_map={"": 0},
-            torch_dtype=torch.bfloat16,
-            revision="refs/pr/15",
-        )
-
-        tokenizer = AutoTokenizer.from_pretrained("THUDM/glm-4-9b", revision="refs/pr/15")
-        tokenizer.padding_side = "right"
-
-        texts = ["hi", "Hello this is a very long sentence"]
-        inputs = tokenizer(texts, return_tensors="pt", padding=True).to(0)
-
-        output_native = model.generate(**inputs, max_new_tokens=15, do_sample=False)
-        output_native = tokenizer.batch_decode(output_native)
-
-        model = GlmForCausalLM.from_pretrained(
-            "THUDM/glm-4-9b",
-            device_map={"": 0},
-            attn_implementation="flash_attention_2",
-            torch_dtype=torch.bfloat16,
-            revision="refs/pr/15",
-        )
-
-        output_fa_2 = model.generate(**inputs, max_new_tokens=15, do_sample=False)
-        output_fa_2 = tokenizer.batch_decode(output_fa_2)
-
-        self.assertListEqual(output_native, output_fa_2)
-
     @parameterized.expand([("float16",), ("bfloat16",), ("float32",)])
     @require_torch_sdpa
     @slow