SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Skip tests properly (#31308)

Browse Source 
* Skip tests properly

* [test_all]

* Add 'reason' as kwarg for skipTest

* [test_all] Fix up

* [test_all]
This commit is contained in:
amyeroberts
2024-06-26 21:59:08 +01:00
committed by GitHub
parent 1f9f57ab4c
commit 1de7dc7403
254 changed files with 1721 additions and 1298 deletions
Download Patch File Download Diff File Expand all files Collapse all files

32
tests/models/encodec/test_modeling_encodec.py
View File

@@ -178,29 +178,35 @@ class EncodecModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
expected_arg_names = ["input_values", "padding_mask", "bandwidth"]
self.assertListEqual(arg_names[: len(expected_arg_names)], expected_arg_names)
@unittest.skip("The EncodecModel is not transformers based, thus it does not have `inputs_embeds` logics")
@unittest.skip(reason="The EncodecModel is not transformers based, thus it does not have `inputs_embeds` logics")
def test_inputs_embeds(self):
pass
@unittest.skip("The EncodecModel is not transformers based, thus it does not have `inputs_embeds` logics")
@unittest.skip(reason="The EncodecModel is not transformers based, thus it does not have `inputs_embeds` logics")
def test_model_get_set_embeddings(self):
pass
@unittest.skip("The EncodecModel is not transformers based, thus it does not have the usual `attention` logic")
@unittest.skip(
reason="The EncodecModel is not transformers based, thus it does not have the usual `attention` logic"
)
def test_retain_grad_hidden_states_attentions(self):
pass
@unittest.skip("The EncodecModel is not transformers based, thus it does not have the usual `attention` logic")
@unittest.skip(
reason="The EncodecModel is not transformers based, thus it does not have the usual `attention` logic"
)
def test_torchscript_output_attentions(self):
pass
@unittest.skip("The EncodecModel is not transformers based, thus it does not have the usual `hidden_states` logic")
@unittest.skip(
reason="The EncodecModel is not transformers based, thus it does not have the usual `hidden_states` logic"
)
def test_torchscript_output_hidden_state(self):
pass
def _create_and_check_torchscript(self, config, inputs_dict):
if not self.test_torchscript:
return
self.skipTest(reason="test_torchscript is set to False")
configs_no_init = _config_zero_init(config) # To be sure we have no Nan
configs_no_init.torchscript = True
@@ -288,7 +294,9 @@ class EncodecModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
# (Even with this call, there are still memory leak by ~0.04MB)
self.clear_torch_jit_class_registry()
@unittest.skip("The EncodecModel is not transformers based, thus it does not have the usual `attention` logic")
@unittest.skip(
reason="The EncodecModel is not transformers based, thus it does not have the usual `attention` logic"
)
def test_attention_outputs(self):
pass
@@ -321,19 +329,21 @@ class EncodecModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
hidden_states_with_chunk = model(**inputs)[0]
self.assertTrue(torch.allclose(hidden_states_no_chunk, hidden_states_with_chunk, atol=1e-3))
@unittest.skip("The EncodecModel is not transformers based, thus it does not have the usual `hidden_states` logic")
@unittest.skip(
reason="The EncodecModel is not transformers based, thus it does not have the usual `hidden_states` logic"
)
def test_hidden_states_output(self):
pass
@unittest.skip("No support for low_cpu_mem_usage=True.")
@unittest.skip(reason="No support for low_cpu_mem_usage=True.")
def test_save_load_low_cpu_mem_usage(self):
pass
@unittest.skip("No support for low_cpu_mem_usage=True.")
@unittest.skip(reason="No support for low_cpu_mem_usage=True.")
def test_save_load_low_cpu_mem_usage_checkpoints(self):
pass
@unittest.skip("No support for low_cpu_mem_usage=True.")
@unittest.skip(reason="No support for low_cpu_mem_usage=True.")
def test_save_load_low_cpu_mem_usage_no_safetensors(self):
pass