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device agnostic models testing (#27146)

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* device agnostic models testing

* add decorator `require_torch_fp16`

* make style

* apply review suggestion

* Oops, the fp16 decorator was misused
This commit is contained in:
Hz, Ji
2023-11-01 01:12:14 +08:00
committed by GitHub
parent 77930f8a01
commit 50378cbf6c
51 changed files with 369 additions and 154 deletions
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20
tests/models/bark/test_modeling_bark.py
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@@ -32,7 +32,13 @@ from transformers.models.bark.generation_configuration_bark import (
BarkFineGenerationConfig,
BarkSemanticGenerationConfig,
)
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from transformers.testing_utils import (
require_torch,
require_torch_fp16,
require_torch_gpu,
slow,
torch_device,
)
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTesterMixin
@@ -570,13 +576,13 @@ class BarkSemanticModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Te
with torch.no_grad():
model(**inputs)[0]
@require_torch_fp16
def test_generate_fp16(self):
config, input_dict = self.model_tester.prepare_config_and_inputs()
input_ids = input_dict["input_ids"]
attention_mask = input_ids.ne(1).to(torch_device)
model = self.all_generative_model_classes[0](config).eval().to(torch_device)
if torch_device == "cuda":
model.half()
model.half()
model.generate(input_ids, attention_mask=attention_mask)
model.generate(num_beams=4, do_sample=True, early_stopping=False, num_return_sequences=3)
@@ -636,13 +642,13 @@ class BarkCoarseModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Test
with torch.no_grad():
model(**inputs)[0]
@require_torch_fp16
def test_generate_fp16(self):
config, input_dict = self.model_tester.prepare_config_and_inputs()
input_ids = input_dict["input_ids"]
attention_mask = input_ids.ne(1).to(torch_device)
model = self.all_generative_model_classes[0](config).eval().to(torch_device)
if torch_device == "cuda":
model.half()
model.half()
model.generate(input_ids, attention_mask=attention_mask)
model.generate(num_beams=4, do_sample=True, early_stopping=False, num_return_sequences=3)
@@ -700,14 +706,14 @@ class BarkFineModelTest(ModelTesterMixin, unittest.TestCase):
with torch.no_grad():
model(**inputs)[0]
@require_torch_fp16
def test_generate_fp16(self):
config, input_dict = self.model_tester.prepare_config_and_inputs()
input_ids = input_dict["input_ids"]
# take first codebook channel
model = self.all_model_classes[0](config).eval().to(torch_device)
if torch_device == "cuda":
model.half()
model.half()
# toy generation_configs
semantic_generation_config = BarkSemanticGenerationConfig(semantic_vocab_size=0)