device agnostic models testing (#27146)

* 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

View File

@@ -18,7 +18,12 @@ import tempfile
import unittest
from transformers import BlenderbotSmallConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.testing_utils import (
require_torch,
require_torch_fp16,
slow,
torch_device,
)
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTesterMixin
@@ -269,13 +274,13 @@ class BlenderbotSmallModelTest(ModelTesterMixin, GenerationTesterMixin, Pipeline
config_and_inputs = self.model_tester.prepare_config_and_inputs_for_common()
self.model_tester.check_encoder_decoder_model_standalone(*config_and_inputs)
@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 = BlenderbotSmallForConditionalGeneration(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)