From 7f9aff910b8fb0b1a2cec97298d1b121ef35d78a Mon Sep 17 00:00:00 2001 From: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Date: Mon, 8 Apr 2024 13:29:20 +0100 Subject: [PATCH] Patch fix - don't use safetensors for TF models (#30118) * Patch fix - don't use safetensors for TF models * Skip test for TF for now * Update for another test --- tests/generation/test_framework_agnostic.py | 8 ++++---- tests/generation/test_tf_utils.py | 2 +- tests/pipelines/test_pipelines_text_generation.py | 1 + 3 files changed, 6 insertions(+), 5 deletions(-) diff --git a/tests/generation/test_framework_agnostic.py b/tests/generation/test_framework_agnostic.py index f4f13dd8d5..85a58bdf28 100644 --- a/tests/generation/test_framework_agnostic.py +++ b/tests/generation/test_framework_agnostic.py @@ -111,7 +111,7 @@ class GenerationIntegrationTestsMixin: article = """Justin Timberlake.""" gpt2_tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2") - gpt2_model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2") + gpt2_model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2", use_safetensors=is_pt) input_ids = gpt2_tokenizer(article, return_tensors=return_tensors).input_ids if is_pt: gpt2_model = gpt2_model.to(torch_device) @@ -582,7 +582,7 @@ class GenerationIntegrationTestsMixin: tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2") text = """Hello, my dog is cute and""" tokens = tokenizer(text, return_tensors=return_tensors) - model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2") + model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2", use_safetensors=is_pt) if is_pt: model = model.to(torch_device) tokens = tokens.to(torch_device) @@ -611,7 +611,7 @@ class GenerationIntegrationTestsMixin: tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2") text = """Hello, my dog is cute and""" tokens = tokenizer(text, return_tensors=return_tensors) - model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2") + model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2", use_safetensors=is_pt) if is_pt: model = model.to(torch_device) tokens = tokens.to(torch_device) @@ -638,7 +638,7 @@ class GenerationIntegrationTestsMixin: tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2") text = """Hello, my dog is cute and""" tokens = tokenizer(text, return_tensors=return_tensors) - model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2") + model = model_cls.from_pretrained("hf-internal-testing/tiny-random-gpt2", use_safetensors=is_pt) if is_pt: model = model.to(torch_device) tokens = tokens.to(torch_device) diff --git a/tests/generation/test_tf_utils.py b/tests/generation/test_tf_utils.py index f40ceebef7..73eba05ece 100644 --- a/tests/generation/test_tf_utils.py +++ b/tests/generation/test_tf_utils.py @@ -194,7 +194,7 @@ class TFGenerationIntegrationTests(unittest.TestCase, GenerationIntegrationTests tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2") text = """Hello, my dog is cute and""" tokens = tokenizer(text, return_tensors="tf") - model = TFAutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-random-gpt2") + model = TFAutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-random-gpt2", use_safetensors=False) eos_token_id = 638 # forces the generation to happen on CPU, to avoid GPU-related quirks diff --git a/tests/pipelines/test_pipelines_text_generation.py b/tests/pipelines/test_pipelines_text_generation.py index ada04c7dbe..318526b850 100644 --- a/tests/pipelines/test_pipelines_text_generation.py +++ b/tests/pipelines/test_pipelines_text_generation.py @@ -268,6 +268,7 @@ class TextGenerationPipelineTests(unittest.TestCase): text_generator = TextGenerationPipeline(model=model, tokenizer=tokenizer) return text_generator, ["This is a test", "Another test"] + @require_torch # See https://github.com/huggingface/transformers/issues/30117 def test_stop_sequence_stopping_criteria(self): prompt = """Hello I believe in""" text_generator = pipeline("text-generation", model="hf-internal-testing/tiny-random-gpt2")