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Generate: Fix CI related to #20727 #21003

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Merged
gante merged 2 commits into from
Jan 4, 2023
Merged

Generate: Fix CI related to #20727 #21003

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b3ddae3
silly pytorch
gante Jan 4, 2023
dd42b80
send the tokenizer to the device instead
gante Jan 4, 2023
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8 changes: 4 additions & 4 deletions tests/generation/test_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3035,7 +3035,7 @@ def test_eos_token_id_int_and_list_greedy_search(self):

tokenizer = GPT2Tokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
text = """Hello, my dog is cute and"""
tokens = tokenizer(text, return_tensors="pt")
tokens = tokenizer(text, return_tensors="pt").to(torch_device)

model = GPT2LMHeadModel.from_pretrained("hf-internal-testing/tiny-random-gpt2").to(torch_device)
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@ydshieh ydshieh Jan 4, 2023

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I feel it's better to keep it is, but change (line above)

tokens = tokenizer(text, return_tensors="pt")

to

tokens = tokenizer(text, return_tensors="pt").to(torch_device)

WDYT?

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@gante gante Jan 4, 2023

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TIL that can be done :D

Changed!


Expand All @@ -3060,7 +3060,7 @@ def test_eos_token_id_int_and_list_contrastive_search(self):

tokenizer = GPT2Tokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
text = """Hello, my dog is cute and"""
tokens = tokenizer(text, return_tensors="pt")
tokens = tokenizer(text, return_tensors="pt").to(torch_device)

model = GPT2LMHeadModel.from_pretrained("hf-internal-testing/tiny-random-gpt2").to(torch_device)

Expand All @@ -3086,7 +3086,7 @@ def test_eos_token_id_int_and_list_top_k_top_sampling(self):

tokenizer = GPT2Tokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
text = """Hello, my dog is cute and"""
tokens = tokenizer(text, return_tensors="pt")
tokens = tokenizer(text, return_tensors="pt").to(torch_device)

model = GPT2LMHeadModel.from_pretrained("hf-internal-testing/tiny-random-gpt2").to(torch_device)

Expand All @@ -3109,7 +3109,7 @@ def test_eos_token_id_int_and_list_beam_search(self):

tokenizer = GPT2Tokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
text = """Hello, my dog is cute and"""
tokens = tokenizer(text, return_tensors="pt")
tokens = tokenizer(text, return_tensors="pt").to(torch_device)

model = GPT2LMHeadModel.from_pretrained("hf-internal-testing/tiny-random-gpt2").to(torch_device)

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