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Tests: remove cuda versions when the result is the same 🧹🧹 (#31955)

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remove cuda versions when the result is the same
This commit is contained in:
Joao Gante
2024-07-16 16:49:54 +01:00
committed by GitHub
parent 693cb828ff
commit 999981daf4
3 changed files with 52 additions and 155 deletions
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43
tests/models/mistral/test_modeling_mistral.py
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@@ -538,10 +538,7 @@ class MistralIntegrationTest(unittest.TestCase):
@slow
@require_bitsandbytes
def test_model_7b_generation(self):
EXPECTED_TEXT_COMPLETION = {
7: "My favourite condiment is 100% ketchup. I’m not a fan of mustard, mayo,",
8: "My favourite condiment is 100% ketchup. I’m not a fan of mustard, mayo,",
}
EXPECTED_TEXT_COMPLETION = "My favourite condiment is 100% ketchup. I’m not a fan of mustard, mayo,"
prompt = "My favourite condiment is "
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", use_fast=False)
@@ -553,7 +550,7 @@ class MistralIntegrationTest(unittest.TestCase):
# greedy generation outputs
generated_ids = model.generate(input_ids, max_new_tokens=20, temperature=0)
text = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, text)
@slow
def test_model_7b_dola_generation(self):
@@ -641,15 +638,7 @@ class MistralIntegrationTest(unittest.TestCase):
@slow
def test_speculative_generation(self):
# Key 9 for MI300, Key 8 for A100/A10, and Key 7 for T4.
#
# Note: Key 9 is currently set for MI300, but may need potential future adjustments for H100s,
# considering differences in hardware processing and potential deviations in generated text.
EXPECTED_TEXT_COMPLETION = {
7: "My favourite condiment is 100% ketchup. I love it on everything. I’m not a big",
8: "My favourite condiment is 100% ketchup. I love it on everything. I’m not a big",
9: "My favourite condiment is 100% ketchup. I love it on everything. I’m not a big",
}
EXPECTED_TEXT_COMPLETION = "My favourite condiment is 100% ketchup. I love it on everything. I’m not a big"
prompt = "My favourite condiment is "
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", use_fast=False)
model = MistralForCausalLM.from_pretrained(
@@ -663,7 +652,7 @@ class MistralIntegrationTest(unittest.TestCase):
input_ids, max_new_tokens=20, do_sample=True, temperature=0.3, assistant_model=model
)
text = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, text)
@slow
@require_read_token
@@ -677,16 +666,10 @@ class MistralIntegrationTest(unittest.TestCase):
self.skipTest(reason="This test is failing (`torch.compile` fails) on Nvidia T4 GPU.")
NUM_TOKENS_TO_GENERATE = 40
EXPECTED_TEXT_COMPLETION = {
8: [
"My favourite condiment is 100% ketchup. I love it on everything. "
"I’m not a big fan of mustard, mayo, or relish. I’m not a fan of pickles"
],
7: [
"My favourite condiment is 100% ketchup. I love it on everything. "
"I’m not a big fan of mustard, mayo, or relish. I’m not a fan of pickles"
],
}
EXPECTED_TEXT_COMPLETION = [
"My favourite condiment is 100% ketchup. I love it on everything. "
"I’m not a big fan of mustard, mayo, or relish. I’m not a fan of pickles"
]
prompts = ["My favourite condiment is "]
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", use_fast=False)
@@ -699,21 +682,21 @@ class MistralIntegrationTest(unittest.TestCase):
# Dynamic Cache
generated_ids = model.generate(**inputs, max_new_tokens=NUM_TOKENS_TO_GENERATE, do_sample=False)
dynamic_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], dynamic_text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, dynamic_text)
# Static Cache
generated_ids = model.generate(
**inputs, max_new_tokens=NUM_TOKENS_TO_GENERATE, do_sample=False, cache_implementation="static"
)
static_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], static_text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, static_text)
# Sliding Window Cache
generated_ids = model.generate(
**inputs, max_new_tokens=NUM_TOKENS_TO_GENERATE, do_sample=False, cache_implementation="sliding_window"
)
static_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], static_text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, static_text)
# Static Cache + compile
forward_function = model.forward
@@ -722,7 +705,7 @@ class MistralIntegrationTest(unittest.TestCase):
**inputs, max_new_tokens=NUM_TOKENS_TO_GENERATE, do_sample=False, cache_implementation="static"
)
static_compiled_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], static_compiled_text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, static_compiled_text)
# Sliding Window Cache + compile
torch._dynamo.reset()
@@ -731,7 +714,7 @@ class MistralIntegrationTest(unittest.TestCase):
**inputs, max_new_tokens=NUM_TOKENS_TO_GENERATE, do_sample=False, cache_implementation="sliding_window"
)
static_compiled_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION[self.cuda_compute_capability_major_version], static_compiled_text)
self.assertEqual(EXPECTED_TEXT_COMPLETION, static_compiled_text)
@slow