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Fix bad test about slower init (#32002)

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Zach Mueller 2024-07-16 10:33:05 -04:00 committed by GitHub
parent 25e5e3fa56
commit 693cb828ff
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1 changed files with 3 additions and 17 deletions
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20
tests/utils/test_modeling_utils.py
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@ -20,7 +20,6 @@ import os.path
import sys
import tempfile
import threading
import time
import unittest
import unittest.mock as mock
import uuid
@ -895,28 +894,22 @@ class ModelUtilsTest(TestCasePlus):
@require_usr_bin_time
@require_accelerate
@mark.accelerate_tests
def test_from_pretrained_low_cpu_mem_usage_slower(self):
def test_from_pretrained_low_cpu_mem_usage_equal(self):
# Before this would test that `from_pretrained(..., low_cpu_mem_usage=True)` uses less cpu memory than default
# Now though the memory is the same, we simply test that loading with `low_cpu_mem_usage` winds up being *slower*
# (mostly from extra logic needed)
# Now though these should be around the same.
# TODO: Look for good bounds to check that their timings are near the same
mname = "hf-internal-testing/tiny-random-bert"
preamble = "from transformers import AutoModel"
one_liner_str = f'{preamble}; AutoModel.from_pretrained("{mname}", low_cpu_mem_usage=False)'
start_time = time.time()
# Save this output as `max_rss_normal` if testing memory results
max_rss_normal = self.python_one_liner_max_rss(one_liner_str)
end_time = time.time()
elapsed_time_normal = end_time - start_time
# print(f"{max_rss_normal=}")
one_liner_str = f'{preamble}; AutoModel.from_pretrained("{mname}", low_cpu_mem_usage=True)'
start_time = time.time()
# Save this output as `max_rss_low_mem` if testing memory results
max_rss_low_mem = self.python_one_liner_max_rss(one_liner_str)
end_time = time.time()
elapsed_time_low_mem = end_time - start_time
# Should be within 2MBs of each other (overhead)
self.assertAlmostEqual(
@ -926,13 +919,6 @@ class ModelUtilsTest(TestCasePlus):
msg="using `low_cpu_mem_usage` should incur the same memory usage in both cases.",
)
self.assertGreater(
elapsed_time_low_mem,
elapsed_time_normal,
"using `low_cpu_mem_usage` should be slower due to extra logic, "
f"but got elapsed_time_normal={elapsed_time_normal} and elapsed_time_low_mem={elapsed_time_low_mem}",
)
# if you want to compare things manually, let's first look at the size of the model in bytes
# model = BertModel.from_pretrained(mname, low_cpu_mem_usage=False)
# total_numel = sum(dict((p.data_ptr(), p.numel()) for p in model.parameters()).values())