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Aug 10, 2025
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Streamlines benchmark suite structure and test scope #99

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b28acd1
Streamlines benchmark suite structure and test scope
LoserCheems Aug 10, 2025
7099f37
Merge branch 'Support-backward' of https://github.com/SmallDoges/flas…
LoserCheems Aug 10, 2025
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62 changes: 0 additions & 62 deletions benchmarks/benchmark_mqar.py
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52 changes: 26 additions & 26 deletions benchmarks/benchmark_forward_equivalence.py → benchmarks/forward_equivalence.py
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Original file line number Diff line number Diff line change
Expand Up @@ -518,27 +518,27 @@ def test_cuda_forward_equivalence(accuracy_threshold=0.95):
# If you encounter NAN issues when running multiple configurations, try running a single configuration
test_configs = [
# (batch_size, num_heads, num_kv_heads, query_len, key_len, head_dim, is_causal)
(1, 1, 1, 64, 64, 32, True),
(1, 1, 1, 64, 64, 32, False),
(1, 1, 1, 128, 128, 32, True),
(1, 1, 1, 128, 128, 32, False),
(1, 1, 1, 256, 256, 32, True),
(1, 1, 1, 256, 256, 32, False),
(1, 1, 1, 512, 512, 32, True),
(1, 1, 1, 512, 512, 32, False),
(1, 1, 1, 1024, 1024, 32, True),
(1, 1, 1, 1024, 1024, 32, False),
(1, 1, 1, 2048, 2048, 32, True),
(1, 1, 1, 2048, 2048, 32, False),
# (1, 1, 1, 64, 64, 32, True),
# (1, 1, 1, 64, 64, 32, False),
# (1, 1, 1, 128, 128, 32, True),
# (1, 1, 1, 128, 128, 32, False),
# (1, 1, 1, 256, 256, 32, True),
# (1, 1, 1, 256, 256, 32, False),
# (1, 1, 1, 512, 512, 32, True),
# (1, 1, 1, 512, 512, 32, False),
# (1, 1, 1, 1024, 1024, 32, True),
# (1, 1, 1, 1024, 1024, 32, False),
# (1, 1, 1, 2048, 2048, 32, True),
# (1, 1, 1, 2048, 2048, 32, False),
(1, 1, 1, 4096, 4096, 32, True),
(1, 1, 1, 4096, 4096, 32, False),
(1, 2, 1, 64, 64, 32, True),
(2, 1, 1, 128, 128, 32, True),
(2, 2, 1, 128, 128, 32, True),
(1, 2, 1, 64, 64, 128, True),
(1, 2, 1, 128, 128, 128, True),
(1, 2, 1, 256, 256, 128, True),
(1, 2, 1, 512, 512, 128, True),
# (1, 1, 1, 4096, 4096, 32, False),
# (1, 2, 1, 64, 64, 32, True),
# (2, 1, 1, 128, 128, 32, True),
# (2, 2, 1, 128, 128, 32, True),
# (1, 2, 1, 64, 64, 128, True),
# (1, 2, 1, 128, 128, 128, True),
# (1, 2, 1, 256, 256, 128, True),
# (1, 2, 1, 512, 512, 128, True),
]

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
Expand Down Expand Up @@ -1050,13 +1050,13 @@ def main():
print("\n" + "📍" + " Starting Standard Forward Pass Tests " + "📍")
test_results['cuda'] = test_cuda_forward_equivalence(args.accuracy_threshold)

if args.test_type in ['all', 'triton']:
print("\n" + "🔥" + " Starting Python vs Triton Tests " + "🔥")
test_results['triton'] = test_triton_forward_equivalence(args.accuracy_threshold)
# if args.test_type in ['all', 'triton']:
# print("\n" + "🔥" + " Starting Python vs Triton Tests " + "🔥")
# test_results['triton'] = test_triton_forward_equivalence(args.accuracy_threshold)

if args.test_type in ['all', 'flex']:
print("\n" + "🌟" + " Starting Python vs Flex Attention Tests " + "🌟")
test_results['flex'] = test_flex_forward_equivalence(args.accuracy_threshold)
# if args.test_type in ['all', 'flex']:
# print("\n" + "🌟" + " Starting Python vs Flex Attention Tests " + "🌟")
# test_results['flex'] = test_flex_forward_equivalence(args.accuracy_threshold)


# Print overall summary
Expand Down
100 changes: 50 additions & 50 deletions benchmarks/benchmark_forward_performance.py → benchmarks/forward_performance.py
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Expand Up @@ -732,57 +732,57 @@ def run_performance_benchmark(test_type='all', num_runs=3, warmup_runs=2):
(1, 2, 1, 4096, 4096, 128, 2048, True),
(1, 2, 1, 8192, 8192, 128, 2048, True),
(1, 2, 1, 16384, 16384, 128, 2048, True),
(1, 2, 1, 32768, 32768, 128, 2048, True),

# Inference
(1, 2, 1, 2, 256, 128, 2048, True),
(1, 2, 1, 2, 512, 128, 2048, True),
(1, 2, 1, 2, 1024, 128, 2048, True),
(1, 2, 1, 2, 2048, 128, 2048, True),
(1, 2, 1, 2, 4096, 128, 2048, True),
(1, 2, 1, 2, 8192, 128, 2048, True),
(1, 2, 1, 2, 16384, 128, 2048, True),
(1, 2, 1, 2, 32768, 128, 2048, True),
# (1, 2, 1, 32768, 32768, 128, 2048, True),

# # Inference
# (1, 2, 1, 2, 256, 128, 2048, True),
# (1, 2, 1, 2, 512, 128, 2048, True),
# (1, 2, 1, 2, 1024, 128, 2048, True),
# (1, 2, 1, 2, 2048, 128, 2048, True),
# (1, 2, 1, 2, 4096, 128, 2048, True),
# (1, 2, 1, 2, 8192, 128, 2048, True),
# (1, 2, 1, 2, 16384, 128, 2048, True),
# (1, 2, 1, 2, 32768, 128, 2048, True),
(1, 2, 1, 2, 65536, 128, 2048, True),
(1, 2, 1, 2, 131072, 128, 2048, True),
(1, 2, 1, 2, 262144, 128, 2048, True),
(1, 2, 1, 2, 524288, 128, 2048, True),

# Vary batch size
(1, 2, 1, 4096, 4096, 32, 2048, True),
(2, 2, 1, 4096, 4096, 32, 2048, True),
(4, 2, 1, 4096, 4096, 32, 2048, True),
(8, 2, 1, 4096, 4096, 32, 2048, True),

# Vary head count
(1, 1, 1, 4096, 4096, 32, 2048, True),
(1, 2, 1, 4096, 4096, 32, 2048, True),
(1, 4, 1, 4096, 4096, 32, 2048, True),
(1, 8, 2, 4096, 4096, 32, 2048, True),

# Vary head dimension
(1, 2, 1, 4096, 4096, 32, 2048, True),
(1, 2, 1, 4096, 4096, 64, 2048, True),
(1, 2, 1, 4096, 4096, 96, 2048, True),
(1, 2, 1, 4096, 4096, 128, 2048, True),
(1, 2, 1, 4096, 4096, 192, 2048, True),
(1, 2, 1, 4096, 4096, 256, 2048, True),

# Vary keep_window_size
(1, 2, 1, 32768, 32768, 128, 32, True),
(1, 2, 1, 32768, 32768, 128, 64, True),
(1, 2, 1, 32768, 32768, 128, 128, True),
(1, 2, 1, 32768, 32768, 128, 256, True),
(1, 2, 1, 32768, 32768, 128, 512, True),
(1, 2, 1, 32768, 32768, 128, 1024, True),
(1, 2, 1, 32768, 32768, 128, 2048, True),
(1, 2, 1, 32768, 32768, 128, 4096, True),
(1, 2, 1, 32768, 32768, 128, 8192, True),
(1, 2, 1, 32768, 32768, 128, 16384, True),
(1, 2, 1, 32768, 32768, 128, 32768, True),

# Test non-causal
(1, 2, 1, 4096, 4096, 128, 2048, False),
# (1, 2, 1, 2, 131072, 128, 2048, True),
# (1, 2, 1, 2, 262144, 128, 2048, True),
# (1, 2, 1, 2, 524288, 128, 2048, True),

# # Vary batch size
# (1, 2, 1, 4096, 4096, 32, 2048, True),
# (2, 2, 1, 4096, 4096, 32, 2048, True),
# (4, 2, 1, 4096, 4096, 32, 2048, True),
# (8, 2, 1, 4096, 4096, 32, 2048, True),

# # Vary head count
# (1, 1, 1, 4096, 4096, 32, 2048, True),
# (1, 2, 1, 4096, 4096, 32, 2048, True),
# (1, 4, 1, 4096, 4096, 32, 2048, True),
# (1, 8, 2, 4096, 4096, 32, 2048, True),

# # Vary head dimension
# (1, 2, 1, 4096, 4096, 32, 2048, True),
# (1, 2, 1, 4096, 4096, 64, 2048, True),
# (1, 2, 1, 4096, 4096, 96, 2048, True),
# (1, 2, 1, 4096, 4096, 128, 2048, True),
# (1, 2, 1, 4096, 4096, 192, 2048, True),
# (1, 2, 1, 4096, 4096, 256, 2048, True),

# # Vary keep_window_size
# (1, 2, 1, 32768, 32768, 128, 32, True),
# (1, 2, 1, 32768, 32768, 128, 64, True),
# (1, 2, 1, 32768, 32768, 128, 128, True),
# (1, 2, 1, 32768, 32768, 128, 256, True),
# (1, 2, 1, 32768, 32768, 128, 512, True),
# (1, 2, 1, 32768, 32768, 128, 1024, True),
# (1, 2, 1, 32768, 32768, 128, 2048, True),
# (1, 2, 1, 32768, 32768, 128, 4096, True),
# (1, 2, 1, 32768, 32768, 128, 8192, True),
# (1, 2, 1, 32768, 32768, 128, 16384, True),
# (1, 2, 1, 32768, 32768, 128, 32768, True),

# # Test non-causal
# (1, 2, 1, 4096, 4096, 128, 2048, False),
]

print(f"\n📊 Benchmark Results (averaged over {num_runs} runs):")
Expand Down
0 benchmarks/benchmark_grad.py → benchmarks/grad_equivalence.py
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