biondizzle
8de47e26ce
- Move test_*.py → tests/integration/ - Move probe_*.py, dump_*.py → helpers/ - Move PERFORMANCE_AUDIT.md → docs/ - Move single_shot_PYTORCH_REFERENCE.py → dsv4/reference/ - Fix 3 import references in test_layer_comparison, test_mhc_comparison, test_compressor_position_bias - Add helpers/import_closure.py (dead-code detection tool)
17 lines
839 B
Python
17 lines
839 B
Python
#!/usr/bin/env python3
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"""Test: quantize_activation_nvfp4 on different GPUs."""
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import torch
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from dsv4.ops.quantize import quantize_activation_nvfp4
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torch.manual_seed(42)
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for gpu in [0, 1]:
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dev = f"cuda:{gpu}"
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x = torch.randn(1, 7168, dtype=torch.bfloat16, device=dev) * 0.5
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gsa = 0.000375
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x_fp4, x_sf = quantize_activation_nvfp4(x, gsa)
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has_nan = torch.isnan(x_fp4.view(torch.float16)).any().item() if x_fp4.dtype == torch.float4_e2m1fn_x2 else torch.isnan(x_fp4).any().item()
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print(f"GPU {gpu} quantize: x_fp4 shape={x_fp4.shape} dtype={x_fp4.dtype} x_sf shape={x_sf.shape} has_nan={has_nan}")
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print(f" x_fp4 uint8 range: [{x_fp4.view(torch.uint8).min().item()}, {x_fp4.view(torch.uint8).max().item()}]")
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print(f" x_sf float range: [{x_sf.float().min().item():.6f}, {x_sf.float().max().item():.6f}]")
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