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Fix: init range #88

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Fix: init range #88

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8 changes: 4 additions & 4 deletions problems/nvidia/nvfp4_dual_gemm/reference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -112,13 +112,13 @@ def generate_input(

# Generate uint8 tensor, then convert to float4e2m1fn_x2 data type
a_ref = torch.randint(
0, 2, (l, m, k // 2), dtype=torch.int8, device="cuda"
0, 4, (l, m, k // 2), dtype=torch.int8, device="cuda"
).permute(1, 2, 0)
b1_ref = torch.randint(
0, 2, (l, n, k // 2), dtype=torch.int8, device="cuda"
0, 4, (l, n, k // 2), dtype=torch.int8, device="cuda"
).permute(1, 2, 0)
b2_ref = torch.randint(
0, 2, (l, n, k // 2), dtype=torch.int8, device="cuda"
0, 4, (l, n, k // 2), dtype=torch.int8, device="cuda"
).permute(1, 2, 0)
a_ref = a_ref.view(torch.float4_e2m1fn_x2)
b1_ref = b1_ref.view(torch.float4_e2m1fn_x2)
Expand All @@ -137,7 +137,7 @@ def create_scale_factor_tensors(l, mn, sf_k):
ref_shape = (l, mn, sf_k)
ref_permute_order = (1, 2, 0)
# Init with uint8 tensor, then convert to float8_e4m3fn
ref_f8_random_int = torch.randint(-1, 2, ref_shape, dtype=torch.int8, device='cuda')
ref_f8_random_int = torch.randint(0, 3, ref_shape, dtype=torch.int8, device='cuda')
ref_f8_torch_tensor = ref_f8_random_int.to(dtype=torch.float8_e4m3fn)
# permute to match ref_permute_order
ref_f8_torch_tensor_permuted = ref_f8_torch_tensor.permute(*ref_permute_order)
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