002f9879b2
Replaces cherry-picked upstream_ref with complete source trees. xllm/ — Iluvatar official C++ inference engine (15MB, 1470 files) Complete: kernels → layers → models → runtime → scheduler → api Excluded: .git, binary images, third_party submodule checkouts ds_vllm/ — Iluvatar official vllm fork (8MB, 703 files) Included: csrc/ (ALL CUDA kernels), fused_moe/, qwen3_5 model, _custom_ops Excluded: tests, benchmarks, docs, examples (not needed for reference) Critical call chains now fully traceable: MoE: moe_topk_softmax_kernels.cuh → ixformer.h → fused_moe.cpp → layer GDN: qwen3_gated_delta_net_base.cpp → qwen3_5_gated_delta_net.cpp Attention: ixformer.h → xllm_paged_attention → attention.cpp
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
import torch
|
|
import numpy as np
|
|
|
|
|
|
def compare_tensors(
|
|
a: torch.Tensor,
|
|
b: torch.Tensor,
|
|
tol: float = 1e-6,
|
|
verbose: bool = False
|
|
) -> int:
|
|
"""
|
|
Compare two PyTorch tensors and count the number of elements whose absolute difference
|
|
exceeds the given tolerance.
|
|
|
|
Args:
|
|
a (torch.Tensor): The first tensor to compare.
|
|
b (torch.Tensor): The second tensor to compare.
|
|
tol (float, optional): The absolute tolerance threshold. Defaults to 1e-6.
|
|
verbose (bool, optional): If True, print the indices and values of differing elements. Defaults to False.
|
|
|
|
Returns:
|
|
int: The number of elements where abs(a - b) > tol.
|
|
|
|
Raises:
|
|
ValueError: If the shapes of the input tensors do not match.
|
|
"""
|
|
# Check if tensor shapes are the same
|
|
if a.shape != b.shape:
|
|
raise ValueError(f"Shape mismatch: {a.shape} vs {b.shape}")
|
|
|
|
# Create a boolean mask where differences exceed the tolerance
|
|
diff_mask = (a - b).abs() > tol
|
|
|
|
# Count the number of differing elements
|
|
diff_count = int(diff_mask.sum().item())
|
|
|
|
# If verbose, print details of differing elements
|
|
if verbose and diff_count > 0:
|
|
indices = torch.nonzero(diff_mask, as_tuple=False)
|
|
for idx in indices:
|
|
i, j = idx[0].item(), idx[1].item()
|
|
print(
|
|
f"diff at {i},{j}: "
|
|
f"{a[i, j].item():.6f} - {b[i, j].item():.6f} = "
|
|
f"{(a[i, j] - b[i, j]).item():.6f}"
|
|
)
|
|
|
|
return diff_count
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# example:
|
|
# a = torch.load("/path/to/a.pt")
|
|
# b = torch.load("/path/to/b.pt")
|
|
# diff_count = compare_tensors(a, b)
|
|
# print(f"diff count: {diff_count}")
|
|
pass
|