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#!/usr/bin/env bash
set -euo pipefail
echo "================= RUNTIME CAPABILITIES ================="
date
echo
if command -v nvidia-smi >/dev/null 2>&1; then
nvidia-smi
else
echo "nvidia-smi: not available"
fi
echo
echo "CUDA_HOME: ${CUDA_HOME:-/usr/local/cuda}"
if command -v nvcc >/dev/null 2>&1; then
nvcc --version || true
else
echo "nvcc: not available"
fi
echo
echo "[PyTorch / CUDA backend]"
python3 - <<'PY'
import json, os, torch, inspect
def to_bool(x):
try:
if callable(x):
try:
sig = inspect.signature(x)
if len(sig.parameters)==0:
return bool(x())
except Exception:
pass
return True
return bool(x)
except Exception:
return None
info = {
"torch": getattr(torch, "__version__", None),
"cuda_available": torch.cuda.is_available(),
"cuda_device_count": torch.cuda.device_count(),
"cuda_runtime_version": getattr(torch.version, "cuda", None),
"cudnn_version": torch.backends.cudnn.version() if torch.backends.cudnn.is_available() else None,
"tf32": (torch.backends.cuda.matmul.allow_tf32 if torch.cuda.is_available() else None),
"flash_sdp": (to_bool(getattr(torch.backends.cuda, "enable_flash_sdp", None)) if torch.cuda.is_available() else None),
"mem_efficient_sdp": (to_bool(getattr(torch.backends.cuda, "enable_mem_efficient_sdp", None)) if torch.cuda.is_available() else None),
"math_sdp": (to_bool(getattr(torch.backends.cuda, "enable_math_sdp", None)) if torch.cuda.is_available() else None),
}
print(json.dumps(info, indent=2))
for i in range(min(torch.cuda.device_count(), 16)):
print(f"GPU {i}: {torch.cuda.get_device_name(i)}")
PY
echo
echo "[Apex (FusedLayerNorm/RMSNorm)]"
python3 - <<'PY'
try:
from apex.normalization import FusedLayerNorm, FusedRMSNorm
import importlib; importlib.import_module("fused_layer_norm_cuda")
print("apex.normalization: OK")
except Exception as e:
print("apex.normalization: FAIL ->", e)
PY
echo
echo "[FlashAttention (CUDA/Triton/RMSNorm)]"
python3 - <<'PY'
import importlib
mods = [
'flash_attn', 'flash_attn_2_cuda',
'flash_attn.ops.rms_norm', 'flash_attn.ops.layer_norm',
'flash_attn.layers.layer_norm'
]
for m in mods:
try:
importlib.import_module(m)
print(f"{m}: OK")
except Exception as e:
print(f"{m}: FAIL -> {e}")
PY
echo
echo "[FlashAttention versão/details]"
python3 - <<'PY'
try:
import flash_attn
fa_ver = getattr(flash_attn, "__version__", None)
print(f"flash_attn: {fa_ver}")
except Exception:
print("flash_attn: not importable.")
try:
import torch
print(f"torch: {torch.__version__} | cuda: {getattr(torch.version, 'cuda', None)}")
except Exception:
pass
PY
echo
echo "[Triton]"
python3 - <<'PY'
try:
import triton
print("triton:", triton.__version__)
try:
import triton.ops as _; print("triton.ops: OK")
except Exception:
print("triton.ops: not present (ok on Triton>=3.x)")
except Exception as e:
print("triton: FAIL ->", e)
PY
echo
echo "[BitsAndBytes (Q8/Q4)]"
python3 - <<'PY'
try:
import bitsandbytes as bnb
print("bitsandbytes:", bnb.__version__)
try:
from bitsandbytes.triton import _custom_ops as _; print("bnb.triton._custom_ops: OK")
except Exception as e:
print("bnb.triton: partial ->", e)
except Exception as e:
print("bitsandbytes: FAIL ->", e)
PY
echo
echo "[Transformers / Diffusers / XFormers / EcoML]"
python3 - <<'PY'
def _v(m):
try:
mod = __import__(m)
print(f"{m}: {getattr(mod, '__version__', 'unknown')}")
except Exception as e:
print(f"{m}: FAIL -> {e}")
for m in ("transformers", "diffusers", "xformers", "ecuml", "mlx", "ecobase"):
_v(m)
PY
echo
echo "[Distribuído / NCCL Env]"
env | grep -E '^(CUDA_VISIBLE_DEVICES|NCCL_|TORCH_|ENABLE_.*SDP|HF_HUB_.*|CUDA_|NV_.*NCCL.*|PYTORCH_CUDA_ALLOC_CONF)=' | sort
echo
echo "[Output dir/perms]"
OUT="/app/outputs"
echo "OUT dir: $OUT"
mkdir -p "$OUT"
ls -la "$OUT" || true
echo "================= END CAPABILITIES ================="
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