Create info.sh

info.sh

@@ -0,0 +1,111 @@
+#!/usr/bin/env bash
+echo "================= RUNTIME CAPABILITIES ================="
+
+echo "[GPU / Driver / CUDA]"
+nvidia-smi || true
+echo "CUDA_HOME: ${CUDA_HOME:-/usr/local/cuda}"
+echo "NVCC: $(nvcc --version 2>/dev/null | tail -n1 || echo 'N/A')"
+echo
+
+echo "[PyTorch / CUDA backend]"
+python3 - <<'PY'
+import json, sys
+try:
+    import torch
+    info = {
+        "torch": torch.__version__,
+        "cuda_available": torch.cuda.is_available(),
+        "cuda_device_count": torch.cuda.device_count(),
+        "cuda_runtime_version": torch.version.cuda if hasattr(torch.version, "cuda") else None,
+        "cudnn_version": (torch.backends.cudnn.version() if torch.cuda.is_available() else None),
+        "tf32": (torch.backends.cuda.matmul.allow_tf32 if torch.cuda.is_available() else None),
+        "flash_sdp": (torch.backends.cuda.flash_sdp_enabled() if hasattr(torch.backends.cuda, "flash_sdp_enabled") else None),
+        "mem_efficient_sdp": (torch.backends.cuda.mem_efficient_sdp_enabled() if hasattr(torch.backends.cuda, "mem_efficient_sdp_enabled") else None),
+        "math_sdp": (torch.backends.cuda.math_sdp_enabled() if hasattr(torch.backends.cuda, "math_sdp_enabled") else None),
+    }
+    print(json.dumps(info, indent=2))
+    if torch.cuda.is_available():
+        for i in range(torch.cuda.device_count()):
+            print(f"GPU {i}: {torch.cuda.get_device_name(i)}")
+except Exception as e:
+    print(f"[ERR torch] {type(e).__name__}: {e}")
+PY
+echo
+
+echo "[Apex]"
+python3 - <<'PY'
+try:
+    import importlib
+    importlib.import_module("apex.normalization")
+    print("apex.normalization: OK")
+except Exception as e:
+    print(f"Apex: ERR {type(e).__name__}: {e}")
+PY
+echo
+
+echo "[FlashAttention]"
+python3 - <<'PY'
+try:
+    import flash_attn
+    print(f"flash_attn: OK (version={getattr(flash_attn,'__version__', 'unknown')})")
+    try:
+        import flash_attn_2_cuda
+        print("flash_attn_2_cuda: OK")
+    except Exception as e:
+        print(f"flash_attn_2_cuda: ERR {type(e).__name__}: {e}")
+except Exception as e:
+    print(f"flash_attn: ERR {type(e).__name__}: {e}")
+PY
+echo
+
+echo "[Triton]"
+python3 - <<'PY'
+try:
+    import triton
+    print(f"triton: OK (version={getattr(triton,'__version__','unknown')})")
+    try:
+        import triton.ops
+        print("triton.ops: OK")
+    except Exception as e:
+        print(f"triton.ops: ERR {type(e).__name__}: {e}")
+except Exception as e:
+    print(f"triton: ERR {type(e).__name__}: {e}")
+PY
+echo
+
+echo "[BitsAndBytes (Q8/Q4)]"
+python3 - <<'PY'
+try:
+    import bitsandbytes as bnb
+    import importlib
+    v = getattr(bnb, "__version__", "unknown")
+    print(f"bitsandbytes: OK (version={v})")
+    # Teste de presença de kernels Triton/Q8
+    try:
+        import bitsandbytes.triton.int8_matmul_mixed_dequantize as q8
+        print("bnb.triton.int8_matmul_mixed_dequantize: OK")
+    except Exception as e:
+        print(f"bnb.triton.int8_matmul_mixed_dequantize: ERR {type(e).__name__}: {e}")
+except Exception as e:
+    print(f"bitsandbytes: ERR {type(e).__name__}: {e}")
+PY
+echo
+
+echo "[Transformers / Diffusers / XFormers]"
+python3 - <<'PY'
+import importlib
+def ver(name):
+    try:
+        m = importlib.import_module(name)
+        return getattr(m, "__version__", "unknown")
+    except Exception as e:
+        return f"ERR:{type(e).__name__}"
+print("transformers:", ver("transformers"))
+print("diffusers:", ver("diffusers"))
+print("xformers:", ver("xformers"))
+PY
+echo
+
+echo "[Distribuído / NCCL Env]"
+env | egrep 'MASTER_|NCCL|CUDA_VISIBLE_DEVICES|TORCH_|ENABLE_' | sort
+echo "================= END CAPABILITIES ================="