Added pre/post calls do quantize_blockwise.

bitsandbytes/functional.py

@@ -458,6 +458,7 @@ def quantize_blockwise(A: Tensor, code: Tensor = None, absmax: Tensor = None, ra
     """
 
 
+    prev_device = pre_call(A.device)
     if code is None:
         if "dynamic" not in name2qmap:
             name2qmap["dynamic"] = create_dynamic_map().to(A.device)
@@ -479,6 +480,7 @@ def quantize_blockwise(A: Tensor, code: Tensor = None, absmax: Tensor = None, ra
         is_on_gpu([code, A, absmax, out, rand])
         cblocksize = ct.c_int32(blocksize)
         if rand is not None:
+            is_on_gpu([code, A, out, absmax, rand])
             assert blocksize==4096
             assert rand.numel() >= 1024
             rand_offset = random.randint(0, 1023)
@@ -489,6 +491,7 @@ def quantize_blockwise(A: Tensor, code: Tensor = None, absmax: Tensor = None, ra
             else:
                 raise ValueError(f"Blockwise quantization only supports 16/32-bit floats, but got {A.dtype}")
         else:
+            is_on_gpu([code, A, out, absmax])
             if A.dtype == torch.float32:
                 lib.cquantize_blockwise_fp32(get_ptr(code), get_ptr(A), get_ptr(absmax), get_ptr(out), cblocksize, ct.c_int(A.numel()))
             elif A.dtype == torch.float16:
@@ -499,6 +502,7 @@ def quantize_blockwise(A: Tensor, code: Tensor = None, absmax: Tensor = None, ra
         # cpu
         assert rand is None
         lib.cquantize_blockwise_cpu_fp32(get_ptr(code), get_ptr(A), get_ptr(absmax), get_ptr(out), ct.c_longlong(blocksize), ct.c_longlong(A.numel()))
+    post_call(A.device)
 
     return out, (absmax, code)
 
@@ -537,6 +541,7 @@ def dequantize_blockwise(
         Dequantized tensor (default: float32)
     """
     assert quant_state is not None or absmax is not None
+    device = pre_call(A.device)
     if code is None and quant_state is None:
         if "dynamic" not in name2qmap:
             name2qmap["dynamic"] = create_dynamic_map().to(A.device)
@@ -561,6 +566,7 @@ def dequantize_blockwise(
             raise ValueError(f"Blockwise quantization only supports 16/32-bit floats, but got {A.dtype}")
     else:
         lib.cdequantize_blockwise_cpu_fp32(get_ptr(quant_state[1]), get_ptr(A), get_ptr(quant_state[0]), get_ptr(out), ct.c_longlong(blocksize), ct.c_longlong(A.numel()))
+    post_call(A.device)
 
     return out