[PyTorch] Use dummy wgrad in GroupedLinear (#2305)

dummy wgrad
Signed-off-by: tongliu <tongliu@nvidia.com>
Signed-off-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>

transformer_engine/pytorch/module/grouped_linear.py

@@ -13,6 +13,7 @@ import transformer_engine_torch as tex
 
 from transformer_engine.common.recipe import Recipe
 from .base import (
+    get_dummy_wgrad,
     get_multi_stream_cublas_workspace,
     TransformerEngineBaseModule,
     _2X_ACC_FPROP,
@@ -447,18 +448,15 @@ class _GroupedLinear(torch.autograd.Function):
                         ):
                             weight.grad_added_to_main_grad = True
                             if getattr(weight, "zero_out_wgrad", False):
-                                wgrad = torch.zeros(
-                                    weight.main_grad.shape,
-                                    dtype=weight.dtype,
-                                    device=torch.cuda.current_device(),
-                                    requires_grad=False,
+                                wgrad = get_dummy_wgrad(
+                                    list(weight.main_grad.shape),
+                                    weight.dtype,
+                                    zero=True,
                                 )
                             else:
-                                wgrad = torch.empty(
-                                    weight.main_grad.shape,
-                                    dtype=weight.dtype,
-                                    device=torch.cuda.current_device(),
-                                    requires_grad=False,
+                                wgrad = get_dummy_wgrad(
+                                    list(weight.main_grad.shape),
+                                    weight.dtype,
                                 )
                         elif ctx.fuse_wgrad_accumulation:
                             wgrad = None