use hard=true gbsm

ml-agents/mlagents/trainers/torch/distributions.py

             logits = branch(inputs)
             norm_logits = self._mask_branch(logits, masks[idx])
             distribution = torch.nn.functional.gumbel_softmax(
-                norm_logits, hard=False, dim=1
+                norm_logits, hard=True, dim=1
             )
             branch_distributions.append(distribution)
         return branch_distributions