[shardformer] support tp+zero for shardformer (#4472)

* support tp+zero/input type cast for hybridplugin

* add tp+zero tests

* fix bucket arguments

tests/test_shardformer/test_model/test_shard_t5.py

@@ -55,12 +55,12 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,
 
     row_layer_for_check = ['shared', 'encoder.block[0].layer[0].SelfAttention.q']
 
-    # check weights and gradients
+    # check grad
     if test_config['precision'] == 'fp32':
         atol, rtol = 1e-5, 1e-3
     else:
         atol, rtol = 5e-3, 5e-3
-    if stage_manager is None or stage_manager.is_first_stage():
+    if (stage_manager is None or stage_manager.is_first_stage()) and booster.plugin.zero_stage == 0:
         check_grad(t5, sharded_t5, row_layer_for_check, tp_group, atol=atol, rtol=rtol, dim=0)
 
     # check weights after optimizer.step()
@@ -110,6 +110,14 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,
     'enable_all_optimization': True,
     'use_lazy_init': False,
     'precision': 'fp32'
+}, {
+    'tp_size': 2,
+    'pp_size': 1,
+    'enable_all_optimization': True,
+    'use_lazy_init': True,
+    'zero_stage': 2,
+    'precision': 'fp16',
+    'initial_scale': 1
 }])
 @clear_cache_before_run()
 def run_t5_test(test_config):