!11462 add pipe for cache embedding

From: @fangzehua
Reviewed-by: 
Signed-off-by:

mindspore/ccsrc/frontend/parallel/cache_embedding/cache_embedding.h

@@ -22,7 +22,7 @@
 namespace mindspore {
 namespace parallel {
 // Automatically adding control depend based on effect order and side effect analysis.
-void AddCacheEmbedding(const FuncGraphPtr &graph);
+void AddCacheEmbedding(const FuncGraphPtr &graph, bool is_pipe = false);
 }  // namespace parallel
 }  // namespace mindspore
 #endif  // MINDSPORE_CCSRC_FRONTEND_PARALLEL_CACHE_EMBEDDING_CACHE_EMBEDDING_H_

mindspore/nn/layer/embedding.py

@@ -21,7 +21,7 @@ from mindspore.ops import functional as F
 from mindspore.common.parameter import Parameter
 from mindspore.common.initializer import initializer
 from mindspore.communication.management import get_group_size
-from mindspore.context import ParallelMode
+from mindspore.context import ParallelMode, get_context
 from mindspore.parallel._utils import _get_parallel_mode, _get_full_batch
 from mindspore.parallel._ps_context import _insert_hash_table_size, _set_cache_enable, _is_role_worker, _get_ps_context
 from mindspore._checkparam import Rel
@@ -278,7 +278,7 @@ class EmbeddingLookup(Cell):
                 raise ValueError("slice_mode should support mode in nn.EmbeddingLookup, but get "
                                  + str(slice_mode))
         if self.cache_enable and not enable_ps:
-            if is_auto_parallel:
+            if parallel_mode != ParallelMode.STAND_ALONE:
                 raise ValueError("parallel mode haven't supported cache enable yet.")
             self._set_cache_enable()
         self.embedding_table.unique = self.forward_unique
@@ -288,15 +288,14 @@ class EmbeddingLookup(Cell):
             self.max_norm = Tensor(self.max_norm, dtype=mstype.float32)
 
     def _set_cache_enable(self):
-        """EmbeddingLookup cache check for not ps env."""
+        """EmbeddingLookup cache check for not ps env, which is only support 'ascend'."""
         if self.target != 'DEVICE':
-            logger.warning("The configuration of 'vocab_cache_size' is valid only in 'DEVICE' target, "
-                           "so it will be ignored.")
-            return
+            raise ValueError("The configuration of 'vocab_cache_size' is valid only in 'DEVICE' target.")
         if not self.sparse:
-            logger.warning("The configuration of 'vocab_cache_size' is valid only 'sparse' is true, "
-                           "so it will be ignored.")
-            return
+            raise ValueError("The configuration of 'vocab_cache_size' is valid only 'sparse' is true.")
+        if get_context("device_target") != 'Ascend':
+            raise ValueError("The configuration of 'vocab_cache_size' is valid only in 'ascend'.")
+
         logger.info("EmbeddingLookup cache enable takes effect.")
         self.forward_unique = True
         self.unique = P.Unique().add_prim_attr('primitive_target', 'CPU')