optimizes the documentation of chinese API of LSTM,EmbeddingLookup,etc.

docs/api/api_python/nn/mindspore.nn.LSTM.rst

@@ -51,7 +51,7 @@ mindspore.nn.LSTM
 
     **异常：**
 
-    - **TypeError** - `input_size`， `hidden_size` 或  `num_layers` 不是整数。
+    - **TypeError** - `input_size`， `hidden_size` 或  `num_layers` 不是int。
     - **TypeError** - `has_bias` ， `batch_first` 或 `bidirectional` 不是bool。
-    - **TypeError** - `dropout` 既不是浮点数也不是整数。
+    - **TypeError** - `dropout` 既不是float也不是int。
     - **ValueError** - `dropout` 不在[0.0, 1.0]范围内。

mindspore/python/mindspore/nn/layer/embedding.py

@@ -176,7 +176,7 @@ class EmbeddingLookup(Cell):
             ['DEVICE', 'CPU']. Default: 'CPU'.
         slice_mode (str): The slicing way in semi_auto_parallel/auto_parallel. The value must get through
             :class:`mindspore.nn.EmbeddingLookup`. Default: :class:`mindspore.nn.EmbeddingLookup.BATCH_SLICE`.
-        manual_shapes (tuple): The accompaniment array in field slice mode, Default: None.
+        manual_shapes (tuple): The accompaniment array in field slice mode. Default: None.
         max_norm (Union[float, None]): A maximum clipping value. The data type must be float16, float32
                                        or None. Default: None
         sparse (bool): Using sparse mode. When 'target' is set to 'CPU', 'sparse' has to be true. Default: True.