add annotation and validation for device_num

mindinsight/lineagemgr/api/model.py

@@ -142,6 +142,8 @@ def filter_summary_lineage(summary_base_dir, search_condition=None):
 
             - batch_size (dict): The filter condition of batch size.
 
+            - device_num (dict): The filter condition of device num.
+
             - loss (dict): The filter condition of loss.
 
             - model_size (dict): The filter condition of model size.

mindinsight/lineagemgr/common/exceptions/error_code.py

@@ -81,7 +81,9 @@ class LineageErrors(LineageErrorCodes):
     LINEAGE_FILE_NOT_FOUND_ERROR = 22 | _MODEL_LINEAGE_API_ERROR_MASK
     LINEAGE_PARAM_SUMMARY_PATH_ERROR = 23 | _MODEL_LINEAGE_API_ERROR_MASK
     LINEAGE_SEARCH_CONDITION_PARAM_ERROR = 24 | _MODEL_LINEAGE_API_ERROR_MASK
+
     LINEAGE_PARAM_LINEAGE_TYPE_ERROR = 25 | _MODEL_LINEAGE_API_ERROR_MASK
+    LINEAGE_PARAM_DEVICE_NUM_ERROR = 26 | _MODEL_LINEAGE_API_ERROR_MASK
 
     # Dataset lineage error codes.
     LINEAGE_PARAM_DATASET_MARK_ERROR = 0 | _DATASET_LINEAGE_ERROR_MASK
@@ -146,6 +148,8 @@ class LineageErrorMsg(Enum):
 
     PARAM_BATCH_SIZE_ERROR = "The parameter batch_size is invalid. It should be a non-negative integer."
 
+    PARAM_DEVICE_NUM_ERROR = "The parameter device_num is invalid. It should be a non-negative integer."
+
     PARAM_CALLBACK_LIST_ERROR = "The parameter list_callback is invalid. It should be an instance of " \
                                 "mindspore.train.callback._ListCallback."
 

mindinsight/lineagemgr/common/validator/model_parameter.py

@@ -123,6 +123,7 @@ class SearchModelConditionParameter(Schema):
     learning_rate = fields.Dict()
     epoch = fields.Dict()
     batch_size = fields.Dict()
+    device_num = fields.Dict()
     loss = fields.Dict()
     model_size = fields.Dict()
     limit = fields.Int(validate=lambda n: 0 < n <= 100)
@@ -228,6 +229,11 @@ class SearchModelConditionParameter(Schema):
         """Check batch size."""
         SearchModelConditionParameter.check_dict_value_type(data, int)
 
+    @validates("device_num")
+    def check_device_num(self, data):
+        """Check device num."""
+        SearchModelConditionParameter.check_dict_value_type(data, int)
+
     @validates("model_size")
     def check_model_size(self, data):
         """Check model size."""

mindinsight/lineagemgr/common/validator/validate.py

@@ -57,6 +57,7 @@ SEARCH_MODEL_ERROR_MAPPING = {
     'learning_rate': LineageErrors.LINEAGE_PARAM_LEARNING_RATE_ERROR,
     'epoch': LineageErrors.LINEAGE_PARAM_EPOCH_ERROR,
     'batch_size': LineageErrors.LINEAGE_PARAM_BATCH_SIZE_ERROR,
+    'device_num': LineageErrors.LINEAGE_PARAM_DEVICE_NUM_ERROR,
     'limit': LineageErrors.PARAM_VALUE_ERROR,
     'offset': LineageErrors.PARAM_VALUE_ERROR,
     'loss': LineageErrors.LINEAGE_PARAM_LOSS_ERROR,
@@ -92,6 +93,7 @@ SEARCH_MODEL_ERROR_MSG_MAPPING = {
     'learning_rate': LineageErrorMsg.LINEAGE_LEARNING_RATE_ERROR.value,
     'epoch': LineageErrorMsg.PARAM_EPOCH_NUM_ERROR.value,
     'batch_size': LineageErrorMsg.PARAM_BATCH_SIZE_ERROR.value,
+    'device_num': LineageErrorMsg.PARAM_DEVICE_NUM_ERROR.value,
     'limit': LineageErrorMsg.PARAM_LIMIT_ERROR.value,
     'offset': LineageErrorMsg.PARAM_OFFSET_ERROR.value,
     'loss': LineageErrorMsg.LINEAGE_LOSS_ERROR.value,