fix param order

add param keys check
add check_param num and support_param check

mindinsight/debugger/conditionmgr/condition.py

@@ -219,6 +219,7 @@ class Condition:
         self._parameters = {
             parameter.name: parameter for parameter in parameters
         }
+        self.ordered_parameter_names = [parameter.name for parameter in parameters]
         self._supported_target_type = supported_target_type
         self.supported_platforms = supported_platforms
         self.minimum_debugger_capability = minimum_debugger_capability

mindinsight/debugger/conditionmgr/condition_list.py

@@ -528,7 +528,7 @@ CONDITION_LIST = [
         optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
         parameters=[
             ConditionParameter(
-                name="abs_update_ratio_mean_gt",
+                name="abs_mean_update_ratio_gt",
                 value_type=ValueTypeEnum.FLOAT64,
                 valid_test_func=check_abs_param_range,
                 default_value=1e-1
@@ -552,7 +552,7 @@ CONDITION_LIST = [
         optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
         parameters=[
             ConditionParameter(
-                name="abs_update_ratio_mean_lt",
+                name="abs_mean_update_ratio_lt",
                 value_type=ValueTypeEnum.FLOAT64,
                 valid_test_func=check_abs_param_range,
                 default_value=1e-4

mindinsight/debugger/conditionmgr/recommender.py

@@ -219,7 +219,7 @@ def _recommend_weight_change_too_small(condition_mgr, trainable_weight_nodes, wa
             "condition": condition.id,
             "params": [
                 _ConditionParameterValue(
-                    parameter=condition.get_parameter_definition("abs_update_ratio_mean_lt"),
+                    parameter=condition.get_parameter_definition("abs_mean_update_ratio_lt"),
                     value=1.0e-4  # set default value to 1.0e-4
                 ),
             ]
@@ -270,8 +270,8 @@ def _recommend_weight_change_too_large(basic_info_nodes, condition_mgr, watch_po
         watch_condition={
             "condition": condition.id,
             "params": [_ConditionParameterValue(
-                parameter=condition.get_parameter_definition("abs_update_ratio_mean_gt"),
-                value=0.1  # set default value to 0.1
+                parameter=condition.get_parameter_definition("abs_mean_update_ratio_gt"),
+                value=1  # set default value to 1
             )]
         },
         watch_nodes=basic_info_nodes.copy(),
@@ -309,54 +309,7 @@ def _recommend_activation_range(basic_info_nodes, condition_mgr, watch_points, c
     if not condition_mgr.has_condition(ConditionIdEnum.ACTIVATION_RANGE.value, condition_context):
         return
     condition = condition_mgr.get_condition(condition_id=ConditionIdEnum.ACTIVATION_RANGE.value)
-    params = []
-    if activation_func == ActivationFuncEnum.TANH.value:
-        # The recommend params for Tanh: The percentage of value in range (tanh(-8.8), tanh(8.8)) is lower than 50.0%
-        params = [
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_percentage_lt"),
-                value=50.0
-            ),
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_start_inclusive"),
-                value=math.tanh(-8.8)
-            ),
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_end_inclusive"),
-                value=math.tanh(8.8)
-            )]
-    if activation_func == ActivationFuncEnum.SIGMOID.value:
-        # The recommend params for Sigmoid:
-        # The percentage of value in range (sigmoid(-16.2)), sigmoid(16.2)) is lower than 50.0%
-        params = [
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_percentage_lt"),
-                value=50.0
-            ),
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_start_inclusive"),
-                value=_sigmoid(-16.2)
-            ),
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_end_inclusive"),
-                value=_sigmoid(16.2)
-            )]
-    if activation_func == ActivationFuncEnum.RELU.value:
-        # The recommend params for ReLU:
-        # The percentage of value in range (float('-inf'), 0) is greater than 50.0%
-        params = [
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_percentage_gt"),
-                value=50.0
-            ),
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_start_inclusive"),
-                value=float('-inf')
-            ),
-            _ConditionParameterValue(
-                parameter=condition.get_parameter_definition("range_end_inclusive"),
-                value=0
-            )]
+    params = _get_recommend_activation_params(condition, activation_func)
     activation_range_watchpoint = _WatchPointData(
         watch_condition={
             "condition": condition.id,
@@ -465,5 +418,58 @@ def _add_graph_name(nodes, graph_stream):
 
 
 def _sigmoid(value):
-    """return sigmoid value"""
+    """calculate the sigmoid of value"""
     return 1.0 / (1.0 + math.exp(value))
+
+
+def _get_recommend_activation_params(condition, activation_func):
+    """Get recommend params for tanh, sigmoid and relu activation function."""
+    params = []
+    if activation_func == ActivationFuncEnum.TANH.value:
+        # The recommend params for Tanh: The percentage of value in range (tanh(-8.8), tanh(8.8)) is lower than 0.1%
+        params = [
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_percentage_lt"),
+                value=0.1
+            ),
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_start_inclusive"),
+                value=math.tanh(-8.8)
+            ),
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_end_inclusive"),
+                value=math.tanh(8.8)
+            )]
+    if activation_func == ActivationFuncEnum.SIGMOID.value:
+        # The recommend params for Sigmoid:
+        # The percentage of value in range (sigmoid(-16.2)), sigmoid(16.2)) is lower than 0.1%
+        params = [
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_percentage_lt"),
+                value=0.1
+            ),
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_start_inclusive"),
+                value=_sigmoid(-16.2)
+            ),
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_end_inclusive"),
+                value=_sigmoid(16.2)
+            )]
+    if activation_func == ActivationFuncEnum.RELU.value:
+        # The recommend params for ReLU:
+        # The percentage of value in range (-1, 0) is greater than 99.9%
+        params = [
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_percentage_gt"),
+                value=99.9
+            ),
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_start_inclusive"),
+                value=-1
+            ),
+            _ConditionParameterValue(
+                parameter=condition.get_parameter_definition("range_end_inclusive"),
+                value=0
+            )]
+    return params

mindinsight/debugger/stream_cache/watchpoint.py

@@ -19,6 +19,7 @@ import copy
 from mindinsight.debugger.common.exceptions.exceptions import DebuggerParamValueError
 from mindinsight.debugger.common.log import LOGGER as log
 from mindinsight.debugger.common.utils import is_scope_type, is_cst_type
+from mindinsight.debugger.conditionmgr.conditionmgr import ConditionMgr
 from mindinsight.debugger.conditionmgr.common.utils import NodeBasicInfo
 from mindinsight.debugger.conditionmgr.condition import ConditionIdEnum
 from mindinsight.debugger.proto.debug_grpc_pb2 import SetCMD, WatchCondition
@@ -287,20 +288,29 @@ class Watchpoint:
     def get_pending_cmd(self, watch_nodes):
         """Return the watchpoint in proto format."""
         # construct SetCMD
+        condition_id = self._condition.get('id')
         set_cmd = SetCMD()
         set_cmd.id = self._id
         set_cmd.delete = False
-        set_cmd.watch_condition.condition = WATCHPOINT_CONDITION_MAPPING.get(
-            self._condition.get('id'))
-        for param in self._condition.get('params'):
-            # at most one param is provided
-            param_proto = set_cmd.watch_condition.params.add()
-            param_proto.name = param.get('name')
-            param_proto.value = param.get('value')
-            param_proto.disabled = False
-
-            # Only one parameter of condition in current version.
-            set_cmd.watch_condition.value = param.get('value')
+        set_cmd.watch_condition.condition = WATCHPOINT_CONDITION_MAPPING.get(condition_id)
+        condition_mgr = ConditionMgr()
+        condition = condition_mgr.get_condition(condition_id)
+        param_dict = {
+            param.get('name'): param for param in self._condition.get('params')
+        }
+        for param_name in condition.ordered_parameter_names:
+            param = param_dict.get(param_name)
+            if param:
+                param_proto = set_cmd.watch_condition.params.add()
+                param_proto.name = param.get('name')
+                param_proto.value = param.get('value')
+                param_proto.disabled = False
+                # Only one parameter of condition in old mindspore version.
+                set_cmd.watch_condition.value = param.get('value')
+            else:
+                param_proto = set_cmd.watch_condition.params.add()
+                param_proto.name = param_name
+                param_proto.disabled = True
 
         for watch_node in watch_nodes:
             event_node = set_cmd.watch_nodes.add()

mindinsight/debugger/stream_handler/watchpoint_handler.py

@@ -14,6 +14,7 @@
 # ============================================================================
 """Define the watchpoint stream handler."""
 from mindinsight.debugger.conditionmgr.condition import ValueTypeEnum
+from mindinsight.debugger.conditionmgr.condition import ParamTypeEnum
 from mindinsight.debugger.common.exceptions.exceptions import DebuggerParamValueError, \
     DebuggerParamTypeError
 from mindinsight.debugger.common.log import LOGGER as log
@@ -540,7 +541,14 @@ def validate_watch_condition_params(condition_mgr, watch_condition):
             raise DebuggerParamValueError("No param is expected.")
         return
 
+    check_param_num = 0
+    support_params = set()
+    defined_support_params = set()
     for param in params:
+        if len(param) > 2:
+            log.error("Invalid param keys for condition: %s", condition_id)
+            raise DebuggerParamValueError("Invalid param keys.")
+
         condition_param_name = param.get("name")
         if condition_param_name not in condition.names:
             log.error("Invalid name of parameter for condition: %s, available values: %s",
@@ -562,6 +570,21 @@ def validate_watch_condition_params(condition_mgr, watch_condition):
             log.error("Param %s out of range for condition: %s", condition_param_name, condition_id)
             raise DebuggerParamValueError("Parameter out of range.")
 
+        if condition_param.param_type == ParamTypeEnum.CHECK_PARAM.value:
+            if condition_param.required_params:
+                defined_support_params = set(condition_param.required_params)
+            check_param_num += 1
+        else:
+            support_params.add(condition_param.name)
+
+        if check_param_num > 1:
+            log.error("Multiple check params for condition: %s", condition_id)
+            raise DebuggerParamValueError("Multiple check params.")
+
+    if support_params != defined_support_params:
+        log.error("Invalid support params for condition: %s", condition_id)
+        raise DebuggerParamValueError("Invalid support params.")
+
 
 def set_default_param(condition_mgr, watch_condition):
     """

tests/st/func/debugger/expect_results/restful_results/create_and_delete_watchpoint.json

@@ -1 +1 @@
-{"watch_points": [{"id": 1, "watch_condition": {"id": "max_gt", "params": [{"name": "param", "value": 1.0, "disable": false}], "abbr": "MAX>"}}, {"id": 2, "watch_condition": {"id": "max_lt", "params": [{"name": "param", "value": -1.0, "disable": false}], "abbr": "MAX<"}}, {"id": 3, "watch_condition": {"id": "min_gt", "params": [{"name": "param", "value": 1e+32, "disable": false}], "abbr": "MIN>"}}, {"id": 5, "watch_condition": {"id": "max_min_gt", "params": [{"name": "param", "value": 0, "disable": false}], "abbr": "MAX-MIN>"}}, {"id": 6, "watch_condition": {"id": "max_min_lt", "params": [{"name": "param", "value": 0, "disable": false}], "abbr": "MAX-Min<"}}, {"id": 7, "watch_condition": {"id": "mean_gt", "params": [{"name": "param", "value": 0, "disable": false}], "abbr": "MEAN>"}}, {"id": 8, "watch_condition": {"id": "mean_lt", "params": [{"name": "param", "value": 0, "disable": false}], "abbr": "MEAN<"}}, {"id": 9, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}, {"id": 10, "watch_condition": {"id": "overflow", "params": [], "abbr": "OVERFLOW"}}]}
+{"watch_points": [{"id": 1, "watch_condition": {"id": "max_gt", "params": [{"name": "param", "value": 1.0}], "abbr": "MAX>"}}, {"id": 2, "watch_condition": {"id": "max_lt", "params": [{"name": "param", "value": -1.0}], "abbr": "MAX<"}}, {"id": 3, "watch_condition": {"id": "min_gt", "params": [{"name": "param", "value": 1e+32}], "abbr": "MIN>"}}, {"id": 5, "watch_condition": {"id": "max_min_gt", "params": [{"name": "param", "value": 0}], "abbr": "MAX-MIN>"}}, {"id": 6, "watch_condition": {"id": "max_min_lt", "params": [{"name": "param", "value": 0}], "abbr": "MAX-Min<"}}, {"id": 7, "watch_condition": {"id": "mean_gt", "params": [{"name": "param", "value": 0}], "abbr": "MEAN>"}}, {"id": 8, "watch_condition": {"id": "mean_lt", "params": [{"name": "param", "value": 0}], "abbr": "MEAN<"}}, {"id": 9, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}, {"id": 10, "watch_condition": {"id": "overflow", "params": [], "abbr": "OVERFLOW"}}]}

tests/st/func/debugger/expect_results/restful_results/multi_run_steps.json

@@ -1 +1 @@
-{"metadata": {"state": "waiting", "step": 2, "device_name": "0", "node_name": "", "backend": "GPU", "enable_recheck": false, "graph_name": ""}, "graph": {"graph_names": ["graph_0", "graph_1"], "nodes": [{"name": "graph_0", "type": "name_scope", "attr": {}, "input": {}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 2, "independent_layout": false}, {"name": "graph_1", "type": "name_scope", "attr": {}, "input": {}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 2, "independent_layout": false}]}, "watch_points": [{"id": 1, "watch_condition": {"id": "weight_initialization", "params": [{"name": "zero_percentage_ge", "disable": false, "value": 100}], "abbr": "WI"}}, {"id": 2, "watch_condition": {"id": "weight_change_too_large", "params": [{"name": "abs_update_ratio_mean_gt", "disable": false, "value": 0.1}], "abbr": "WCL"}}, {"id": 3, "watch_condition": {"id": "gradient_vanishing", "params": [{"name": "abs_mean_lt", "disable": false, "value": 1e-09}], "abbr": "GV"}}, {"id": 4, "watch_condition": {"id": "tensor_overflow", "params": [], "abbr": "TO"}}, {"id": 5, "watch_condition": {"id": "tensor_all_zero", "params": [{"name": "zero_percentage_ge", "disable": false, "value": 100}], "abbr": "TZ"}}]}
+{"metadata": {"state": "waiting", "step": 2, "device_name": "0", "node_name": "", "backend": "GPU", "enable_recheck": false, "graph_name": ""}, "graph": {"graph_names": ["graph_0", "graph_1"], "nodes": [{"name": "graph_0", "type": "name_scope", "attr": {}, "input": {}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 2, "independent_layout": false}, {"name": "graph_1", "type": "name_scope", "attr": {}, "input": {}, "output": {}, "output_i": 0, "proxy_input": {}, "proxy_output": {}, "subnode_count": 2, "independent_layout": false}]}, "watch_points": [{"id": 1, "watch_condition": {"id": "weight_initialization", "params": [{"name": "zero_percentage_ge", "disable": false, "value": 100}], "abbr": "WI"}}, {"id": 2, "watch_condition": {"id": "weight_change_too_large", "params": [{"name": "abs_mean_update_ratio_gt", "disable": false, "value": 0.1}], "abbr": "WCL"}}, {"id": 3, "watch_condition": {"id": "gradient_vanishing", "params": [{"name": "abs_mean_lt", "disable": false, "value": 1e-09}], "abbr": "GV"}}, {"id": 4, "watch_condition": {"id": "tensor_overflow", "params": [], "abbr": "TO"}}, {"id": 5, "watch_condition": {"id": "tensor_all_zero", "params": [{"name": "zero_percentage_ge", "disable": false, "value": 100}], "abbr": "TZ"}}]}

tests/st/func/debugger/test_restful_api.py

@@ -130,14 +130,14 @@ class TestAscendDebugger:
         with self._debugger_client.get_thread_instance():
             check_waiting_state(app_client)
             conditions = [
-                {'id': 'max_gt', 'params': [{'name': 'param', 'value': 1.0, 'disable': False}]},
-                {'id': 'max_lt', 'params': [{'name': 'param', 'value': -1.0, 'disable': False}]},
-                {'id': 'min_gt', 'params': [{'name': 'param', 'value': 1e+32, 'disable': False}]},
-                {'id': 'min_lt', 'params': [{'name': 'param', 'value': -1e+32, 'disable': False}]},
-                {'id': 'max_min_gt', 'params': [{'name': 'param', 'value': 0, 'disable': False}]},
-                {'id': 'max_min_lt', 'params': [{'name': 'param', 'value': 0, 'disable': False}]},
-                {'id': 'mean_gt', 'params': [{'name': 'param', 'value': 0, 'disable': False}]},
-                {'id': 'mean_lt', 'params': [{'name': 'param', 'value': 0, 'disable': False}]},
+                {'id': 'max_gt', 'params': [{'name': 'param', 'value': 1.0}]},
+                {'id': 'max_lt', 'params': [{'name': 'param', 'value': -1.0}]},
+                {'id': 'min_gt', 'params': [{'name': 'param', 'value': 1e+32}]},
+                {'id': 'min_lt', 'params': [{'name': 'param', 'value': -1e+32}]},
+                {'id': 'max_min_gt', 'params': [{'name': 'param', 'value': 0}]},
+                {'id': 'max_min_lt', 'params': [{'name': 'param', 'value': 0}]},
+                {'id': 'mean_gt', 'params': [{'name': 'param', 'value': 0}]},
+                {'id': 'mean_lt', 'params': [{'name': 'param', 'value': 0}]},
                 {'id': 'inf', 'params': []},
                 {'id': 'overflow', 'params': []},
             ]

tests/ut/debugger/expected_results/watchpoint/watchpoint_handler_get_1.json

@@ -1 +1 @@
-[{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}, {"id": 2, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}, {"id": 3, "watch_condition": {"id": "max_gt", "params": [{"name": "param", "value": 1, "disable": false}], "abbr": "MAX>"}}]
+[{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}, {"id": 2, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}, {"id": 3, "watch_condition": {"id": "max_gt", "params": [{"name": "param", "value": 1}], "abbr": "MAX>"}}]

tests/ut/debugger/stream_handler/test_watchpoint_handler.py

@@ -63,7 +63,7 @@ class TestWatchpointHandler:
         watchpoints = [
             ({'id': 'inf', 'params': []}, None, None, 1),
             ({'id': 'inf', 'params': []}, ["Default"], None, 2),
-            ({'id': 'max_gt', 'params': [{'name': 'param', 'value': 1, 'disable': False}]},
+            ({'id': 'max_gt', 'params': [{'name': 'param', 'value': 1}]},
              ["Gradients/Default/network-WithLossCell/_backbone-LeNet5/relu-ReLU/gradReLU/ReluGradV2-op92"],
              None, 3)
         ]
@@ -233,13 +233,13 @@ def test_validate_watch_condition_type_error():
 
 def test_validate_watch_condition_params_except():
     """Test validate_watch_condition_params."""
-    watch_condition = {'id': 'inf', 'params': [{'name': 'param', 'value': 0, 'disable': False}]}
+    watch_condition = {'id': 'inf', 'params': [{'name': 'param', 'value': 0}]}
     conditionmgr = ConditionMgr()
     with pytest.raises(DebuggerParamValueError) as err:
         validate_watch_condition_params(conditionmgr, watch_condition)
     assert err.value.error_code == '5054B081'
 
-    watch_condition = {'id': 'max_gt', 'params': [{'name': 'param', 'value': '0', 'disable': False}]}
+    watch_condition = {'id': 'max_gt', 'params': [{'name': 'param', 'value': '0'}]}
     with pytest.raises(DebuggerParamValueError) as err:
         validate_watch_condition_params(conditionmgr, watch_condition)
     assert err.value.error_code == '5054B081'