delete 'disable' on ui as it useless for ui

auto choose nodes when create watchpoints
add actual_value when hit watchpoints
add error_code when to show the Nan and Inf error

mindinsight/conditionmgr/condition.py → mindinsight/debugger/conditionmgr/condition.py

@@ -21,7 +21,7 @@ This module also provide the available conditions to condition_collections api.
 import math
 
 from enum import Enum
-from mindinsight.conditionmgr.log import logger
+from mindinsight.debugger.conditionmgr.log import logger
 
 
 class ConditionIdEnum(Enum):
@@ -53,9 +53,6 @@ class ConditionIdEnum(Enum):
     WEIGHT_NOT_CHANGED = "weight_not_changed"
     WEIGHT_CHANGE_TOO_LARGE = "weight_change_too_large"
     WEIGHT_CHANGE_TOO_SMALL = "weight_change_too_small"
-    TENSOR_CHANGE_TOO_LARGE = "tensor_change_too_large"
-    TENSOR_CHANGE_TOO_SMALL = "tensor_change_too_small"
-    TENSOR_NOT_CHANGED = "tensor_not_changed"
     ACTIVATION_RANGE = "activation_range"
     TENSOR_RANGE = "tensor_range"
 

mindinsight/conditionmgr/condition_list.py → mindinsight/debugger/conditionmgr/condition_list.py

@@ -17,19 +17,19 @@ Condition list.
 
 This module provide the detail conditions list.
 """
-from mindinsight.conditionmgr.condition import Condition
-from mindinsight.conditionmgr.condition import OptimizePhaseEnum
-from mindinsight.conditionmgr.condition import ConditionParameter
-from mindinsight.conditionmgr.condition import ValueTypeEnum
-from mindinsight.conditionmgr.condition import TargetTypeEnum
-from mindinsight.conditionmgr.condition import PlatformEnum
-from mindinsight.conditionmgr.condition import ParamTypeEnum
-from mindinsight.conditionmgr.condition import ConditionIdEnum
-from mindinsight.conditionmgr.condition import check_initialization_available
-from mindinsight.conditionmgr.condition import check_normal_param_range
-from mindinsight.conditionmgr.condition import check_percentage_param_range
-from mindinsight.conditionmgr.condition import check_abs_param_range
-from mindinsight.conditionmgr.condition import check_not_nan
+from mindinsight.debugger.conditionmgr.condition import Condition
+from mindinsight.debugger.conditionmgr.condition import OptimizePhaseEnum
+from mindinsight.debugger.conditionmgr.condition import ConditionParameter
+from mindinsight.debugger.conditionmgr.condition import ValueTypeEnum
+from mindinsight.debugger.conditionmgr.condition import TargetTypeEnum
+from mindinsight.debugger.conditionmgr.condition import PlatformEnum
+from mindinsight.debugger.conditionmgr.condition import ParamTypeEnum
+from mindinsight.debugger.conditionmgr.condition import ConditionIdEnum
+from mindinsight.debugger.conditionmgr.condition import check_initialization_available
+from mindinsight.debugger.conditionmgr.condition import check_normal_param_range
+from mindinsight.debugger.conditionmgr.condition import check_percentage_param_range
+from mindinsight.debugger.conditionmgr.condition import check_abs_param_range
+from mindinsight.debugger.conditionmgr.condition import check_not_nan
 
 
 CONDITION_LIST = [
@@ -569,89 +569,10 @@ CONDITION_LIST = [
         supported_platforms=(PlatformEnum.ASCEND, PlatformEnum.GPU),
         minimum_debugger_capability=(1, 1)
     ),
-    Condition(
-        condition_id=ConditionIdEnum.TENSOR_CHANGE_TOO_LARGE,
-        abbr="TCL",
-        # Send this condition to MindSpore will use WatchCondition.Condition.tensor_change_too_large
-        optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
-        parameters=[
-            ConditionParameter(
-                name="abs_update_ratio_mean_gt",
-                value_type=ValueTypeEnum.FLOAT64,
-                valid_test_func=check_abs_param_range,
-                default_value=1e-1
-            ),
-            ConditionParameter(
-                name="epsilon",
-                value_type=ValueTypeEnum.FLOAT64,
-                support_disable=False,
-                default_value=1e-9,
-                visible_on_ui=False
-            )
-        ],
-        supported_target_type=TargetTypeEnum.TENSOR,
-        supported_platforms=(PlatformEnum.ASCEND, PlatformEnum.GPU),
-        minimum_debugger_capability=(1, 1)
-    ),
-    Condition(
-        condition_id=ConditionIdEnum.TENSOR_CHANGE_TOO_SMALL,
-        abbr="TCS",
-        # Send this condition to MindSpore will use WatchCondition.Condition.tensor_change_too_small
-        optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
-        parameters=[
-            ConditionParameter(
-                name="abs_update_ratio_mean_lt",
-                value_type=ValueTypeEnum.FLOAT64,
-                valid_test_func=check_abs_param_range,
-                default_value=1e-4
-            ),
-            ConditionParameter(
-                name="epsilon",
-                value_type=ValueTypeEnum.FLOAT64,
-                support_disable=False,
-                default_value=1e-9,
-                visible_on_ui=False
-            )
-        ],
-        supported_target_type=TargetTypeEnum.TENSOR,
-        supported_platforms=(PlatformEnum.ASCEND, PlatformEnum.GPU),
-        minimum_debugger_capability=(1, 1)
-    ),
-    Condition(
-        condition_id=ConditionIdEnum.TENSOR_NOT_CHANGED,
-        abbr="TNC",
-        # Send this condition to MindSpore will use WatchCondition.Condition.tensor_not_changed
-        optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
-        parameters=[
-            ConditionParameter(
-                name="rtol",
-                value_type=ValueTypeEnum.FLOAT64,
-                valid_test_func=check_abs_param_range,
-                default_value=1e-5
-            ),
-            ConditionParameter(
-                name="atol",
-                value_type=ValueTypeEnum.FLOAT64,
-                support_disable=False,
-                default_value=1e-8,
-                visible_on_ui=False
-            ),
-            ConditionParameter(
-                name="equal_nan",
-                value_type=ValueTypeEnum.BOOL,
-                support_disable=False,
-                default_value=False,
-                visible_on_ui=False
-            )
-        ],
-        supported_target_type=TargetTypeEnum.TENSOR,
-        supported_platforms=(PlatformEnum.ASCEND, PlatformEnum.GPU),
-        minimum_debugger_capability=(1, 1)
-    ),
     Condition(
         condition_id=ConditionIdEnum.ACTIVATION_RANGE,
         abbr="AR",
-        # Send this condition to MindSpore will use WatchCondition.Condition.tensor_not_changed
+        # Send this condition to MindSpore will use WatchCondition.Condition.activation_range
         optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
         parameters=[
             ConditionParameter(
@@ -696,7 +617,7 @@ CONDITION_LIST = [
     Condition(
         condition_id=ConditionIdEnum.TENSOR_RANGE,
         abbr="TR",
-        # Send this condition to MindSpore will use WatchCondition.Condition.tensor_not_changed
+        # Send this condition to MindSpore will use WatchCondition.Condition.tensor_range
         optimize_phase=OptimizePhaseEnum.TENSOR_CHECK,
         parameters=[
             ConditionParameter(

mindinsight/conditionmgr/conditionmgr.py → mindinsight/debugger/conditionmgr/conditionmgr.py

@@ -17,10 +17,10 @@ Condition manager..
 
 This module provide condition manager function.
 """
-from mindinsight.conditionmgr.condition import Condition
-from mindinsight.conditionmgr.condition import TargetTypeEnum
-from mindinsight.conditionmgr.condition_list import CONDITION_LIST
-from mindinsight.conditionmgr.log import logger
+from mindinsight.debugger.conditionmgr.condition import Condition
+from mindinsight.debugger.conditionmgr.condition import TargetTypeEnum
+from mindinsight.debugger.conditionmgr.condition_list import CONDITION_LIST
+from mindinsight.debugger.conditionmgr.log import logger
 
 
 class ConditionMgr:

mindinsight/conditionmgr/recommender.py → mindinsight/debugger/conditionmgr/recommender.py

@@ -19,11 +19,11 @@ This module predefine recommend watchpoints.
 """
 import queue as Queue
 
-from mindinsight.conditionmgr.conditionmgr import ConditionMgr
-from mindinsight.conditionmgr.condition import TargetTypeEnum
-from mindinsight.conditionmgr.condition import ConditionIdEnum
-from mindinsight.conditionmgr.common.utils import NodeBasicInfo
-from mindinsight.conditionmgr.log import logger
+from mindinsight.debugger.conditionmgr.conditionmgr import ConditionMgr
+from mindinsight.debugger.conditionmgr.condition import TargetTypeEnum
+from mindinsight.debugger.conditionmgr.condition import ConditionIdEnum
+from mindinsight.debugger.conditionmgr.common.utils import NodeBasicInfo
+from mindinsight.debugger.conditionmgr.log import logger
 from mindinsight.conf import settings
 
 
@@ -43,7 +43,6 @@ class _WatchPointData:
             "id": self.watch_condition.get("condition"),
             "params": [{
                 "name": param.get_parameter_name(),
-                "disable": False,
                 "value": param.value
             } for param in self.watch_condition.get("params")]
         }
@@ -81,7 +80,7 @@ def recommend_watchpoints(condition_mgr: ConditionMgr, graph_stream, condition_c
         return watch_points
 
     # add weight watch points
-    merged_info = _get_basic_node_info(TargetTypeEnum.WEIGHT.value, graph_stream)
+    merged_info = get_basic_node_info(TargetTypeEnum.WEIGHT.value, graph_stream)
     _recommend_weight_initialization(merged_info, condition_mgr, watch_points, condition_context)
     _recommend_weight_change_too_large(merged_info, condition_mgr, watch_points, condition_context)
 
@@ -92,11 +91,11 @@ def recommend_watchpoints(condition_mgr: ConditionMgr, graph_stream, condition_c
     _recommend_weight_change_too_small(condition_mgr, trainable_weight_nodes, watch_points, condition_context)
 
     # add gradient watch points
-    merged_info = _get_basic_node_info(TargetTypeEnum.GRADIENT.value, graph_stream)
+    merged_info = get_basic_node_info(TargetTypeEnum.GRADIENT.value, graph_stream)
     _recommend_gradient_vanishing(merged_info, condition_mgr, watch_points, condition_context)
 
     # add tensor watch points
-    merged_info = _get_basic_node_info(TargetTypeEnum.TENSOR.value, graph_stream)
+    merged_info = get_basic_node_info(TargetTypeEnum.TENSOR.value, graph_stream)
     _recommend_overflow_ascend_chip(merged_info, condition_mgr, watch_points, condition_context)
     _recommend_tensor_overflow(merged_info, condition_mgr, watch_points, condition_context)
     _recommend_tensor_all_zero(merged_info, condition_mgr, watch_points, condition_context)
@@ -272,7 +271,7 @@ def _recommend_weight_initialization(basic_info_nodes, condition_mgr, watch_poin
     watch_points.append(weight_initialization_watchpoint)
 
 
-def _get_basic_node_info(node_category, graph_stream):
+def get_basic_node_info(node_category, graph_stream):
     """Get node merged info."""
     basic_info_nodes = _get_basic_node_info_by_node_category(node_category, graph_stream)
     merged_info = _merge_nodes(basic_info_nodes, graph_stream.whole_graph)

mindinsight/debugger/debugger_grpc_server.py

@@ -13,6 +13,8 @@
 # limitations under the License.
 # ============================================================================
 """Implement the debugger grpc server."""
+import copy
+
 from functools import wraps
 
 from mindinsight.debugger.common.log import LOGGER as log
@@ -443,10 +445,22 @@ class DebuggerGrpcServer(grpc_server_base.EventListenerServicer):
                 continue
             watchpoint_hit = {
                 'tensor_proto': watchpoint_hit_proto.tensor,
-                'watchpoint': watchpoint_stream.get_watchpoint_by_id(watchpoint_hit_proto.id),
+                'watchpoint': copy.deepcopy(watchpoint_stream.get_watchpoint_by_id(watchpoint_hit_proto.id)),
                 'node_name': ui_node_name,
                 'graph_name': graph_name
             }
+            hit_params = {}
+            for param in watchpoint_hit_proto.watch_condition.params:
+                if param.actual_value:
+                    hit_params[param.name] = param.actual_value
+            for i, param in enumerate(watchpoint_hit['watchpoint'].condition['params']):
+                name = param['name']
+                if name in hit_params.keys():
+                    watchpoint_hit['watchpoint'].condition['params'][i]['actual_value'] = hit_params[name]
+                else:
+                    watchpoint_hit['watchpoint'].condition['params'][i]['actual_value'] = None
+            if watchpoint_hit_proto.error_code:
+                watchpoint_hit['error_code'] = watchpoint_hit_proto.error_code
             watchpoint_hits.append(watchpoint_hit)
         self._received_hit = watchpoint_hits
         reply = get_ack_reply()

mindinsight/debugger/debugger_server.py

@@ -20,9 +20,9 @@ from threading import Thread
 
 import grpc
 
-from mindinsight.conditionmgr.condition import ConditionContext
-from mindinsight.conditionmgr.conditionmgr import ConditionMgr
-from mindinsight.conditionmgr.recommender import recommend_watchpoints
+from mindinsight.debugger.conditionmgr.condition import ConditionContext
+from mindinsight.debugger.conditionmgr.conditionmgr import ConditionMgr
+from mindinsight.debugger.conditionmgr.recommender import recommend_watchpoints
 from mindinsight.conf import settings
 from mindinsight.datavisual.data_transform.graph import NodeTypeEnum
 from mindinsight.datavisual.utils.tools import to_float
@@ -517,7 +517,6 @@ class DebuggerServer:
                         "params": [
                             {
                                 "name": "abs_mean_gt",
-                                "disable": false,
                                 "value": 1.1
                             }
                         ]

mindinsight/debugger/stream_cache/watchpoint.py

@@ -13,12 +13,12 @@
 # limitations under the License.
 # ============================================================================
 """Define the watchpoint stream."""
-from mindinsight.conditionmgr.common.utils import NodeBasicInfo
+from mindinsight.debugger.conditionmgr.common.utils import NodeBasicInfo
 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
 from mindinsight.debugger.proto.debug_grpc_pb2 import SetCMD, WatchCondition
-from mindinsight.conditionmgr.condition import ConditionIdEnum
+from mindinsight.debugger.conditionmgr.condition import ConditionIdEnum
 
 
 WATCHPOINT_CONDITION_MAPPING = {
@@ -46,11 +46,8 @@ WATCHPOINT_CONDITION_MAPPING = {
     ConditionIdEnum.WEIGHT_TOO_SMALL.value: WatchCondition.Condition.tensor_too_small,
     ConditionIdEnum.GRADIENT_VANISHING.value: WatchCondition.Condition.tensor_too_small,
     ConditionIdEnum.TENSOR_ALL_ZERO.value: WatchCondition.Condition.tensor_all_zero,
-    ConditionIdEnum.TENSOR_CHANGE_TOO_LARGE.value: WatchCondition.Condition.tensor_change_too_large,
     ConditionIdEnum.WEIGHT_CHANGE_TOO_LARGE.value: WatchCondition.Condition.tensor_change_too_large,
-    ConditionIdEnum.TENSOR_CHANGE_TOO_SMALL.value: WatchCondition.Condition.tensor_change_too_small,
     ConditionIdEnum.WEIGHT_CHANGE_TOO_SMALL.value: WatchCondition.Condition.tensor_change_too_small,
-    ConditionIdEnum.TENSOR_NOT_CHANGED.value: WatchCondition.Condition.tensor_not_changed,
     ConditionIdEnum.WEIGHT_NOT_CHANGED.value: WatchCondition.Condition.tensor_not_changed
 }
 
@@ -288,7 +285,7 @@ class Watchpoint:
             param_proto = set_cmd.watch_condition.params.add()
             param_proto.name = param.get('name')
             param_proto.value = param.get('value')
-            param_proto.disabled = param.get('disable')
+            param_proto.disabled = False
 
             # Only one parameter of condition in current version.
             set_cmd.watch_condition.value = param.get('value')
@@ -317,6 +314,7 @@ class WatchpointHit:
         self.node_name = node_name
         self.slot = tensor_proto.slot
         self.graph_name = graph_name
+        self.error_code = 0
 
     @property
     def tensor_full_name(self):

mindinsight/debugger/stream_handler/graph_handler.py

@@ -13,8 +13,8 @@
 # limitations under the License.
 # ============================================================================
 """Define the graph stream handler."""
-from mindinsight.conditionmgr.common.utils import NodeBasicInfo
-from mindinsight.conditionmgr.condition import TargetTypeEnum as CategoryTypeEnum
+from mindinsight.debugger.conditionmgr.common.utils import NodeBasicInfo
+from mindinsight.debugger.conditionmgr.condition import TargetTypeEnum as CategoryTypeEnum
 from mindinsight.debugger.common.exceptions.exceptions import DebuggerParamValueError, \
     DebuggerNodeNotInGraphError, DebuggerGraphNotExistError
 from mindinsight.debugger.common.log import LOGGER as log

mindinsight/debugger/stream_handler/watchpoint_handler.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 """Define the watchpoint stream handler."""
-from mindinsight.conditionmgr.condition import ValueTypeEnum
+from mindinsight.debugger.conditionmgr.condition import ValueTypeEnum
 from mindinsight.debugger.common.exceptions.exceptions import DebuggerParamValueError, \
     DebuggerParamTypeError
 from mindinsight.debugger.common.log import LOGGER as log
@@ -256,7 +256,6 @@ class WatchpointHandler(StreamHandlerBase):
                     "params": [
                         {
                             "name": "abs_mean_gt",
-                            "disable": false,
                             "value": 1.1
                         }
                     ]
@@ -403,6 +402,8 @@ class WatchpointHitHandler(StreamHandlerBase):
             node_name=value.get('node_name'),
             graph_name=value.get('graph_name')
         )
+        if 'error_code' in value.keys():
+            watchpoint_hit.error_code = value.get('error_code')
         # get all hit watchpoints according to node name ans tensor slot
         watchpoint_hits = self._get_watchpoints_by_tensor_name(watchpoint_hit.node_name,
                                                                watchpoint_hit.slot)
@@ -482,10 +483,24 @@ class WatchpointHitHandler(StreamHandlerBase):
             dict, tensor hit info.
         """
         res = {}
-        watch_points = [tensor_hit.watchpoint for tensor_hit in tensor_hits]
+        watch_points = []
+        error_codes = set()
+        for tensor_hit in tensor_hits:
+            error_code = tensor_hit.error_code
+            watchpoint = tensor_hit.watchpoint
+            watchpoint['error_code'] = error_code
+            watch_points.append(watchpoint)
+            error_codes.add(error_code)
+
+        summarized_error_code = error_codes.pop()
+        while error_codes:
+            temp = error_codes.pop()
+            summarized_error_code = summarized_error_code | temp
+
         if watch_points:
             res = {
                 'slot': slot,
+                'summarized_error_code': summarized_error_code,
                 'watch_points': watch_points
             }
         return res
@@ -608,7 +623,6 @@ def set_default_param(condition_mgr, watch_condition):
                 "params": [
                     {
                         "name": "abs_mean_gt",
-                        "disable": false,
                         "value": 1.1
                     }
                 ]
@@ -625,7 +639,6 @@ def set_default_param(condition_mgr, watch_condition):
         if not param.visible_on_ui and not param.support_disable:
             watch_condition["params"].append({
                 "name": param.name,
-                "disable": False,
                 "value": param.default_value
             })
     watch_condition["abbr"] = condition.abbr

mindinsight/debugger/stream_operator/watchpoint_operator.py

@@ -14,8 +14,10 @@
 # ============================================================================
 """This module is aimed to deal with watchpoint commands."""
 
-from mindinsight.conditionmgr.common.utils import NodeBasicInfo
-from mindinsight.conditionmgr.condition import ConditionIdEnum
+from mindinsight.debugger.conditionmgr.common.utils import NodeBasicInfo
+from mindinsight.debugger.conditionmgr.condition import ConditionIdEnum, TargetTypeEnum
+from mindinsight.debugger.conditionmgr.recommender import get_basic_node_info
+from mindinsight.debugger.stream_handler.watchpoint_handler import validate_watch_condition
 from mindinsight.debugger.common.exceptions.exceptions import DebuggerParamValueError, \
     DebuggerCreateWatchPointError, DebuggerUpdateWatchPointError, \
     DebuggerDeleteWatchPointError
@@ -44,7 +46,6 @@ class WatchpointOperator:
                         "params": [
                             {
                                 "name": "abs_mean_gt",
-                                "disable": false,
                                 "value": 1.1
                             }
                         ]
@@ -73,6 +74,14 @@ class WatchpointOperator:
             node_names=params.get('watch_nodes'),
             search_pattern=params.get('search_pattern'),
             graph_name=params.get('graph_name'))
+
+        validate_watch_condition(self._condition_mgr, watch_condition)
+        condition_id = watch_condition.get('id')
+        condition = self._condition_mgr.get_condition(condition_id)
+        if condition.supported_target_type in [TargetTypeEnum.ACTIVATION, TargetTypeEnum.GRADIENT,
+                                               TargetTypeEnum.WEIGHT]:
+            watch_nodes = get_basic_node_info(condition.supported_target_type.value, self._graph_stream).copy()
+
         watchpoint_stream = self._watchpoint_stream
         watch_point_id = watchpoint_stream.create_watchpoint(
             self._condition_mgr, watch_condition, watch_nodes, params.get('watch_point_id'))

tests/st/func/debugger/expect_results/restful_results/retrieve_tensor_graph-0.json

@@ -1,184 +1 @@
-{
-  "graph": {
-    "nodes": [
-      {
-        "name": "Default/args0",
-        "full_name": "Default/args0",
-        "type": "Parameter",
-        "input": {},
-        "output": {
-          "Default/TransData-op99": {
-            "shape": [
-              [
-                32,
-                1,
-                32,
-                32
-              ]
-            ],
-            "edge_type": "data",
-            "independent_layout": false,
-            "data_type": "DT_TENSOR[DT_FLOAT32]",
-            "slot_mapping": [
-              [
-                "0",
-                ""
-              ]
-            ]
-          }
-        },
-        "slots": [
-          {
-            "slot": "0",
-            "statistics": {
-              "overall_max": 6.0,
-              "overall_min": 1.0,
-              "overall_avg": 3.5,
-              "overall_count": 6,
-              "overall_nan_count": 0,
-              "overall_neg_inf_count": 0,
-              "overall_pos_inf_count": 0,
-              "overall_zero_count": 0.0,
-              "overall_neg_zero_count": 0.0,
-              "overall_pos_zero_count": 6.0
-            },
-            "shape": [
-              2,
-              3
-            ],
-            "has_prev_step": true
-          }
-        ],
-        "graph_name": "graph_0"
-      },
-      {
-        "name": "Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op190",
-        "full_name": "Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op190",
-        "type": "Cast",
-        "input": {
-          "Default/TransData-op99": {
-            "shape": [
-              [
-                32,
-                1,
-                32,
-                32
-              ]
-            ],
-            "edge_type": "data",
-            "independent_layout": false,
-            "data_type": "DT_TENSOR[DT_FLOAT32]",
-            "slot_mapping": [
-              [
-                "0",
-                ""
-              ]
-            ]
-          }
-        },
-        "output": {},
-        "slots": [
-          {
-            "slot": "0",
-            "statistics": {
-              "overall_max": 6.0,
-              "overall_min": 1.0,
-              "overall_avg": 3.5,
-              "overall_count": 6,
-              "overall_nan_count": 0,
-              "overall_neg_inf_count": 0,
-              "overall_pos_inf_count": 0,
-              "overall_zero_count": 0.0,
-              "overall_neg_zero_count": 0.0,
-              "overall_pos_zero_count": 6.0
-            },
-            "shape": [
-              2,
-              3
-            ]
-          }
-        ],
-        "graph_name": "graph_0"
-      },
-      {
-        "name": "Default/TransData-op99",
-        "full_name": "Default/TransData-op99",
-        "type": "TransData",
-        "input": {
-          "Default/args0": {
-            "shape": [
-              [
-                32,
-                1,
-                32,
-                32
-              ]
-            ],
-            "edge_type": "data",
-            "independent_layout": false,
-            "data_type": "DT_TENSOR[DT_FLOAT32]",
-            "slot_mapping": [
-              [
-                "0",
-                ""
-              ]
-            ]
-          }
-        },
-        "output": {
-          "Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op190": {
-            "shape": [
-              [
-                32,
-                1,
-                32,
-                32
-              ]
-            ],
-            "edge_type": "data",
-            "independent_layout": false,
-            "data_type": "DT_TENSOR[DT_FLOAT32]",
-            "slot_mapping": [
-              [
-                "0",
-                ""
-              ]
-            ]
-          }
-        },
-        "slots": [
-          {
-            "slot": "0",
-            "watch_points": [
-              {
-                "id": 1,
-                "watch_condition": {
-                  "id": "inf",
-                  "params": [],
-                  "abbr": "INF"
-                }
-              }
-            ],
-            "statistics": {
-              "overall_max": 6.0,
-              "overall_min": 1.0,
-              "overall_avg": 3.5,
-              "overall_count": 6,
-              "overall_nan_count": 0,
-              "overall_neg_inf_count": 0,
-              "overall_pos_inf_count": 0,
-              "overall_zero_count": 0.0,
-              "overall_neg_zero_count": 0.0,
-              "overall_pos_zero_count": 6.0
-            },
-            "shape": [
-              2,
-              3
-            ]
-          }
-        ],
-        "graph_name": "graph_0"
-      }
-    ]
-  }
-}
+{"graph": {"nodes": [{"name": "Default/args0", "full_name": "Default/args0", "type": "Parameter", "input": {}, "output": {"Default/TransData-op99": {"shape": [[32, 1, 32, 32]], "edge_type": "data", "independent_layout": false, "data_type": "DT_TENSOR[DT_FLOAT32]", "slot_mapping": [["0", ""]]}}, "slots": [{"slot": "0", "statistics": {"overall_max": 6.0, "overall_min": 1.0, "overall_avg": 3.5, "overall_count": 6, "overall_nan_count": 0, "overall_neg_inf_count": 0, "overall_pos_inf_count": 0, "overall_zero_count": 0.0, "overall_neg_zero_count": 0.0, "overall_pos_zero_count": 6.0}, "shape": [2, 3], "has_prev_step": true}], "graph_name": "graph_0"}, {"name": "Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op190", "full_name": "Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op190", "type": "Cast", "input": {"Default/TransData-op99": {"shape": [[32, 1, 32, 32]], "edge_type": "data", "independent_layout": false, "data_type": "DT_TENSOR[DT_FLOAT32]", "slot_mapping": [["0", ""]]}}, "output": {}, "slots": [{"slot": "0", "statistics": {"overall_max": 6.0, "overall_min": 1.0, "overall_avg": 3.5, "overall_count": 6, "overall_nan_count": 0, "overall_neg_inf_count": 0, "overall_pos_inf_count": 0, "overall_zero_count": 0.0, "overall_neg_zero_count": 0.0, "overall_pos_zero_count": 6.0}, "shape": [2, 3]}], "graph_name": "graph_0"}, {"name": "Default/TransData-op99", "full_name": "Default/TransData-op99", "type": "TransData", "input": {"Default/args0": {"shape": [[32, 1, 32, 32]], "edge_type": "data", "independent_layout": false, "data_type": "DT_TENSOR[DT_FLOAT32]", "slot_mapping": [["0", ""]]}}, "output": {"Default/network-WithLossCell/_backbone-LeNet5/conv1-Conv2d/Cast-op190": {"shape": [[32, 1, 32, 32]], "edge_type": "data", "independent_layout": false, "data_type": "DT_TENSOR[DT_FLOAT32]", "slot_mapping": [["0", ""]]}}, "slots": [{"slot": "0", "summarized_error_code": 0, "watch_points": [{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}, "error_code": 0}], "statistics": {"overall_max": 6.0, "overall_min": 1.0, "overall_avg": 3.5, "overall_count": 6, "overall_nan_count": 0, "overall_neg_inf_count": 0, "overall_pos_inf_count": 0, "overall_zero_count": 0.0, "overall_neg_zero_count": 0.0, "overall_pos_zero_count": 6.0}, "shape": [2, 3]}], "graph_name": "graph_0"}]}}

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

@@ -1 +1 @@
-{"watch_point_hits": [{"node_name": "Default/TransData-op99", "tensors": [{"slot": "0", "watch_points": [{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}]}], "graph_name": "graph_0"}, {"node_name": "Default/optimizer-Momentum/ApplyMomentum[8]_1/ApplyMomentum-op25", "tensors": [{"slot": "0", "watch_points": [{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}}]}], "graph_name": "graph_0"}]}
+{"watch_point_hits": [{"node_name": "Default/TransData-op99", "tensors": [{"slot": "0", "summarized_error_code": 0, "watch_points": [{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}, "error_code": 0}]}], "graph_name": "graph_0"}, {"node_name": "Default/optimizer-Momentum/ApplyMomentum[8]_1/ApplyMomentum-op25", "tensors": [{"slot": "0", "summarized_error_code": 0, "watch_points": [{"id": 1, "watch_condition": {"id": "inf", "params": [], "abbr": "INF"}, "error_code": 0}]}], "graph_name": "graph_0"}]}

tests/ut/debugger/expected_results/watchpoint/watchpoint_hit_handler_get_0.json

@@ -5,9 +5,11 @@
       "tensors": [
         {
           "slot": "0",
+          "summarized_error_code": 0,
           "watch_points": [
             {
               "id": 1,
+              "error_code": 0,
               "watch_condition": {
                 "condition": "MAX_GT",
                 "param": 1

tests/ut/debugger/stream_handler/test_watchpoint_handler.py

@@ -25,7 +25,7 @@ from unittest import mock, TestCase
 import pytest
 from google.protobuf import json_format
 
-from mindinsight.conditionmgr.conditionmgr import ConditionMgr
+from mindinsight.debugger.conditionmgr.conditionmgr import ConditionMgr
 from mindinsight.debugger.common.exceptions.exceptions import DebuggerParamValueError, \
     DebuggerParamTypeError
 from mindinsight.debugger.common.log import LOGGER as log

tests/ut/debugger/test_debugger_grpc_server.py

@@ -23,7 +23,7 @@ from unittest.mock import MagicMock
 
 import numpy as np
 
-from mindinsight.conditionmgr.conditionmgr import ConditionMgr
+from mindinsight.debugger.conditionmgr.conditionmgr import ConditionMgr
 from mindinsight.debugger.common.utils import get_ack_reply, ServerStatus
 from mindinsight.debugger.debugger_cache import DebuggerCache
 from mindinsight.debugger.debugger_grpc_server import DebuggerGrpcServer

tests/ut/debugger/test_debugger_server.py

@@ -190,7 +190,7 @@ class TestDebuggerServer:
     def test_create_watchpoint_with_wrong_state(self):
         """Test create watchpoint with wrong state."""
         with pytest.raises(DebuggerCreateWatchPointError, match='Failed to create watchpoint'):
-            self._server.create_watchpoint({'watch_condition': {'condition': 'INF'}})
+            self._server.create_watchpoint({'watch_condition': {'id': 'inf'}})
 
     @mock.patch.object(MetadataHandler, 'state', 'waiting')
     @mock.patch.object(GraphHandler, 'get_node_basic_info', return_value=[MagicMock()])
@@ -199,7 +199,7 @@ class TestDebuggerServer:
     def test_create_watchpoint(self, *args):
         """Test create watchpoint."""
         args[0].return_value = 1
-        res = self._server.create_watchpoint({'watch_condition': {'condition': 'INF'},
+        res = self._server.create_watchpoint({'watch_condition': {'id': 'inf'},
                                               'watch_nodes': ['watch_node_name']})
         assert res == {'id': 1, 'metadata': {'enable_recheck': False, 'state': 'waiting'}}