fix the bug for tensor history

mindinsight/backend/debugger/debugger_api.py

@@ -126,7 +126,7 @@ def tensor_comparisons():
 
     Examples:
         >>> Get http://xxxx/v1/mindinsight/debugger/tensor-comparisons?
-            name=node_name&detail=data&shape=[0, 0, :, :]&tolerance=0.5
+        >>> name=node_name&detail=data&shape=[0, 0, :, :]&tolerance=0.5
     """
     name = request.args.get('name')
     detail = request.args.get('detail', 'data')

mindinsight/debugger/debugger_grpc_server.py

@@ -257,7 +257,6 @@ class DebuggerGrpcServer(grpc_server_base.EventListenerServicer):
     def SendTensors(self, request_iterator, context):
         """Send tensors into DebuggerCache."""
         log.info("Received tensor.")
-        self._received_view_cmd['wait_for_tensor'] = False
         tensor_construct = []
         tensor_stream = self._cache_store.get_stream_handler(Streams.TENSOR)
         metadata_stream = self._cache_store.get_stream_handler(Streams.METADATA)
@@ -266,6 +265,8 @@ class DebuggerGrpcServer(grpc_server_base.EventListenerServicer):
         for tensor in request_iterator:
             tensor_construct.append(tensor)
             if tensor.finished:
+                if self._received_view_cmd.get('wait_for_tensor') and tensor.tensor_content:
+                    self._received_view_cmd['wait_for_tensor'] = False
                 tensor_stream.put({'step': step, 'tensor_protos': tensor_construct})
                 tensor_construct = []
                 tensor_names.append(':'.join([tensor.node_name, tensor.slot]))

mindinsight/debugger/debugger_server.py

@@ -445,8 +445,7 @@ class DebuggerServer:
         if metadata_stream.state != ServerStatus.WAITING.value:
             log.error("Failed to create watchpoint as the MindSpore is not in waiting state.")
             raise DebuggerCreateWatchPointError(
-                "Failed to create watchpoint as the MindSpore is not in waiting state."
-            )
+                "Failed to create watchpoint as the MindSpore is not in waiting state.")
         if metadata_stream.backend == 'GPU' and watch_condition.get('condition') == 'OVERFLOW':
             log.error("GPU doesn't support OVERFLOW watch condition.")
             raise DebuggerParamValueError("GPU doesn't support OVERFLOW watch condition.")

mindinsight/debugger/stream_cache/tensor.py

@@ -152,7 +152,9 @@ class OpTensor(BaseTensor):
             statistics = TensorUtils.get_statistics_from_tensor(tensor_value)
             res['statistics'] = TensorUtils.get_statistics_dict(statistics)
             res['value'] = tensor_value.tolist()
-            return res
+        elif isinstance(tensor_value, str):
+            res['value'] = tensor_value
+
         return res
 
     def get_tensor_value_by_shape(self, shape=None):
@@ -188,6 +190,7 @@ class OpTensor(BaseTensor):
             value = np.asarray(value)
         return value
 
+
 class ConstTensor(BaseTensor):
     """Tensor data structure for Const Node."""
 

mindinsight/debugger/stream_handler/tensor_handler.py

@@ -188,6 +188,9 @@ class TensorHandler(StreamHandlerBase):
             # add `has_prev_step` field to tensor basic info.
             if basic_info:
                 tensor_info.update(basic_info)
+                if not basic_info.get('value'):
+                    missed_tensors.append(tensor_info)
+                    log.debug("Add view cmd for %s", tensor_name)
             else:
                 missed_tensors.append(tensor_info)
                 log.debug("Add view cmd for %s", tensor_name)
@@ -221,13 +224,7 @@ class TensorHandler(StreamHandlerBase):
         if prev_step < 0:
             return flag
         tensor = self._get_tensor(tensor_name, step=prev_step)
-        if not tensor:
-            # the tensor need to be queried from client
-            flag = False
-        elif tensor.value:
-            flag = True
-
-        return flag
+        return bool(tensor and tensor.valule)
 
     def get_tensor_value_by_name(self, tensor_name, prev=False):
         """Get tensor value by name in numpy type."""
@@ -283,13 +280,16 @@ class TensorHandler(StreamHandlerBase):
         curr_tensor_slice = curr_tensor.get_tensor_value_by_shape(shape)
         prev_tensor_slice = prev_tensor.get_tensor_value_by_shape(shape)
         tensor_info = curr_tensor.get_basic_info()
+        if isinstance(tensor_info, dict):
+            del tensor_info['has_prev_step']
+            del tensor_info['value']
         if isinstance(curr_tensor_slice, np.ndarray) and isinstance(prev_tensor_slice, np.ndarray):
             diff_tensor = TensorUtils.calc_diff_between_two_tensor(curr_tensor_slice, prev_tensor_slice, tolerance)
             result = np.stack([prev_tensor_slice, curr_tensor_slice, diff_tensor], axis=-1)
             tensor_info['diff'] = result.tolist()
             stats = TensorUtils.get_statistics_from_tensor(diff_tensor)
             tensor_info['statistics'] = TensorUtils.get_statistics_dict(stats)
-            del tensor_info['has_prev_step']
-            del tensor_info['value']
+        elif isinstance(curr_tensor_slice, str):
+            tensor_info['diff'] = curr_tensor_slice
         reply = {'tensor_value': tensor_info}
         return reply