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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/04/23 00:11:48 UTC
[GitHub] [tvm] tkonolige commented on a change in pull request #7903: [Graph Executor Debugger] Fix parameter dump
tkonolige commented on a change in pull request #7903:
URL: https://github.com/apache/tvm/pull/7903#discussion_r618826620
##########
File path: python/tvm/contrib/debugger/debug_executor.py
##########
@@ -170,22 +173,74 @@ def _create_debug_env(self, graph_json, device):
# init the debug dumping environment
self.debug_datum = debug_result.DebugResult(graph_json, self._dump_path)
+ def _execute_next_node(self, node_index, entry_id):
+ """Execute node assuming all previous nodes has been executed.
+ Return the output of this node.
+
+ Parameters
+ ----------
+ node_index : int
+ The node index
+
+ entry_id : int
+ The entry id.
+ """
+ out_tensor = self._execute_next_node_get_output(node_index, entry_id)
+ return array(out_tensor)
+
+ def _run_per_layer(self):
+ """Execute up to each node and each debug output will be
+ copied to the buffer.
+
+ """
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ num_outputs = self.debug_datum.get_graph_node_output_num(node)
+ for j in range(num_outputs):
+ logging.info("running: output=%d of node_name: %s", j, node["name"])
+ out_tensor = self._execute_next_node(i, j)
+ self.debug_datum._output_tensor_list.append(out_tensor)
+
+ def execute_node(self, node_name):
+ """Execute network up to this node.
+ Return the outputs of this node.
+
+ Parameters
+ ----------
+ node_index : str
Review comment:
```suggestion
node_name : str
```
##########
File path: python/tvm/contrib/debugger/debug_executor.py
##########
@@ -170,22 +173,74 @@ def _create_debug_env(self, graph_json, device):
# init the debug dumping environment
self.debug_datum = debug_result.DebugResult(graph_json, self._dump_path)
+ def _execute_next_node(self, node_index, entry_id):
+ """Execute node assuming all previous nodes has been executed.
+ Return the output of this node.
+
+ Parameters
+ ----------
+ node_index : int
+ The node index
+
+ entry_id : int
+ The entry id.
+ """
+ out_tensor = self._execute_next_node_get_output(node_index, entry_id)
+ return array(out_tensor)
+
+ def _run_per_layer(self):
+ """Execute up to each node and each debug output will be
+ copied to the buffer.
+
+ """
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ num_outputs = self.debug_datum.get_graph_node_output_num(node)
+ for j in range(num_outputs):
+ logging.info("running: output=%d of node_name: %s", j, node["name"])
+ out_tensor = self._execute_next_node(i, j)
+ self.debug_datum._output_tensor_list.append(out_tensor)
+
+ def execute_node(self, node_name):
+ """Execute network up to this node.
+ Return the outputs of this node.
+
+ Parameters
+ ----------
+ node_index : str
+ The node name
+ """
+ node_index = None
+ selected_node = None
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ if node["name"] == node_name:
+ selected_node = node
+ node_index = i
+ break
+ if not node_index:
+ raise AttributeError("Node name is not valid.")
Review comment:
```suggestion
raise AttributeError(f"Could not find a node named {node_name} in this graph.")
```
##########
File path: python/tvm/contrib/debugger/debug_executor.py
##########
@@ -170,22 +173,74 @@ def _create_debug_env(self, graph_json, device):
# init the debug dumping environment
self.debug_datum = debug_result.DebugResult(graph_json, self._dump_path)
+ def _execute_next_node(self, node_index, entry_id):
+ """Execute node assuming all previous nodes has been executed.
+ Return the output of this node.
+
+ Parameters
+ ----------
+ node_index : int
+ The node index
+
+ entry_id : int
+ The entry id.
+ """
+ out_tensor = self._execute_next_node_get_output(node_index, entry_id)
+ return array(out_tensor)
+
+ def _run_per_layer(self):
+ """Execute up to each node and each debug output will be
+ copied to the buffer.
+
+ """
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ num_outputs = self.debug_datum.get_graph_node_output_num(node)
+ for j in range(num_outputs):
+ logging.info("running: output=%d of node_name: %s", j, node["name"])
+ out_tensor = self._execute_next_node(i, j)
+ self.debug_datum._output_tensor_list.append(out_tensor)
+
+ def execute_node(self, node_name):
+ """Execute network up to this node.
+ Return the outputs of this node.
+
+ Parameters
+ ----------
+ node_index : str
+ The node name
+ """
+ node_index = None
+ selected_node = None
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ if node["name"] == node_name:
+ selected_node = node
+ node_index = i
+ break
+ if not node_index:
+ raise AttributeError("Node name is not valid.")
+
+ num_outputs = self.debug_datum.get_graph_node_output_num(selected_node)
+ output_tensors = []
+ for j in range(num_outputs):
+ out = self._execute_node_get_output(node_index, j)
Review comment:
`_execute_node_get_output` should return all of the outputs instead of making you index into them. This way we can avoid re-executing for each output.
##########
File path: src/runtime/graph_executor/debug/graph_executor_debug.cc
##########
@@ -208,25 +201,70 @@ class GraphExecutorDebug : public GraphExecutor {
}
/*!
- * \brief Copy index-th node to data_out.
+ * \brief Get number of outputs of the node.
+ * \param index The index of the node.
+ * \return The number of outputs.
+ */
+ size_t GetNodeNumOfOutputs(size_t index) {
+ if (nodes_[index].op_type != "tvm_op") return 1;
+ return static_cast<size_t>(nodes_[index].param.num_outputs);
+ }
+
+ /*!
+ * \brief Execute network to a specific node and return result.
*
* This method will do a partial run of the the graph
* from begining upto the index-th node and return output of index-th node.
* This is costly operation and suggest to use only for debug porpose.
*
- * \param index: The index of the node.
- * \param data_out the node data.
+ * \param index: The index of the node.
+ * \param eid The Entry id of the op.
+ * \return Node output array.
*/
- void DebugGetNodeOutput(int index, DLTensor* data_out) {
+ NDArray ExecuteNodeGetOutput(int index, int eid) {
ICHECK_LT(static_cast<size_t>(index), op_execs_.size());
- uint32_t eid = index;
- for (size_t i = 0; i < op_execs_.size(); ++i) {
+ for (size_t i = 0; i <= static_cast<size_t>(index); i++) {
if (op_execs_[i]) op_execs_[i]();
- if (static_cast<int>(i) == index) break;
}
- data_entry_[eid].CopyTo(data_out);
+ return data_entry_[entry_id(index, eid)];
+ }
+
+ /*!
+ * \brief Execute next node in the network.
+ *
+ * This method will execute next node assuming
+ * previous nodes has been executed and return output of index-th node.
+ *
+ * \param index: The index of the node.
+ * \param eid The Entry id of the op.
+ * \return Node output array.
+ */
+ NDArray ExecuteNextNodeGetOutput(int index, int eid) {
+ ICHECK_LT(static_cast<size_t>(index), op_execs_.size());
+ if (op_execs_[index]) op_execs_[index]();
+ return data_entry_[entry_id(index, eid)];
+ }
+
+ /*!
+ * \brief Execute full network and store each layer outputs.
+ *
+ * This method will execute a full network and store layer
+ * outputs along execution.
+ *
+ * \return All node outputs.
+ */
+ Array<NDArray> RunAndGetLayersOutputs() {
Review comment:
This function should return an `Array<Array<NDArray>>` where the outer node corresponds to the layer and the inner array is that layers outputs.
##########
File path: python/tvm/contrib/debugger/debug_executor.py
##########
@@ -170,22 +173,74 @@ def _create_debug_env(self, graph_json, device):
# init the debug dumping environment
self.debug_datum = debug_result.DebugResult(graph_json, self._dump_path)
+ def _execute_next_node(self, node_index, entry_id):
+ """Execute node assuming all previous nodes has been executed.
+ Return the output of this node.
+
+ Parameters
+ ----------
+ node_index : int
+ The node index
+
+ entry_id : int
+ The entry id.
+ """
+ out_tensor = self._execute_next_node_get_output(node_index, entry_id)
+ return array(out_tensor)
+
+ def _run_per_layer(self):
+ """Execute up to each node and each debug output will be
+ copied to the buffer.
+
+ """
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ num_outputs = self.debug_datum.get_graph_node_output_num(node)
+ for j in range(num_outputs):
+ logging.info("running: output=%d of node_name: %s", j, node["name"])
+ out_tensor = self._execute_next_node(i, j)
+ self.debug_datum._output_tensor_list.append(out_tensor)
+
+ def execute_node(self, node_name):
+ """Execute network up to this node.
+ Return the outputs of this node.
+
+ Parameters
+ ----------
+ node_index : str
+ The node name
+ """
+ node_index = None
+ selected_node = None
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ if node["name"] == node_name:
+ selected_node = node
+ node_index = i
+ break
+ if not node_index:
+ raise AttributeError("Node name is not valid.")
+
+ num_outputs = self.debug_datum.get_graph_node_output_num(selected_node)
+ output_tensors = []
+ for j in range(num_outputs):
+ out = self._execute_node_get_output(node_index, j)
+ out = array(out)
+ output_tensors.append(out)
+ return output_tensors
+
def _run_debug(self):
"""Execute the node specified with index will be executed.
Each debug output will be copied to the buffer
Time consumed for each execution will be set as debug output.
"""
+ # Get timing.
self.debug_datum._time_list = [[float(t)] for t in self.run_individual(10, 1, 1)]
- for i, node in enumerate(self.debug_datum.get_graph_nodes()):
- num_outputs = self.debug_datum.get_graph_node_output_num(node)
- for j in range(num_outputs):
- out_tensor = self._get_output_by_layer(i, j)
- out_tensor = array(out_tensor)
- self.debug_datum._output_tensor_list.append(out_tensor)
+
+ # Get outputs.
+ self._run_per_layer()
def debug_get_output(self, node, out=None):
Review comment:
Let's replace `debug_get_output` with `execute_node`. (Rename `execute_node` to `debug_get_output`).
##########
File path: python/tvm/contrib/debugger/debug_executor.py
##########
@@ -170,22 +173,74 @@ def _create_debug_env(self, graph_json, device):
# init the debug dumping environment
self.debug_datum = debug_result.DebugResult(graph_json, self._dump_path)
+ def _execute_next_node(self, node_index, entry_id):
+ """Execute node assuming all previous nodes has been executed.
+ Return the output of this node.
+
+ Parameters
+ ----------
+ node_index : int
+ The node index
+
+ entry_id : int
+ The entry id.
+ """
+ out_tensor = self._execute_next_node_get_output(node_index, entry_id)
+ return array(out_tensor)
+
+ def _run_per_layer(self):
+ """Execute up to each node and each debug output will be
+ copied to the buffer.
+
+ """
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ num_outputs = self.debug_datum.get_graph_node_output_num(node)
+ for j in range(num_outputs):
+ logging.info("running: output=%d of node_name: %s", j, node["name"])
+ out_tensor = self._execute_next_node(i, j)
+ self.debug_datum._output_tensor_list.append(out_tensor)
+
+ def execute_node(self, node_name):
+ """Execute network up to this node.
+ Return the outputs of this node.
+
+ Parameters
+ ----------
+ node_index : str
+ The node name
+ """
+ node_index = None
+ selected_node = None
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ if node["name"] == node_name:
+ selected_node = node
+ node_index = i
+ break
+ if not node_index:
+ raise AttributeError("Node name is not valid.")
+
+ num_outputs = self.debug_datum.get_graph_node_output_num(selected_node)
+ output_tensors = []
+ for j in range(num_outputs):
+ out = self._execute_node_get_output(node_index, j)
+ out = array(out)
Review comment:
Is this necessary?
##########
File path: src/runtime/graph_executor/debug/graph_executor_debug.cc
##########
@@ -208,25 +201,70 @@ class GraphExecutorDebug : public GraphExecutor {
}
/*!
- * \brief Copy index-th node to data_out.
+ * \brief Get number of outputs of the node.
+ * \param index The index of the node.
+ * \return The number of outputs.
+ */
+ size_t GetNodeNumOfOutputs(size_t index) {
Review comment:
```suggestion
size_t NodeGetNumOutputs(size_t index) {
```
##########
File path: python/tvm/contrib/debugger/debug_executor.py
##########
@@ -170,22 +173,74 @@ def _create_debug_env(self, graph_json, device):
# init the debug dumping environment
self.debug_datum = debug_result.DebugResult(graph_json, self._dump_path)
+ def _execute_next_node(self, node_index, entry_id):
+ """Execute node assuming all previous nodes has been executed.
+ Return the output of this node.
+
+ Parameters
+ ----------
+ node_index : int
+ The node index
+
+ entry_id : int
+ The entry id.
+ """
+ out_tensor = self._execute_next_node_get_output(node_index, entry_id)
+ return array(out_tensor)
+
+ def _run_per_layer(self):
+ """Execute up to each node and each debug output will be
+ copied to the buffer.
+
+ """
+ for i, node in enumerate(self.debug_datum.get_graph_nodes()):
+ num_outputs = self.debug_datum.get_graph_node_output_num(node)
+ for j in range(num_outputs):
+ logging.info("running: output=%d of node_name: %s", j, node["name"])
+ out_tensor = self._execute_next_node(i, j)
+ self.debug_datum._output_tensor_list.append(out_tensor)
+
+ def execute_node(self, node_name):
Review comment:
Document return value.
##########
File path: src/runtime/graph_executor/debug/graph_executor_debug.cc
##########
@@ -208,25 +201,70 @@ class GraphExecutorDebug : public GraphExecutor {
}
/*!
- * \brief Copy index-th node to data_out.
+ * \brief Get number of outputs of the node.
+ * \param index The index of the node.
+ * \return The number of outputs.
+ */
+ size_t GetNodeNumOfOutputs(size_t index) {
+ if (nodes_[index].op_type != "tvm_op") return 1;
+ return static_cast<size_t>(nodes_[index].param.num_outputs);
+ }
+
+ /*!
+ * \brief Execute network to a specific node and return result.
*
* This method will do a partial run of the the graph
* from begining upto the index-th node and return output of index-th node.
* This is costly operation and suggest to use only for debug porpose.
*
- * \param index: The index of the node.
- * \param data_out the node data.
+ * \param index: The index of the node.
+ * \param eid The Entry id of the op.
+ * \return Node output array.
*/
- void DebugGetNodeOutput(int index, DLTensor* data_out) {
+ NDArray ExecuteNodeGetOutput(int index, int eid) {
Review comment:
```suggestion
NDArray DebugGetNodeOutput(int index, int eid) {
```
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