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modified the code to dump the tensor shape #1

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modified the code to dump the tensor shape #1

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fae4d5a
modified the code to dump the tensor shape
Apr 20, 2018
eca4280
fix bugs
Apr 20, 2018
0bc88b2
fix bugs
Apr 22, 2018
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89 changes: 60 additions & 29 deletions tensorflow/core/common_runtime/executor.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -2396,35 +2396,66 @@ void ExecutorState::FrameState::ActivateNodes(const NodeItem* item,
}
const Node *node = item->node;
fprintf(dump_file_shape, "op[%s][%s][%s][%d]", node->type_string().data(), node->name().data(), node->assigned_device_name().data(), node->id());
std::vector<int> out_node_id_array;
for (Node *out: node->out_nodes()) {
fprintf(dump_file_shape, "\t%d", out->id());
out_node_id_array.push_back(out->id());
}
// std::vector<int> out_node_id_array;
// for (Node *out: node->out_nodes()) {
// fprintf(dump_file_shape, "\t%d", out->id());
// out_node_id_array.push_back(out->id());
// }
fprintf(dump_file_shape, "\n");
const EdgeSet& out_edges = node->out_edges();
fprintf(dump_file_shape, "edge");
for (EdgeSet::const_iterator iter = out_edges.begin(); iter != out_edges.end(); iter++) {
fprintf(dump_file_shape, "\t%d", (*iter)->src_output());
}
fprintf(dump_file_shape,"\n");
for (int i = 0; i < item->num_outputs; ++i) {
const Entry& out = ((*outputs)[i]);
Tensor const * t;
if (!out.has_value) {
t = kEmptyTensor;
} else if (out.ref == nullptr) {
t = out.val.get();
} else {
t = out.ref;
}
// quanlu: dump shape
fprintf(dump_file_shape, "one_output");
for (int j = 0; j < t->dims(); ++j) {
int64 ds = t->dim_size(j);
fprintf(dump_file_shape, "\t%lld", ds);

//yunteng: get che output and their shape
const EdgeInfo* edges = item->output_edge_list();
const size_t num_output_edges = item->num_output_edges;
for (size_t out_index = 0; out_index < num_output_edges; out_index++){
const EdgeInfo& e = edges[out_index];
const int dst_id = e.dst_id;
const int src_slot = e.output_slot;
fprintf(dump_file_shape, "edge: %d ", dst_id);
if (src_slot == Graph::kControlSlot){//src_slot=-1, so that it is a control edge
fprintf(dump_file_shape, "{-1}\n");
}else{
fprintf(dump_file_shape, "{");
const Entry& out = (*outputs)[src_slot];
const Tensor* t;
if(!out.has_value){
t = kEmptyTensor;
}else if(out.ref == nullptr){
t =out.val.get();
}else{
t = out.ref;
}
for(int j = 0; j < t->dims(); j++){
int64 ds = t->dim_size(j);
fprintf(dump_file_shape, "%d ", ds);
}
fprintf(dump_file_shape, "}\n");
}
fprintf(dump_file_shape, "\n");

}

// const EdgeSet& out_edges = node->out_edges();
// fprintf(dump_file_shape, "edge");
// for (EdgeSet::const_iterator iter = out_edges.begin(); iter != out_edges.end(); iter++) {
// fprintf(dump_file_shape, "\t%d", (*iter)->src_output());
// }
// fprintf(dump_file_shape,"\n");
// for (int i = 0; i < item->num_outputs; ++i) {
// const Entry& out = ((*outputs)[i]);
// Tensor const * t;
// if (!out.has_value) {
// t = kEmptyTensor;
// } else if (out.ref == nullptr) {
// t = out.val.get();
// } else {
// t = out.ref;
// }
// // quanlu: dump shape
// fprintf(dump_file_shape, "one_output");
// for (int j = 0; j < t->dims(); ++j) {
// int64 ds = t->dim_size(j);
// fprintf(dump_file_shape, "\t%lld", ds);
// }
// fprintf(dump_file_shape, "\n");
// quanlu: dump tensor content
/*if (t == kEmptyTensor) {
printf("empty tensor\n");
Expand Down Expand Up @@ -2467,7 +2498,7 @@ void ExecutorState::FrameState::ActivateNodes(const NodeItem* item,
tmp_proto.SerializeToFileDescriptor(dump_file_tensor);
}*/
// dump buf_ directly
if (t->IsInitialized() && t->NumElements() != 0) {
/* if (t->IsInitialized() && t->NumElements() != 0) {
int src_id = node->id();
//int dst_id = out_node_id_array[i];
int output_index = i;
Expand All @@ -2492,7 +2523,7 @@ void ExecutorState::FrameState::ActivateNodes(const NodeItem* item,
ret = write(dump_file_tensor, ptr, len);
if (ret != len) { printf("tensor content error, %d, %p, %d, %d\n", ret, ptr, len, errno); exit(-1); }
}
}
*/
fclose(dump_file_shape);
close(dump_file_tensor);
}
Expand Down