[RUNTIME] Fix graph runtime for gpu

python/tvm/contrib/graph_runtime.py

@@ -72,6 +72,7 @@ def __init__(self, module, ctx):
         self._set_input = module["set_input"]
         self._run = module["run"]
         self._get_output = module["get_output"]
+        self._load_params = module["load_params"]
         self.ctx = ctx
 
     def set_input(self, key=None, value=None, **params):
@@ -120,6 +121,16 @@ def get_output(self, index, out):
         self._get_output(index, out)
         return out
 
+    def load_params(self, params_bytes):
+        """Load parameters from serialized byte array of parameter dict.
+
+        Parameters
+        ----------
+        params_bytes : bytearray
+            The serialized parameter dict.
+        """
+        self._load_params(bytearray(params_bytes))
+
     def __getitem__(self, key):
         """Get internal module function
 

src/runtime/graph/graph_runtime.cc

@@ -299,7 +299,7 @@ class GraphRuntime : public ModuleNode {
       }
       CHECK_EQ(bitmask, 1|2|4|8|16) << "invalid format";
   }
-  bool LoadDLTensor(dmlc::Stream* strm, DLTensor* tensor);
+  void LoadDLTensor(dmlc::Stream* strm, DLTensor* tensor);
   /*! \brief Setup the temporal storage */
   void SetupStorage();
   /*! \brief Setup the executors */
@@ -353,7 +353,7 @@ class GraphRuntime : public ModuleNode {
 };
 
 
-bool GraphRuntime::LoadDLTensor(dmlc::Stream* strm, DLTensor* tensor) {
+void GraphRuntime::LoadDLTensor(dmlc::Stream* strm, DLTensor* dst) {
   uint64_t header, reserved;
   CHECK(strm->Read(&header, sizeof(header)))
       << "Invalid DLTensor file format";
@@ -362,30 +362,37 @@ bool GraphRuntime::LoadDLTensor(dmlc::Stream* strm, DLTensor* tensor) {
   CHECK(header == kTVMNDArrayMagic)
       << "Invalid DLTensor file format";
 
-  CHECK(strm->Read(&tensor->ctx, sizeof(tensor->ctx)))
+  DLTensor tensor;
+  CHECK(strm->Read(&tensor.ctx, sizeof(tensor.ctx)))
       << "Invalid DLTensor file format";
-  CHECK(strm->Read(&tensor->ndim, sizeof(tensor->ndim)))
+  CHECK(strm->Read(&tensor.ndim, sizeof(tensor.ndim)))
       << "Invalid DLTensor file format";
-  CHECK(strm->Read(&tensor->dtype, sizeof(tensor->dtype)))
+  CHECK(strm->Read(&tensor.dtype, sizeof(tensor.dtype)))
       << "Invalid DLTensor file format";
-
-  int ndim = tensor->ndim;
-  CHECK(strm->Read(tensor->shape, sizeof(int64_t) * ndim))
+  std::vector<int64_t> shape(tensor.ndim);
+  CHECK(strm->Read(&shape[0], sizeof(int64_t) * tensor.ndim))
       << "Invalid DLTensor file format";
-
-  int64_t size = 1;
-  int type_size = tensor->dtype.bits / 8;
-  for (int i = 0; i < ndim; ++i) {
-    size *= tensor->shape[i];
+  CHECK_EQ(tensor.ndim, dst->ndim) << "param dimension mismatch";
+  CHECK(tensor.dtype.bits == dst->dtype.bits &&
+        tensor.dtype.code == dst->dtype.code &&
+        tensor.dtype.lanes == dst->dtype.lanes) << "param type mismatch";
+  for (int i = 0; i < tensor.ndim; ++i) {
+    CHECK_EQ(shape[i], dst->shape[i]) << "param shape mismatch";
+  }
+  size_t bits = dst->dtype.bits * dst->dtype.lanes;
+  size_t size = (bits + 7) / 8;
+  for (int i = 0; i < dst->ndim; ++i) {
+    size *= dst->shape[i];
   }
   int64_t data_byte_size;
   CHECK(strm->Read(&data_byte_size, sizeof(data_byte_size)))
       << "Invalid DLTensor file format";
-  CHECK(data_byte_size == type_size * size)
+  CHECK(data_byte_size == size)
       << "Invalid DLTensor file format";
-  CHECK(strm->Read(tensor->data, type_size * size))
+  std::vector<uint8_t> bytes(data_byte_size + 1);
+  CHECK(strm->Read(&bytes[0], data_byte_size))
       << "Invalid DLTensor file format";
-  return true;
+  TVM_CCALL(TVMArrayCopyFromBytes(dst, &bytes[0], data_byte_size));
 }
 
 void GraphRuntime::LoadParams(dmlc::Stream* strm) {
@@ -406,11 +413,11 @@ void GraphRuntime::LoadParams(dmlc::Stream* strm) {
 
   CHECK(size == names.size())
       << "Invalid parameters file format";
-
   for (size_t i = 0; i < size; ++i) {
     uint32_t in_idx = GetInputIndex(names[i]);
-    CHECK(LoadDLTensor(strm, &data_entry_[this->entry_id(input_nodes_[in_idx], 0)]))
-        << "Invalid parameters file format";
+    uint32_t eid = this->entry_id(input_nodes_[in_idx], 0);
+    CHECK_LT(eid, data_entry_.size());
+    LoadDLTensor(strm, &data_entry_[eid]);
   }
 }
 
@@ -461,6 +468,7 @@ void GraphRuntime::SetupStorage() {
   // Assign the pooled entries.
   for (size_t i = 0; i < data_entry_.size(); ++i) {
     int storage_id = attrs_.storage_id[i];
+    CHECK_LT(static_cast<size_t>(storage_id), storage_pool_.size());
     data_entry_[i] = *storage_pool_[storage_id];
     data_entry_[i].shape = const_cast<int64_t*>(attrs_.shape[i].data());
     data_entry_[i].ndim = static_cast<int>(attrs_.shape[i].size());