eric-haibin-lin commented on a change in pull request #10882: move exec.reshape
to backend
URL: https://github.com/apache/incubator-mxnet/pull/10882#discussion_r187844712
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File path: src/executor/graph_executor.cc
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@@ -1043,6 +1043,108 @@ void GraphExecutor::Init(nnvm::Symbol symbol,
FinishInitGraph(symbol, g, shared_exec, feed_dict);
}
+/*!
+ * \brief Return a new executor with the same symbol and shared memory,
+ * but different input/output shapes.
+ * For runtime reshaping, variable length sequences, etc.
+ * The returned executor shares state with the current one,
+ * and cannot be used in parallel with it.
+ */
+Executor* GraphExecutor::Reshape(const bool partial_shaping,
+ const bool allow_up_sizing,
+ const Context& default_ctx,
+ const std::map<std::string, Context>& ctx_map,
+ const std::unordered_map<std::string, TShape>&
+ provided_arg_shapes,
+ std::vector<NDArray>* in_args,
+ std::vector<NDArray>* arg_grads,
+ std::vector<NDArray>* aux_states) {
+ nnvm::Graph g;
+ g.outputs = std::vector<nnvm::NodeEntry>(graph_.outputs.begin(),
+ graph_.outputs.begin() + num_forward_outputs_);
+ nnvm::Symbol symbol;
+ symbol.outputs = g.outputs;
+ const nnvm::IndexedGraph& idx = g.indexed_graph();
+ nnvm::ShapeVector arg_shapes(idx.input_nodes().size(), TShape());
+ for (size_t i = 0; i < num_forward_inputs_; ++i) {
+ const uint32_t nid = idx.input_nodes().at(i);
+ const std::string& name = idx[nid].source->attrs.name;
+ auto it = provided_arg_shapes.find(name);
+ if (provided_arg_shapes.end() != it) {
+ arg_shapes[i] = it->second;
+ }
+ }
+ g = InferShape(std::move(g), std::move(arg_shapes), "__shape__");
+ if (g.GetAttr<size_t>("shape_num_unknown_nodes") != 0U) {
+ HandleInferShapeError(num_forward_inputs_, g.indexed_graph(),
+ g.GetAttr<nnvm::ShapeVector>("shape"));
+ }
+ const nnvm::ShapeVector& shape_vec = g.GetAttr<nnvm::ShapeVector>("shape");
+ std::vector<OpReqType> grad_req_types;
+ size_t grad_top = 0;
+
+ std::ostringstream up_sizing_msg, unspecified_msg;
+ up_sizing_msg << ": Arg of new shape which is larger than original."
+ << "First making a big executor and then down sizing it "
+ << "is more efficient than the reverse."
+ << "If you really want to up size, set allow_up_sizing=True "
+ << "to enable allocation of new arrays.";
+ unspecified_msg << ": unspecified array's shape changed. "
+ << "This can cause the new executor to not share parameters "
+ << "with the old one. Please check for error in network."
+ << "If this is intended, set partial_shaping=True to
suppress this warning.";
+ for (uint32_t nid : idx.input_nodes()) {
+ std::string name = idx[nid].source->attrs.name;
+ const TShape& new_shape = shape_vec[idx.entry_id(nid, 0)];
+ if (idx.mutable_input_nodes().count(nid) == 0) {
+ NDArray& arr = in_arg_map_.at(name);
+ auto it = arg_grad_map_.find(name);
+ if (partial_shaping || provided_arg_shapes.count(name) || new_shape ==
arr.shape()) {
+ if (new_shape.Size() > arr.shape().Size()) {
+ CHECK(allow_up_sizing) << name << up_sizing_msg.str();
Review comment:
Need better error message
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