feat(lite): fix typo

GitOrigin-RevId: 8c46aa3a303b8a9ad5e29b8779bb4961fa3e3a85

imperative/src/impl/backward_graph_opt.cpp

@@ -16,7 +16,7 @@
 using namespace mgb;
 using namespace imperative;
 
-OptimizedBackwardGraphResult::OptimizedBackwardGraphResult(const EncodedSubraph& src)
+OptimizedBackwardGraphResult::OptimizedBackwardGraphResult(const EncodedSubgraph& src)
         : input_has_grad(src.output_mask) {
     if (src.graph.exprs.size() <= 1) {
         // backward graph only contains a single op

imperative/src/impl/op_def.cpp

@@ -80,12 +80,12 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> OpDef::infer_output_attrs_falli
     return def.trait()->infer_output_attrs_fallible(def, inputs);
 }
 
-EncodedSubraph OpDef::make_backward_graph(
+EncodedSubgraph OpDef::make_backward_graph(
     const OpDef& def,
     const SmallVector<LogicalTensorDesc>& inputs,
     const SmallVector<bool>& input_requires_grad,
     const SmallVector<bool>& output_has_grad) {
-    using BackwardGraphCache = OpMethResultCache<EncodedSubraph, SmallVector<bool>, SmallVector<bool>>;
+    using BackwardGraphCache = OpMethResultCache<EncodedSubgraph, SmallVector<bool>, SmallVector<bool>>;
     thread_local BackwardGraphCache cache;
     decltype(cache)::key_t cache_key{const_cast<OpDef&>(def).shared_from_this(), inputs, {input_requires_grad, output_has_grad}};
     auto iter = cache.find(cache_key);
@@ -100,10 +100,10 @@ std::vector<std::pair<const char*, std::string>> OpDef::props(
     return def.trait()->props(def);
 }
 
-EncodedSubraph OpDef::make_forward_graph(
+EncodedSubgraph OpDef::make_forward_graph(
     const OpDef& def,
     const SmallVector<LogicalTensorDesc>& inputs){
-    using ForwardGraphCache = OpMethResultCache<EncodedSubraph, SmallVector<bool>, SmallVector<bool>>;
+    using ForwardGraphCache = OpMethResultCache<EncodedSubgraph, SmallVector<bool>, SmallVector<bool>>;
     thread_local ForwardGraphCache cache;
     decltype(cache)::key_t cache_key{const_cast<OpDef&>(def).shared_from_this(), inputs};
     auto iter = cache.find(cache_key);

imperative/src/impl/ops/utility.cpp

@@ -182,11 +182,11 @@ OP_TRAIT_REG(Identity, Identity)
 
 namespace { namespace subgraph {
 
-EncodedSubraph make_forward_graph(const OpDef& def, SmallVector<LogicalTensorDesc> inputs) {
-    return EncodedSubraph::make(*def.cast_final_safe<SubgraphOp>().graph);
+EncodedSubgraph make_forward_graph(const OpDef& def, SmallVector<LogicalTensorDesc> inputs) {
+    return EncodedSubgraph::make(*def.cast_final_safe<SubgraphOp>().graph);
 }
 
-EncodedSubraph make_backward_graph(
+EncodedSubgraph make_backward_graph(
         const OpDef& def, 
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,
@@ -199,7 +199,7 @@ EncodedSubraph make_backward_graph(
         }
     }
     auto bgraph = subgraph_detail::make_backward_graph(def, inputs, input_requires_grad, output_has_grad);
-    return EncodedSubraph::make_single(
+    return EncodedSubgraph::make_single(
             SubgraphOp::make(op.name + "Grad",
                              std::make_shared<Subgraph>(bgraph.graph)),
             bgraph.input_mask, bgraph.output_mask);
@@ -430,7 +430,7 @@ std::tuple<SmallVector<MemoryDesc>, SmallVector<MemoryDesc>> infer_output_mem_de
     return {};
 }
 
-EncodedSubraph make_backward_graph(
+EncodedSubgraph make_backward_graph(
         const OpDef& def, 
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,
@@ -452,7 +452,7 @@ EncodedSubraph make_backward_graph(
                 grad_outputs_has_grad, key);
     }
     auto compiled_op = CompiledOp::make(bgraph_op, op.gopt_level);
-    auto encoded_graph = EncodedSubraph::make_single(compiled_op, backward_graph.input_mask, backward_graph.output_mask);
+    auto encoded_graph = EncodedSubgraph::make_single(compiled_op, backward_graph.input_mask, backward_graph.output_mask);
     return encoded_graph;
 }
 

imperative/src/impl/proxy_graph.cpp

@@ -669,7 +669,7 @@ struct ProxyGraph::GradGraph {
     cg::VarNode* grad;
 };
 
-EncodedSubraph
+EncodedSubgraph
 ProxyGraph::make_backward_graph(
         const OpDef& opdef,
         const SmallVector<LogicalTensorDesc>& input_descs,
@@ -704,7 +704,7 @@ ProxyGraph::make_backward_graph(
     }
     auto* gfunc = cg::lookup_grad_func(fwd->dyn_typeinfo());
 
-    EncodedSubraph result;
+    EncodedSubgraph result;
     auto&& igraph = result.graph;
 
     size_t nr_backward_graph_inputs = 0;

imperative/src/impl/proxy_graph.h

@@ -40,7 +40,7 @@ public:
             const SmallVector<Tensor*>& outputs,
             const SmallVector<Tensor*>& workspace);
 
-    EncodedSubraph make_backward_graph(
+    EncodedSubgraph make_backward_graph(
             const OpDef& opdef,
             const SmallVector<LogicalTensorDesc>& input_descs,
             const SmallVector<bool>& input_requires_grad,

imperative/src/impl/proxy_graph_detail.cpp

@@ -113,7 +113,7 @@ void execute(const OpDef& def,
 //     return graph->infer_output_attrs_fallible(def, inputs);
 // }
 
-EncodedSubraph
+EncodedSubgraph
 make_backward_graph(const OpDef& def,
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,

imperative/src/impl/subgraph.cpp

@@ -101,7 +101,7 @@ void Subgraph::replace_vars(
     }
 }
 
-std::string EncodedSubraph::repr() const {
+std::string EncodedSubgraph::repr() const {
     std::string buffer;
     buffer.push_back('|');
     for (size_t i = 0; i < input_mask.size(); ++i) {
@@ -118,7 +118,7 @@ std::string EncodedSubraph::repr() const {
     return buffer;
 }
 
-size_t EncodedSubraph::hash() const {
+size_t EncodedSubgraph::hash() const {
     return std::hash<std::string>{}(repr());
 }
 

imperative/src/impl/subgraph_detail.cpp

@@ -76,11 +76,11 @@ SmallVector<TensorPtr> apply_on_physical_tensor(
     return outputs;
 }
 
-static EncodedSubraph make_backward_graph_from_forward(
+static EncodedSubgraph make_backward_graph_from_forward(
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,
         const SmallVector<bool>& output_has_grad,
-        EncodedSubraph forward_graph) {
+        EncodedSubgraph forward_graph) {
     using namespace std::placeholders;
     using var_t = Subgraph::var_t;
     using vars_t = Subgraph::vars_t;
@@ -149,7 +149,7 @@ static EncodedSubraph make_backward_graph_from_forward(
     return backward_graph;
 }
 
-EncodedSubraph make_backward_graph(
+EncodedSubgraph make_backward_graph(
         const OpDef& def, 
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,

imperative/src/include/megbrain/imperative/backward_graph_opt.h

@@ -19,7 +19,7 @@ struct OptimizedBackwardGraphResult {
     SmallVector<bool> save_for_backward;
     SmallVector<bool> input_has_grad;
 
-    OptimizedBackwardGraphResult(const EncodedSubraph& bgraph);
+    OptimizedBackwardGraphResult(const EncodedSubgraph& bgraph);
 };
 
 } // namespace mgb::imperative

imperative/src/include/megbrain/imperative/graph_builder.h

@@ -29,7 +29,7 @@ class Subgraph::Builder {
     using desc_t = TDesc;
     using descs_t = SmallVector<TDesc>;
     using infer_fn_t = std::function<descs_t(op_t, descs_t, size_t)>;
-    using encoded_graph_t = EncodedSubraph;
+    using encoded_graph_t = EncodedSubgraph;
     using var_map_t = std::unordered_map<var_t, var_t>;
     vars_t m_inputs;
     SmallVector<std::pair<var_t, TensorPtr>> m_constants;

imperative/src/include/megbrain/imperative/op_def.h

@@ -87,7 +87,7 @@ public:
         const SmallVector<TensorPtr>& inputs_tensors,
         const SmallVector<MemoryDesc>& inputs_mems);
 
-    static EncodedSubraph make_backward_graph(
+    static EncodedSubgraph make_backward_graph(
         const OpDef& def,
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,
@@ -96,7 +96,7 @@ public:
     static std::vector<std::pair<const char*, std::string>> props(
         const OpDef& def);
 
-    static EncodedSubraph make_forward_graph(
+    static EncodedSubgraph make_forward_graph(
         const OpDef& def,
         const SmallVector<LogicalTensorDesc>& inputs);
 

imperative/src/include/megbrain/imperative/ops/utility.h

@@ -40,7 +40,7 @@ struct ShapeInfer final : OpDefImplBase<ShapeInfer> {
     std::shared_ptr<OpDef> op;
     SmallVector<CompNode> devices;
     SmallVector<DType> dtypes;
-    EncodedSubraph graph;
+    EncodedSubgraph graph;
     ShapeInfer() = default;
     ShapeInfer(std::shared_ptr<OpDef> op, SmallVector<CompNode> devices,
                SmallVector<DType> dtypes)

imperative/src/include/megbrain/imperative/proxy_graph_detail.h

@@ -38,7 +38,7 @@ void exec(const OpDef& def,
         const SmallVector<TensorPtr>& inputs,
         const SmallVector<TensorPtr>& outputs);
 
-EncodedSubraph
+EncodedSubgraph
 make_backward_graph(const OpDef& def,
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,

imperative/src/include/megbrain/imperative/subgraph.h

@@ -96,7 +96,7 @@ struct Subgraph {
     bool operator==(const Subgraph& rhs) const;
 };
 
-struct EncodedSubraph {
+struct EncodedSubgraph {
     Subgraph graph;
     SmallVector<bool> input_mask;
     SmallVector<bool> output_mask;
@@ -146,8 +146,8 @@ struct EncodedSubraph {
         return decoded_outputs;
     }
 
-    static EncodedSubraph make(Subgraph graph) {
-        EncodedSubraph result;
+    static EncodedSubgraph make(Subgraph graph) {
+        EncodedSubgraph result;
         result.input_mask = graph.gen_input_mask();
         result.output_mask = graph.gen_output_mask();
         graph.inputs = result.encode_inputs(graph.inputs);
@@ -156,11 +156,11 @@ struct EncodedSubraph {
         return result;
     }
 
-    static EncodedSubraph make_single(
+    static EncodedSubgraph make_single(
             std::shared_ptr<OpDef> op,
             SmallVector<bool> input_mask,
             SmallVector<bool> output_mask) {
-        EncodedSubraph result;
+        EncodedSubgraph result;
         result.input_mask = input_mask;
         result.output_mask = output_mask;
         Subgraph::var_t last_var = 0;

imperative/src/include/megbrain/imperative/subgraph_detail.h

@@ -24,7 +24,7 @@ apply_on_physical_tensor(const OpDef& def,
 std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(const OpDef& def,
         const SmallVector<LogicalTensorDesc>& inputs);
 
-EncodedSubraph
+EncodedSubgraph
 make_backward_graph(const OpDef& def,
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,
@@ -35,7 +35,7 @@ apply_on_var_node(
         const OpDef& def,
         const VarNodeArray& inputs);
 
-EncodedSubraph make_backward_graph(
+EncodedSubgraph make_backward_graph(
         const OpDef& def, 
         const SmallVector<LogicalTensorDesc>& inputs,
         const SmallVector<bool>& input_requires_grad,

imperative/src/test/backward_graph.cpp

@@ -22,7 +22,7 @@ using namespace cg;
 using namespace imperative;
 
 template <typename T>
-T prepare_backward_graph_inputs(const EncodedSubraph& bg, const T& inputs,
+T prepare_backward_graph_inputs(const EncodedSubgraph& bg, const T& inputs,
                                 const T& outputs, const T& grads) {
     T ret;
     size_t i = 0;

lite/pylite/pylite.md

@@ -143,7 +143,7 @@ LiteNetwork 主要为用户提供模型载入，运行等功能。使用的模
 * CPU 基本模型载入运行的 example
 ```
 def test_network_basic():
-    source_dir = os.getenv("LITE_TEST_RESOUCE")
+    source_dir = os.getenv("LITE_TEST_RESOURCE")
     input_data_path = os.path.join(source_dir, "input_data.npy")
     # read input to input_data
     input_data = np.load(input_data_path)
@@ -176,7 +176,7 @@ def test_network_basic():
 * CUDA 上使用 device 内存作为模型输入，需要在构造 network 候配置 config 和 IO 信息
 ```
 def test_network_device_IO():
-    source_dir = os.getenv("LITE_TEST_RESOUCE")
+    source_dir = os.getenv("LITE_TEST_RESOURCE")
     input_data_path = os.path.join(source_dir, "input_data.npy")
     model_path = os.path.join(source_dir, "shufflenet.mge")
     # read input to input_data

lite/pylite/test/test_global.py

@@ -18,7 +18,7 @@ set_log_level(2)
 
 
 class TestShuffleNet(unittest.TestCase):
-    source_dir = os.getenv("LITE_TEST_RESOUCE")
+    source_dir = os.getenv("LITE_TEST_RESOURCE")
     input_data_path = os.path.join(source_dir, "input_data.npy")
     correct_data_path = os.path.join(source_dir, "output_data.npy")
     correct_data = np.load(correct_data_path).flatten()

lite/pylite/test/test_network.py

@@ -52,7 +52,7 @@ def test_network_io():
 
 
 class TestShuffleNet(unittest.TestCase):
-    source_dir = os.getenv("LITE_TEST_RESOUCE")
+    source_dir = os.getenv("LITE_TEST_RESOURCE")
     input_data_path = os.path.join(source_dir, "input_data.npy")
     correct_data_path = os.path.join(source_dir, "output_data.npy")
     model_path = os.path.join(source_dir, "shufflenet.mge")

lite/pylite/test/test_network_cuda.py

@@ -33,7 +33,7 @@ def require_cuda(ngpu=1):
 
 
 class TestShuffleNetCuda(unittest.TestCase):
-    source_dir = os.getenv("LITE_TEST_RESOUCE")
+    source_dir = os.getenv("LITE_TEST_RESOURCE")
     input_data_path = os.path.join(source_dir, "input_data.npy")
     correct_data_path = os.path.join(source_dir, "output_data.npy")
     model_path = os.path.join(source_dir, "shufflenet.mge")