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Zhijxu/fix conv1d replacement (#19758)
remove the constraint - "group number should be less than 3"; add more condition to make sure the conv1d replacement only happens on conv1d instead of conv2d/conv3d; add more tests;
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zhijiang
GitHub
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2a5c9b86eb
2 changed files with 99 additions and 34 deletions
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@ -42,30 +42,45 @@
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*/
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namespace onnxruntime {
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bool NodeCanBeReplacedByMatmul(const Node& node) {
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// If node type is Conv, and attr "dilations" is 1, "kernel_shape" is 1, "stride" is 1, group is 1 or 2,
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// then it can be replaced by MatMul
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// Kernel_shape is 1 means it is conv1d
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/*
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If node type is Conv, and satisfy the following conditions then it can be replaced by MatMul:
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- not bias as input which means only has 2 inputs: input and weight
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- "dilations" should be [1]
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size 1 means conv1d
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- "strides" should be [1]
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- "pads" should be [0,0]
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- "autopad" should be "NOTSET"
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- "kernel_shape" should be [1]
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*/
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if (!graph_utils::IsSupportedOptypeVersionAndDomain(node, "Conv", {1, 11})) {
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return false;
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}
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const auto* dilations = graph_utils::GetNodeAttribute(node, "dilations");
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const auto* kernel_shape = graph_utils::GetNodeAttribute(node, "kernel_shape");
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const auto* stride = graph_utils::GetNodeAttribute(node, "strides");
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const auto* group = graph_utils::GetNodeAttribute(node, "group");
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if (dilations == nullptr || kernel_shape == nullptr || stride == nullptr || group == nullptr) {
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return false;
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}
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if ((dilations->ints_size() && dilations->ints(0) != 1) ||
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(kernel_shape->ints_size() && kernel_shape->ints(0) != 1) ||
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(stride->ints_size() && stride->ints(0) != 1) ||
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group->i() >= 3) {
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// TODO: bias input can also be supported if needed
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if (node.InputDefs().size() != 2) {
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return false;
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}
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return true;
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const auto* dilations = graph_utils::GetNodeAttribute(node, "dilations");
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const auto* strides = graph_utils::GetNodeAttribute(node, "strides");
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const auto* pads = graph_utils::GetNodeAttribute(node, "pads");
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const auto* autopad = graph_utils::GetNodeAttribute(node, "auto_pad");
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const auto* kernel_shape = graph_utils::GetNodeAttribute(node, "kernel_shape");
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if (dilations == nullptr || strides == nullptr || pads == nullptr || autopad == nullptr || kernel_shape == nullptr) {
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return false;
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}
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if ((dilations->ints_size() == 1 && dilations->ints(0) == 1) &&
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(strides->ints_size() == 1 && strides->ints(0) == 1) &&
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(autopad->s() == "NOTSET") &&
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(pads->ints_size() == 2 && pads->ints(0) == 0 && pads->ints(1) == 0) &&
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(kernel_shape->ints_size() == 1 && kernel_shape->ints(0) == 1)) {
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return true;
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}
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return false;
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}
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void Conv1dToMatmul(Graph& graph, Node& conv) {
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void Conv1dToMatmul(Graph& graph, Node& conv, const std::string transformer_name) {
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// Shape of conv1d input: [batch_size, in_channels, in_length]
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// Shape of conv1d weight:[output_channels, input_channels/group, kernel_shape], kernel_shape is 1
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// We need to split the input into "group", and squeeze&split the weight, and then do MatMul
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@ -83,7 +98,7 @@ void Conv1dToMatmul(Graph& graph, Node& conv) {
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conv1d_input_splitted_outputs.push_back(&graph.GetOrCreateNodeArg(
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graph.GenerateNodeArgName("input_split_output"), nullptr));
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}
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auto& input_split = graph.AddNode(graph.GenerateNodeName("Split"), "Split", node_description, {conv1d_input},
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auto& input_split = graph.AddNode(graph.GenerateNodeName(transformer_name + "Split"), "Split", node_description, {conv1d_input},
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{conv1d_input_splitted_outputs});
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input_split.SetExecutionProviderType(execution_provider_type);
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input_split.AddAttribute("axis", int64_t(1));
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@ -93,23 +108,25 @@ void Conv1dToMatmul(Graph& graph, Node& conv) {
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}
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// 2. Squeeze conv weight
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auto conv1d_weight = conv.MutableInputDefs()[1];
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// auto con1d_bias = xx;
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auto weight_squeeze_output = &graph.GetOrCreateNodeArg(graph.GenerateNodeArgName("weight_squeeze_output"), nullptr);
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auto& weight_squeeze = graph.AddNode(graph.GenerateNodeName("WeightSqueeze"), "Squeeze",
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auto& weight_squeeze = graph.AddNode(graph.GenerateNodeName(transformer_name + "WeightSqueeze"), "Squeeze",
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node_description, {conv1d_weight}, {weight_squeeze_output});
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int64_t weight_squeeze_axis = 2;
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if (onnx_opset_version > 12) {
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// After onnx version 12, squeeze node has axes as input instead of attribute
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ONNX_NAMESPACE::TensorProto initializer_proto;
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initializer_proto.set_name(graph.GenerateNodeName("ConstAsInitializer"));
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initializer_proto.set_name(graph.GenerateNodeName(transformer_name + "ConstAsInitializer"));
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initializer_proto.add_dims(static_cast<int64_t>(1));
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initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64);
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InlinedVector<int64_t> initializer_proto_value{2};
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InlinedVector<int64_t> initializer_proto_value{weight_squeeze_axis};
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initializer_proto.set_raw_data(initializer_proto_value.data(), initializer_proto_value.size() * sizeof(int64_t));
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auto& axes_input = graph_utils::AddInitializer(graph, initializer_proto);
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// Squeeze node doesn't have opschema here, so we need to set input args count manually
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weight_squeeze.MutableInputArgsCount().resize(2);
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graph_utils::AddNodeInput(weight_squeeze, 1, axes_input);
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} else {
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weight_squeeze.AddAttribute("axes", std::vector<int64_t>{2});
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weight_squeeze.AddAttribute("axes", std::vector<int64_t>{weight_squeeze_axis});
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}
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weight_squeeze.SetExecutionProviderType(execution_provider_type);
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// 3. Split conv weight
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@ -118,7 +135,7 @@ void Conv1dToMatmul(Graph& graph, Node& conv) {
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conv1d_weight_splitted_outputs.push_back(&graph.GetOrCreateNodeArg(
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graph.GenerateNodeArgName("weight_split_output"), nullptr));
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}
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auto& weight_split = graph.AddNode(graph.GenerateNodeName("Split"), "Split", node_description,
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auto& weight_split = graph.AddNode(graph.GenerateNodeName(transformer_name + "Split"), "Split", node_description,
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{weight_squeeze_output}, {conv1d_weight_splitted_outputs});
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weight_split.AddAttribute("axis", int64_t(0));
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weight_split.SetExecutionProviderType(execution_provider_type);
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@ -130,13 +147,13 @@ void Conv1dToMatmul(Graph& graph, Node& conv) {
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for (int i = 0; i < group_num; i++) {
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auto matmul_output = &graph.GetOrCreateNodeArg(graph.GenerateNodeArgName("matmul_output"), nullptr);
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matmul_outputs.push_back(matmul_output);
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auto& matmul = graph.AddNode(graph.GenerateNodeName("Matmul"), "MatMul", node_description,
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auto& matmul = graph.AddNode(graph.GenerateNodeName(transformer_name + "Matmul"), "MatMul", node_description,
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{conv1d_weight_splitted_outputs[i], conv1d_input_splitted_outputs[i]},
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{matmul_output});
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matmul.SetExecutionProviderType(execution_provider_type);
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}
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// 5. Concat matmul outputs
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auto& concat_node = graph.AddNode(graph.GenerateNodeName("Concat"), "Concat", node_description,
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auto& concat_node = graph.AddNode(graph.GenerateNodeName(transformer_name + "Concat"), "Concat", node_description,
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matmul_outputs, {});
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concat_node.SetExecutionProviderType(execution_provider_type);
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concat_node.AddAttribute("axis", int64_t(1));
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@ -155,7 +172,7 @@ Status Conv1dReplacement::ApplyImpl(Graph& graph, bool& modified, int graph_leve
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ORT_RETURN_IF_ERROR(Recurse(node, modified, graph_level, logger));
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if (NodeCanBeReplacedByMatmul(node)) {
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LOGS(logger, VERBOSE) << "lora conv1d replacement, node name: " + node.Name();
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Conv1dToMatmul(graph, node);
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Conv1dToMatmul(graph, node, Name());
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modified = true;
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}
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}
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@ -1200,7 +1200,7 @@ TEST_P(QDQFusionTestsParameterized, CheckModelComposition) {
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ASSERT_EQ(op_to_count_post_fusion["com.microsoft.FakeQuant"], 1);
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}
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TEST_F(GraphTransformationTests, Conv1dReplacement) {
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TEST_F(GraphTransformationTests, Conv1dReplacement_TakeEffect) {
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auto pre_graph_checker = [&](Graph& graph) {
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auto op_count_map = CountOpsInGraph(graph);
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TEST_RETURN_IF_NOT(op_count_map["Conv"] == 1);
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@ -1208,7 +1208,7 @@ TEST_F(GraphTransformationTests, Conv1dReplacement) {
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};
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for (auto opset : {11, 12, 13, 14, 15, 16, 17, 18}) {
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for (auto group : {1, 2}) {
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for (auto group : {1, 2, 4}) {
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auto build_test_case = [&](ModelTestBuilder& builder) {
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auto [batch_size, in_channel, in_length] = std::make_tuple(8, 16, 128);
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auto out_channel = 64;
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@ -1222,6 +1222,8 @@ TEST_F(GraphTransformationTests, Conv1dReplacement) {
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conv_node.AddAttribute("kernel_shape", std::vector<int64_t>{1});
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conv_node.AddAttribute("strides", std::vector<int64_t>{1});
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conv_node.AddAttribute("group", static_cast<int64_t>(group));
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conv_node.AddAttribute("pads", std::vector<int64_t>{0, 0});
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conv_node.AddAttribute("auto_pad", "NOTSET");
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};
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auto post_graph_checker = [&](Graph& graph) {
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@ -1243,28 +1245,31 @@ TEST_F(GraphTransformationTests, Conv1dReplacement) {
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}
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}
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TEST_F(GraphTransformationTests, Conv1dReplacement_NoTakeEffect) {
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// node has bias input so conv not replaced
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TEST_F(GraphTransformationTests, Conv1dReplacement_NoTakeEffect1) {
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auto pre_graph_checker = [&](Graph& graph) {
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auto op_count_map = CountOpsInGraph(graph);
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TEST_RETURN_IF_NOT(op_count_map["Conv"] == 1);
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return Status::OK();
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};
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// "group" is 3 so conv not replaced
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for (auto opset : {11, 12, 13, 14, 15, 16, 17, 18}) {
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auto build_test_case = [&](ModelTestBuilder& builder) {
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auto [batch_size, in_channel, in_length] = std::make_tuple(8, 16, 128);
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auto out_channel = 64;
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auto* data_arg = builder.MakeInput<float>({{batch_size, in_channel, in_length}});
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auto* weight_arg = builder.MakeInitializer<float>({out_channel, in_channel / 3, 1}, {-1.0f, 1.0f});
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auto* weight_arg = builder.MakeInitializer<float>({out_channel, in_channel, 1}, {-1.0f, 1.0f});
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auto* bias_arg = builder.MakeInitializer<float>({out_channel}, {-1.0f, 1.0f});
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auto* conv_output = builder.MakeOutput();
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auto& conv_node = builder.AddNode("Conv", {data_arg, weight_arg}, {conv_output});
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auto& conv_node = builder.AddNode("Conv", {data_arg, weight_arg, bias_arg}, {conv_output});
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conv_node.AddAttribute("dilations", std::vector<int64_t>{1});
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conv_node.AddAttribute("kernel_shape", std::vector<int64_t>{1});
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conv_node.AddAttribute("strides", std::vector<int64_t>{1});
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conv_node.AddAttribute("group", static_cast<int64_t>(3));
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conv_node.AddAttribute("group", static_cast<int64_t>(1));
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conv_node.AddAttribute("pads", std::vector<int64_t>{0, 0});
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conv_node.AddAttribute("auto_pad", "NOTSET");
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};
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std::unique_ptr<GraphTransformer> transformer = std::make_unique<Conv1dReplacement>();
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@ -1272,8 +1277,16 @@ TEST_F(GraphTransformationTests, Conv1dReplacement_NoTakeEffect) {
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TransformerLevel::Level1, 1,
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pre_graph_checker, pre_graph_checker));
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}
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}
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// "auto_pad " is not NOTSET so conv not replaced
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TEST_F(GraphTransformationTests, Conv1dReplacement_NoTakeEffect2) {
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auto pre_graph_checker = [&](Graph& graph) {
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auto op_count_map = CountOpsInGraph(graph);
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TEST_RETURN_IF_NOT(op_count_map["Conv"] == 1);
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return Status::OK();
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};
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// "kernel_shape" is not 1 so conv not replaced
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for (auto opset : {11, 12, 13, 14, 15, 16, 17, 18}) {
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auto build_test_case = [&](ModelTestBuilder& builder) {
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auto [batch_size, in_channel, in_length] = std::make_tuple(8, 16, 128);
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@ -1285,9 +1298,44 @@ TEST_F(GraphTransformationTests, Conv1dReplacement_NoTakeEffect) {
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auto& conv_node = builder.AddNode("Conv", {data_arg, weight_arg}, {conv_output});
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conv_node.AddAttribute("dilations", std::vector<int64_t>{1});
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conv_node.AddAttribute("kernel_shape", std::vector<int64_t>{2});
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conv_node.AddAttribute("kernel_shape", std::vector<int64_t>{1});
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conv_node.AddAttribute("strides", std::vector<int64_t>{1});
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conv_node.AddAttribute("group", static_cast<int64_t>(1));
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conv_node.AddAttribute("pads", std::vector<int64_t>{0, 0});
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conv_node.AddAttribute("auto_pad", "VALID");
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};
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std::unique_ptr<GraphTransformer> transformer = std::make_unique<Conv1dReplacement>();
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ASSERT_STATUS_OK(TestGraphTransformer(build_test_case, opset, *logger_, std::move(transformer),
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TransformerLevel::Level1, 1,
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pre_graph_checker, pre_graph_checker));
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}
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}
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// pads is not all zero, so conv not replaced
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TEST_F(GraphTransformationTests, Conv1dReplacement_NoTakeEffect3) {
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auto pre_graph_checker = [&](Graph& graph) {
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auto op_count_map = CountOpsInGraph(graph);
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TEST_RETURN_IF_NOT(op_count_map["Conv"] == 1);
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return Status::OK();
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};
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for (auto opset : {11, 12, 13, 14, 15, 16, 17, 18}) {
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auto build_test_case = [&](ModelTestBuilder& builder) {
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auto [batch_size, in_channel, in_length] = std::make_tuple(8, 16, 128);
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auto out_channel = 64;
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auto* data_arg = builder.MakeInput<float>({{batch_size, in_channel, in_length}});
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auto* weight_arg = builder.MakeInitializer<float>({out_channel, in_channel, 1}, {-1.0f, 1.0f});
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auto* conv_output = builder.MakeOutput();
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auto& conv_node = builder.AddNode("Conv", {data_arg, weight_arg}, {conv_output});
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conv_node.AddAttribute("dilations", std::vector<int64_t>{1});
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conv_node.AddAttribute("kernel_shape", std::vector<int64_t>{1});
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conv_node.AddAttribute("strides", std::vector<int64_t>{1});
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conv_node.AddAttribute("group", static_cast<int64_t>(1));
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conv_node.AddAttribute("pads", std::vector<int64_t>{1, 0});
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conv_node.AddAttribute("auto_pad", "NOTSET");
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};
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std::unique_ptr<GraphTransformer> transformer = std::make_unique<Conv1dReplacement>();
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