[XPU] mul unittest (#2676)

test=develop

lite/kernels/xpu/bridges/mul_op.cc

@@ -67,15 +67,27 @@ int MulConverter(void* ctx, OpLite* op, KernelBase* kernel) {
     x_node =
         graph->AddNode(x_name + "/reshape",
                        graph->builder_.CreateReshape(
-                           *x_node, {-1, static_cast<int>(y_matrix_dims[0])}));
+                           *x_node, {-1, static_cast<int>(x_matrix_dims[1])}));
   }
 
   // Y node
-  auto y_const_node = graph->AddNode(y_name, *y, y_matrix_dims);
+  std::shared_ptr<xtcl::xExpr> y_node = nullptr;
+  if (graph->HasNode(y_name)) {
+    y_node = graph->GetNode(y_name);
+  } else {
+    y_node = graph->AddNode(y_name, y_dims);
+  }
+  // Flatten Y node
+  if (y_dims.size() != 2) {
+    y_node =
+        graph->AddNode(y_name + "/reshape",
+                       graph->builder_.CreateReshape(
+                           *y_node, {static_cast<int>(y_matrix_dims[0]), -1}));
+  }
 
   // Reshape the matmul node with the inferred shape as the output node
   auto matmul_node = graph->AddNode(
-      out_name, graph->builder_.CreateMatmul2D(*x_node, *y_const_node, false));
+      out_name, graph->builder_.CreateMatmul2D(*x_node, *y_node, false));
   if (out_dims.size() != 2) {
     graph->AddNode(out_name,
                    graph->builder_.CreateReshape(

lite/tests/kernels/CMakeLists.txt

@@ -30,6 +30,7 @@ if((NOT LITE_WITH_OPENCL AND NOT LITE_WITH_FPGA) AND (LITE_WITH_X86 OR LITE_WITH
     lite_cc_test(test_kernel_layer_norm_compute SRCS layer_norm_compute_test.cc DEPS arena_framework ${xpu_kernels} ${x86_kernels} ${arm_kernels} ${lite_ops} ${host_kernels})
     lite_cc_test(test_kernel_dropout_compute SRCS dropout_compute_test.cc DEPS arena_framework ${xpu_kernels} ${x86_kernels} ${arm_kernels} ${lite_ops} ${host_kernels})
     lite_cc_test(test_kernel_softmax_compute SRCS softmax_compute_test.cc DEPS arena_framework ${xpu_kernels} ${x86_kernels} ${arm_kernels} ${lite_ops} ${host_kernels})
+    lite_cc_test(test_kernel_mul_compute SRCS mul_compute_test.cc DEPS arena_framework ${xpu_kernels} ${x86_kernels} ${arm_kernels} ${lite_ops} ${host_kernels})
 
 if(LITE_BUILD_EXTRA)
     lite_cc_test(test_gru_unit SRCS gru_unit_test.cc DEPS arena_framework ${x86_kernels} ${arm_kernels} ${lite_ops} ${host_kernels})

lite/tests/kernels/mul_compute_test.cc

+// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <gtest/gtest.h>
+#include <cmath>
+#include <string>
+#include "lite/api/paddle_use_kernels.h"
+#include "lite/api/paddle_use_ops.h"
+#include "lite/core/arena/framework.h"
+#include "lite/tests/utils/fill_data.h"
+
+namespace paddle {
+namespace lite {
+
+class MulComputeTester : public arena::TestCase {
+ protected:
+  // common attributes for this op.
+  std::string type_ = "mul";
+  std::string x_ = "x";
+  std::string y_ = "y";
+  std::string out_ = "out";
+  DDim x_dims_{{1, 2}};
+  DDim y_dims_{{2, 1}};
+  int x_num_col_dims_{1};
+  int y_num_col_dims_{1};
+
+ public:
+  MulComputeTester(const Place& place,
+                   const std::string& alias,
+                   DDim x_dims,
+                   DDim y_dims,
+                   int x_num_col_dims,
+                   int y_num_col_dims)
+      : TestCase(place, alias),
+        x_dims_(x_dims),
+        y_dims_(y_dims),
+        x_num_col_dims_(x_num_col_dims),
+        y_num_col_dims_(y_num_col_dims) {}
+
+  void RunBaseline(Scope* scope) override {
+    auto* x = scope->FindTensor(x_);
+    auto* y = scope->FindTensor(y_);
+    auto x_mat_dims = x_dims_.Flatten2D(x_num_col_dims_);
+    auto y_mat_dims = y_dims_.Flatten2D(y_num_col_dims_);
+    CHECK_EQ(x_mat_dims[1], y_mat_dims[0]);
+
+    auto* out = scope->NewTensor(out_);
+    CHECK(out);
+    std::vector<int64_t> out_shape;
+    for (int i = 0; i < x_num_col_dims_; i++) {
+      out_shape.push_back(x_dims_[i]);
+    }
+    for (int i = y_num_col_dims_; i < y_dims_.size(); i++) {
+      out_shape.push_back(y_dims_[i]);
+    }
+    out->Resize(DDim(out_shape));
+
+    auto x_data = x->data<float>();
+    auto y_data = y->data<float>();
+    auto* out_data = out->mutable_data<float>();
+
+    const int M = x_mat_dims[0];
+    const int K = x_mat_dims[1];
+    const int N = y_mat_dims[1];
+    for (int m = 0; m < M; ++m) {
+      for (int n = 0; n < N; ++n) {
+        out_data[m * N + n] = 0;
+        for (int k = 0; k < K; ++k) {
+          out_data[m * N + n] += x_data[m * K + k] * y_data[k * N + n];
+        }
+      }
+    }
+  }
+
+  void PrepareOpDesc(cpp::OpDesc* op_desc) {
+    op_desc->SetType(type_);
+    op_desc->SetInput("X", {x_});
+    op_desc->SetInput("Y", {y_});
+    op_desc->SetOutput("Out", {out_});
+    op_desc->SetAttr("x_num_col_dims", x_num_col_dims_);
+    op_desc->SetAttr("y_num_col_dims", y_num_col_dims_);
+  }
+
+  void PrepareData() override {
+    std::vector<float> x(x_dims_.production());
+    fill_data_rand(x.data(), -1.f, 1.f, x_dims_.production());
+    SetCommonTensor(x_, x_dims_, x.data());
+
+    std::vector<float> y(y_dims_.production());
+    fill_data_rand(y.data(), -1.f, 1.f, y_dims_.production());
+    SetCommonTensor(y_, y_dims_, y.data());
+  }
+};
+
+void TestMul(const std::vector<int64_t>& x_dims,
+             const std::vector<int64_t>& y_dims,
+             int x_num_col_dims,
+             int y_num_col_dims,
+             const Place& place,
+             float abs_error) {
+  std::unique_ptr<arena::TestCase> tester(new MulComputeTester(place,
+                                                               "def",
+                                                               DDim(x_dims),
+                                                               DDim(y_dims),
+                                                               x_num_col_dims,
+                                                               y_num_col_dims));
+  arena::Arena arena(std::move(tester), place, abs_error);
+  arena.TestPrecision();
+}
+
+TEST(Mul, precision) {
+  LOG(INFO) << "test mul op";
+  float abs_error = 2e-5;
+  Place place;
+#if defined(LITE_WITH_XPU)
+  place = TARGET(kXPU);
+#else
+  return;
+#endif
+
+  TestMul({4, 5}, {5, 4}, 1, 1, place, abs_error);
+  TestMul({4, 5}, {5, 4, 3, 2}, 1, 1, place, abs_error);
+  TestMul({4, 20}, {5, 4, 3, 2}, 1, 2, place, abs_error);
+  TestMul({4, 60}, {5, 4, 3, 2}, 1, 3, place, abs_error);
+  TestMul({2, 3, 4, 5}, {60, 4}, 1, 1, place, abs_error);
+  TestMul({2, 3, 4, 5}, {20, 4}, 2, 1, place, abs_error);
+  TestMul({2, 3, 4, 5}, {5, 4}, 3, 1, place, abs_error);
+  TestMul({2, 3, 4, 5}, {60, 3, 4, 5}, 1, 1, place, abs_error);
+  TestMul({2, 3, 4, 5}, {4, 5, 6, 2}, 2, 2, place, abs_error);
+  TestMul({2, 3, 4, 5}, {5, 1, 4, 2}, 3, 2, place, abs_error);
+}
+
+}  // namespace lite
+}  // namespace paddle