commit 674778d3a430450c5b3bb1831a1fdcd8ff2c8fff
author Frank Barchard <fbarchard@google.com> Sat Aug 08 10:17:25 2020 -0700
committer XNNPACK Team <xnnpack-github-robot@google.com> Sat Aug 08 10:17:56 2020 -0700
tree 2fbc66f92ecaf6b007d6a2fa5cd0b2a98d03a9de
parent 75215d82c6853e55e5d1d584741f09f837faa7d7

Add binary op microkernels with RELU activation

PiperOrigin-RevId: 325607697

test/vbinaryc-microkernel-tester.h

diff --git a/test/vbinaryc-microkernel-tester.h b/test/vbinaryc-microkernel-tester.h
index 0f9efa8..ac2729a 100644
--- a/test/vbinaryc-microkernel-tester.h
+++ b/test/vbinaryc-microkernel-tester.h
@@ -387,6 +387,79 @@
     }
   }
 
+  void Test(xnn_f32_vbinary_relu_ukernel_function vbinaryc_relu, OpType op_type, Variant variant = Variant::Native) const {
+    std::random_device random_device;
+    auto rng = std::mt19937(random_device());
+    auto f32rng = std::bind(std::uniform_real_distribution<float>(-1.0f, 1.0f), rng);
+
+    std::vector<float> a(batch_size() + XNN_EXTRA_BYTES / sizeof(float));
+    const float b = f32rng();
+    std::vector<float> y(batch_size() + (inplace() ? XNN_EXTRA_BYTES / sizeof(float) : 0));
+    std::vector<float> y_ref(batch_size());
+    for (size_t iteration = 0; iteration < iterations(); iteration++) {
+      std::generate(a.begin(), a.end(), std::ref(f32rng));
+      if (inplace()) {
+        std::generate(y.begin(), y.end(), std::ref(f32rng));
+      } else {
+        std::fill(y.begin(), y.end(), nanf(""));
+      }
+      const float* a_data = inplace() ? y.data() : a.data();
+
+      // Compute reference results.
+      for (size_t i = 0; i < batch_size(); i++) {
+        switch (op_type) {
+          case OpType::AddC:
+            y_ref[i] = a_data[i] + b;
+            break;
+          case OpType::DivC:
+            y_ref[i] = a_data[i] / b;
+            break;
+          case OpType::RDivC:
+            y_ref[i] = b / a_data[i];
+            break;
+          case OpType::MaxC:
+            y_ref[i] = std::max<float>(a_data[i], b);
+            break;
+          case OpType::MinC:
+            y_ref[i] = std::min<float>(a_data[i], b);
+            break;
+          case OpType::MulC:
+            y_ref[i] = a_data[i] * b;
+            break;
+          case OpType::SqrDiffC:
+          {
+            const float diff = a_data[i] - b;
+            y_ref[i] = diff * diff;
+            break;
+          }
+          case OpType::SubC:
+            y_ref[i] = a_data[i] - b;
+            break;
+          case OpType::RSubC:
+            y_ref[i] = b - a_data[i];
+            break;
+        }
+      }
+      for (size_t i = 0; i < batch_size(); i++) {
+        y_ref[i] = std::max(y_ref[i], 0.0f);
+      }
+
+      // Prepare parameters.
+      xnn_f32_relu_params params = { };
+
+      // Call optimized micro-kernel.
+      vbinaryc_relu(batch_size() * sizeof(float), a_data, &b, y.data(), &params);
+
+      // Verify results.
+      for (size_t i = 0; i < batch_size(); i++) {
+        ASSERT_GE(y[i], 0.0f)
+          << "at " << i << " / " << batch_size();
+        ASSERT_NEAR(y[i], y_ref[i], std::abs(y_ref[i]) * 1.0e-6f)
+          << "at " << i << " / " << batch_size();
+      }
+    }
+  }
+
  private:
   size_t batch_size_{1};
   bool inplace_{false};