add pad_sequence (#84)

sherpa-onnx/csrc/pad-sequence-test.cc

@@ -0,0 +1,43 @@
+// sherpa-onnx/csrc/pad-sequence-test.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/csrc/pad-sequence.h"
+
+#include <numeric>
+
+#include "gtest/gtest.h"
+#include "sherpa-onnx/csrc/onnx-utils.h"
+
+namespace sherpa_onnx {
+
+TEST(PadSequence, ThreeTensors) {
+  Ort::AllocatorWithDefaultOptions allocator;
+
+  std::array<int64_t, 2> shape1{3, 5};
+  Ort::Value v1 =
+      Ort::Value::CreateTensor<float>(allocator, shape1.data(), shape1.size());
+  float *p1 = v1.GetTensorMutableData<float>();
+  std::iota(p1, p1 + shape1[0] * shape1[1], 0);
+
+  std::array<int64_t, 2> shape2{4, 5};
+  Ort::Value v2 =
+      Ort::Value::CreateTensor<float>(allocator, shape2.data(), shape2.size());
+  float *p2 = v2.GetTensorMutableData<float>();
+  std::iota(p2, p2 + shape2[0] * shape2[1], 0);
+
+  std::array<int64_t, 2> shape3{2, 5};
+  Ort::Value v3 =
+      Ort::Value::CreateTensor<float>(allocator, shape3.data(), shape3.size());
+  float *p3 = v3.GetTensorMutableData<float>();
+  std::iota(p3, p3 + shape3[0] * shape3[1], 0);
+
+  auto ans = PadSequence(allocator, {&v1, &v2, &v3}, -1);
+
+  Print2D(&v1);
+  Print2D(&v2);
+  Print2D(&v3);
+  Print3D(&ans);
+}
+
+}  // namespace sherpa_onnx