Add cumprod function

fastdeploy/function/cumprod.cc

@@ -0,0 +1,78 @@
+// Copyright (c) 2022 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 "fastdeploy/function/cumprod.h"
+
+namespace fastdeploy {
+namespace function {
+
+void GetCumprodDimInfo(const std::vector<int64_t>& dim, int cumprod_dim,
+                       size_t* outer_dim, size_t* mid_dim, size_t* inner_dim) {
+  int dim_size = dim.size();
+  FDASSERT(cumprod_dim >= -dim_size,
+           "The input dim of CumprodOp should be larger than the opposite "
+           "rank of input x which is %d. But received dim = %d",
+           -dim_size, cumprod_dim);
+  FDASSERT(cumprod_dim < dim_size,
+           "The input dim of CumprodOp should be smaller than the "
+           "rank of input x which is %d. But received dim = %d",
+           dim_size, cumprod_dim);
+  if (cumprod_dim < 0)
+    cumprod_dim += dim_size;
+
+  *outer_dim = 1;
+  for (int i = 0; i < cumprod_dim; ++i) {
+    *outer_dim *= dim[i];
+  }
+  *mid_dim = dim[cumprod_dim];
+  *inner_dim = 1;
+  for (int i = cumprod_dim + 1; i < dim_size; ++i) {
+    *inner_dim *= dim[i];
+  }
+}
+
+template <typename T>
+void CumprodKernel(const FDTensor& x, FDTensor* out, int axis) {
+  auto* x_data = reinterpret_cast<const T*>(x.Data());
+  auto shape = x.Shape();
+
+  size_t outer_dim = 1;
+  size_t mid_dim = 1;
+  size_t inner_dim = 1;
+  GetCumprodDimInfo(shape, axis, &outer_dim, &mid_dim, &inner_dim);
+
+  out->Allocate(x.Shape(), x.Dtype());
+  auto* out_data = reinterpret_cast<T*>(out->Data());
+
+  for (size_t i = 0; i < outer_dim; i++) {
+    for (size_t j = 0; j < mid_dim; j++) {
+      for (size_t k = 0; k < inner_dim; k++) {
+        size_t pos = i * mid_dim * inner_dim + j * inner_dim + k;
+        if (j == 0) {
+          out_data[pos] = x_data[pos];
+        } else {
+          out_data[pos] = out_data[pos - inner_dim] * x_data[pos];
+        }
+      }
+    }
+  }
+}
+
+void Cumprod(const FDTensor& x, FDTensor* out, int axis) {
+  FD_VISIT_INT_FLOAT_TYPES(x.dtype, "CumprodKernel",
+                           ([&] { CumprodKernel<data_t>(x, out, axis); }));
+}
+
+}  // namespace function
+}  // namespace fastdeploy

fastdeploy/function/cumprod.h

@@ -0,0 +1,31 @@
+// Copyright (c) 2022 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.
+
+#pragma once
+
+#include "fastdeploy/core/fd_tensor.h"
+
+namespace fastdeploy {
+namespace function {
+
+/** Excute the concatenate operation for input FDTensor along given axis.
+    @param x The input tensor.
+    @param out The output tensor which stores the result.
+    @param axisi Axis which will be concatenated.
+*/
+
+FASTDEPLOY_DECL void Cumprod(const FDTensor& x, FDTensor* out, int axis = 0);
+
+}  // namespace function
+}  // namespace fastdeploy

tests/function/test_cumprod.cc

@@ -0,0 +1,73 @@
+// Copyright (c) 2022 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 "fastdeploy/core/fd_tensor.h"
+#include "fastdeploy/function/cumprod.h"
+#include "glog/logging.h"
+#include "gtest_utils.h"
+#include "gtest/gtest.h"
+#include <array>
+#include <vector>
+
+namespace fastdeploy {
+namespace function {
+
+std::vector<float> CreateTestData() {
+  // Shape: [2, 3, 4]
+  std::vector<float> x_data = {
+      0.8428625,  0.6461913, 0.13740455, 0.11430702, 0.659926,  0.535816,
+      0.7429162,  0.8456049, 0.21228176, 0.29970083, 0.8621713, 0.40894133,
+      0.12684688, 0.1566195, 0.42884097, 0.8476526,  0.2458633, 0.669046,
+      0.87888306, 0.6762589, 0.666453,   0.32523027, 0.4139388, 0.8341406};
+  return x_data;
+}
+
+TEST(fastdeploy, cumprod) {
+  CheckShape check_shape;
+  CheckData check_data;
+  FDTensor x, y;
+  auto test_data = CreateTestData();
+  x.SetExternalData({2, 3, 4}, FDDataType::FP32, test_data.data());
+
+  std::vector<float> result = {0.842862, 0.646191, 0.137405, 0.114307, 0.659926,
+                               0.535816, 0.742916, 0.845605, 0.212282, 0.299701,
+                               0.862171, 0.408941, 0.106914, 0.101206, 0.058925,
+                               0.096893, 0.162252, 0.358486, 0.652937, 0.571848,
+                               0.141476, 0.097472, 0.356886, 0.341115};
+  Cumprod(x, &y, 0);
+  check_shape(y.shape, {2, 3, 4});
+  check_data(reinterpret_cast<const float*>(y.Data()), result.data(),
+             result.size());
+
+  result = {0.842862, 0.646191, 0.137405, 0.114307, 0.556227, 0.34624,
+            0.10208,  0.096659, 0.118077, 0.103768, 0.088011, 0.039528,
+            0.126847, 0.15662,  0.428841, 0.847653, 0.031187, 0.104786,
+            0.376901, 0.573233, 0.020785, 0.034079, 0.156014, 0.478157};
+  Cumprod(x, &y, 1);
+  check_shape(y.shape, {2, 3, 4});
+  check_data(reinterpret_cast<const float*>(y.Data()), result.data(),
+             result.size());
+
+  result = {0.842862, 0.54465,  0.074837, 0.008554, 0.659926, 0.353599,
+            0.262694, 0.222136, 0.212282, 0.063621, 0.054852, 0.022431,
+            0.126847, 0.019867, 0.00852,  0.007222, 0.245863, 0.164494,
+            0.144571, 0.097767, 0.666453, 0.216751, 0.089722, 0.07484};
+  Cumprod(x, &y, 2);
+  check_shape(y.shape, {2, 3, 4});
+  check_data(reinterpret_cast<const float*>(y.Data()), result.data(),
+             result.size());
+}
+
+}  // namespace function
+}  // namespace fastdeploy