Remove train pad function

Samsung · Jan 24, 2024 · b04c37a · b04c37a
1 parent e8985be
commit b04c37a
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Showing 2 changed files with 8 additions and 21 deletions.
diff --git a/compute/cker/include/cker/train/operation/Pad.h b/compute/cker/include/cker/train/operation/Pad.h
@@ -36,19 +36,9 @@ namespace train
  *             ->    [C,2,3,C]
  *             ->    [C,C,C,C]
  */
-template <typename T>
-inline void Pad(const int32_t *padding_data, int32_t pad_rank, const Shape &input_shape,
-                const T *input_data, const Shape &output_shape, T *output_data,
-                const T *constant_value_data)
-{
-  // Use nnfw::cker::Pad directly
-  nnfw::cker::Pad<T>(padding_data, pad_rank, input_shape, input_data, output_shape, output_data,
-                     constant_value_data);
-}
-
 /*
- * input_data(backward_output_data) will be transformed by backward of PAD operation with padding
- * options to output_data(backward_input_data)
+ * input_data(backward_output_data) will be transformed by backward of PAD operation (Depad) with
+ * padding options to output_data(backward_input_data)
  *
  * input_data(backward_output_data)  ->  output_data(backward_input_data)
  *   [C,C,C,C]                       ->    [0,1]
@@ -119,10 +109,9 @@ inline void Depad(const int32_t *padding_data, int32_t pad_rank, const Shape &in
       {
         for (auto h = 0; h < out_height; ++h)
         {
-          // TODO: Remove unnecessary literal value 0
           const auto in_offset =
-            (d + padding_depth) * in_plain_size + (h + padding_top) * in_width + (0 + padding_left);
-          const auto out_offset = (d * out_plain_size) + (h * out_width) + (0);
+            (d + padding_depth) * in_plain_size + (h + padding_top) * in_width + (padding_left);
+          const auto out_offset = (d * out_plain_size) + (h * out_width);
           // copy a row of input data to output data
           std::memcpy(output_data + out_offset, input_data + in_offset, out_width * sizeof(T));
         }
@@ -152,12 +141,10 @@ inline void Depad(const int32_t *padding_data, int32_t pad_rank, const Shape &in
         {
           for (auto h = 0; h < out_height; ++h)
           {
-            // TODO: Remove unnecessary literal value 0
             const auto in_offset = (c + padding_cube) * in_cube_size +
                                    (d + padding_depth) * in_plain_size +
-                                   (h + padding_top) * in_width + (0 + padding_left);
-            const auto out_offset =
-              (c * out_cube_size) + (d * out_plain_size) + (h * out_width) + (0);
+                                   (h + padding_top) * in_width + (padding_left);
+            const auto out_offset = (c * out_cube_size) + (d * out_plain_size) + (h * out_width);
             // copy a row of input data to output data
             std::memcpy(output_data + out_offset, input_data + in_offset, out_width * sizeof(T));
           }

diff --git a/compute/cker/src/train/Pad.test.cc b/compute/cker/src/train/Pad.test.cc
@@ -50,8 +50,8 @@ template <typename T> class PadOpVerifier
     assert(expected_output.size() == _out_shape.FlatSize());
 
     std::vector<T> cacluated_output(_out_shape.FlatSize());
-    nnfw::cker::train::Pad(_op_params.data, _op_params.rank, _in_shape, input.data(), _out_shape,
-                           cacluated_output.data(), &_constant_value);
+    nnfw::cker::Pad(_op_params.data, _op_params.rank, _in_shape, input.data(), _out_shape,
+                    cacluated_output.data(), &_constant_value);
 
     if (expect_eq)
       EXPECT_EQ(expected_output, cacluated_output);