Merge pull request #12408 from tensor-tang/refine/im2col

tensor-tang · web-flow · commit 059b27840c80 · 2018-07-30T17:56:56.000+08:00
Refine CPU im2col padding with 1
diff --git a/paddle/fluid/operators/math/im2col.cc b/paddle/fluid/operators/math/im2col.cc
@@ -14,6 +14,7 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/math/im2col.h"
 #include <vector>
+#include "paddle/fluid/operators/math/im2col_cfo_cpu.h"
 
 namespace paddle {
 namespace operators {
@@ -35,61 +36,18 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col->dims().size() == 5);
 
-    int im_channels = im.dims()[0];
-    int im_height = im.dims()[1];
-    int im_width = im.dims()[2];
-    int filter_height = col->dims()[1];
-    int filter_width = col->dims()[2];
-    int output_height = col->dims()[3];
-    int output_width = col->dims()[4];
-
-    int channels_col = im_channels * filter_height * filter_width;
-
-    const T* im_data = im.data<T>();
-    T* col_data = col->data<T>();
-    // TODO(TJ): change me to template
-    // further optimaze:
-    // 1. padding != 1
-    // 2. could also support stride_h != 1
     if (stride[0] == 1 && stride[1] == 1 && dilation[0] == 1 &&
-        dilation[1] == 1 && padding[0] == 0 && padding[1] == 0) {
-      int col_matrix_width = output_width * output_height;
-      size_t copy_size = sizeof(T) * output_width;
-      for (int oh = 0; oh < output_height; ++oh) {
-        const T* im_data_start = im_data + oh * im_width;
-        T* dst_data = col_data + oh * output_width;
-        for (int ic = 0; ic < im_channels; ++ic) {
-          const T* src_data = im_data_start + ic * im_height * im_width;
-          for (int kh = 0; kh < filter_height; ++kh) {
-            for (int kw = 0; kw < filter_width; ++kw) {
-              std::memcpy(dst_data, src_data + kw, copy_size);
-              dst_data = dst_data + col_matrix_width;
-            }
-            src_data = src_data + im_width;
-          }
-        }
-      }
-      return;
-    }
-
-    for (int c = 0; c < channels_col; ++c) {
-      int w_offset = c % filter_width;
-      int h_offset = (c / filter_width) % filter_height;
-      int c_im = c / (filter_width * filter_height);
-      for (int h = 0; h < output_height; ++h) {
-        int im_row_idx = h * stride[0] - padding[0] + h_offset * dilation[0];
-        for (int w = 0; w < output_width; ++w) {
-          int im_col_idx = w * stride[1] - padding[1] + w_offset * dilation[1];
-          int col_idx = (c * output_height + h) * output_width + w;
-          int im_idx = (im_row_idx + c_im * im_height) * im_width + im_col_idx;
-
-          col_data[col_idx] = (im_row_idx < 0 || im_row_idx >= im_height ||
-                               im_col_idx < 0 || im_col_idx >= im_width)
-                                  ? static_cast<T>(0)
-                                  : im_data[im_idx];
-        }
+        dilation[1] == 1) {
+      if (padding[0] == 0 && padding[1] == 0) {
+        im2col_sh1sw1dh1dw1ph0pw0<T>(im, col);
+        return;
+      } else if (padding[0] == 1 && padding[1] == 1) {
+        im2col_sh1sw1dh1dw1ph1pw1<T>(im, col);
+        return;
       }
+      // TODO(TJ): complete padding >=2
     }
+    im2col_common<T>(im, dilation, stride, padding, col);
   }
 };
 
diff --git a/paddle/fluid/operators/math/im2col_cfo_cpu.h b/paddle/fluid/operators/math/im2col_cfo_cpu.h
@@ -0,0 +1,252 @@
+/* Copyright (c) 2016 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 <vector>
+#include "paddle/fluid/framework/tensor.h"
+
+namespace paddle {
+namespace operators {
+namespace math {
+
+/**
+ * The most common im2col algorithm.
+ * Support dilation, stride and padding.
+ */
+template <typename T>
+inline void im2col_common(const framework::Tensor& im,
+                          const std::vector<int>& dilation,
+                          const std::vector<int>& stride,
+                          const std::vector<int>& padding,
+                          framework::Tensor* col) {
+  int im_channels = im.dims()[0];
+  int im_height = im.dims()[1];
+  int im_width = im.dims()[2];
+  int filter_height = col->dims()[1];
+  int filter_width = col->dims()[2];
+  int output_height = col->dims()[3];
+  int output_width = col->dims()[4];
+  int channels_col = im_channels * filter_height * filter_width;
+
+  const T* im_data = im.data<T>();
+  T* col_data = col->data<T>();
+  for (int c = 0; c < channels_col; ++c) {
+    int w_offset = c % filter_width;
+    int h_offset = (c / filter_width) % filter_height;
+    int c_im = c / (filter_width * filter_height);
+    for (int h = 0; h < output_height; ++h) {
+      int im_row_idx = h * stride[0] - padding[0] + h_offset * dilation[0];
+      for (int w = 0; w < output_width; ++w) {
+        int im_col_idx = w * stride[1] - padding[1] + w_offset * dilation[1];
+        int col_idx = (c * output_height + h) * output_width + w;
+        int im_idx = (im_row_idx + c_im * im_height) * im_width + im_col_idx;
+        col_data[col_idx] = (im_row_idx < 0 || im_row_idx >= im_height ||
+                             im_col_idx < 0 || im_col_idx >= im_width)
+                                ? static_cast<T>(0)
+                                : im_data[im_idx];
+      }
+    }
+  }
+}
+
+/**
+ * im2col algorithm with strides == 1, dilations == 1, paddings == 0
+ */
+template <typename T>
+inline void im2col_sh1sw1dh1dw1ph0pw0(const framework::Tensor& im,
+                                      framework::Tensor* col) {
+  int im_channels = im.dims()[0];
+  int im_height = im.dims()[1];
+  int im_width = im.dims()[2];
+  int filter_height = col->dims()[1];
+  int filter_width = col->dims()[2];
+  int output_height = col->dims()[3];
+  int output_width = col->dims()[4];
+
+  const T* im_data = im.data<T>();
+  T* col_data = col->data<T>();
+  int col_matrix_width = output_width * output_height;
+  int im_size = im_height * im_width;
+  size_t copy_size = sizeof(T) * output_width;
+  const T* im_data_oh = im_data;
+  T* dst_data_oh = col_data;
+  for (int oh = 0; oh < output_height; ++oh) {
+    const T* src_data_ic = im_data_oh;
+    T* dst_data = dst_data_oh;
+    for (int ic = 0; ic < im_channels; ++ic) {
+      const T* src_data = src_data_ic;
+      for (int kh = 0; kh < filter_height; ++kh) {
+        for (int kw = 0; kw < filter_width; ++kw) {
+          std::memcpy(dst_data, src_data + kw, copy_size);
+          dst_data = dst_data + col_matrix_width;
+        }
+        src_data = src_data + im_width;
+      }
+      src_data_ic = src_data_ic + im_size;
+    }
+    im_data_oh = im_data_oh + im_width;
+    dst_data_oh = dst_data_oh + output_width;
+  }
+}
+
+/**
+ * im2col algorithm with strides == 1, dilations == 1, paddings == 1
+ * and filter_width == 1 have a special implementation
+ */
+template <typename T>
+inline void im2col_sh1sw1dh1dw1ph1pw1(const framework::Tensor& im,
+                                      framework::Tensor* col) {
+  int im_channels = im.dims()[0];
+  int im_height = im.dims()[1];
+  int im_width = im.dims()[2];
+  int filter_height = col->dims()[1];
+  int filter_width = col->dims()[2];
+  int output_height = col->dims()[3];
+  int output_width = col->dims()[4];
+
+  constexpr int plh = 1;
+  constexpr int prh = 1;
+  constexpr int plw = 1;
+  constexpr int prw = 1;
+
+  const T* im_data = im.data<T>();
+  T* col_data = col->data<T>();
+  int im_size = im_height * im_width;
+  int col_matrix_width = output_width * output_height;
+  int col_block_fh = filter_width * col_matrix_width;  // fw*oh*ow
+  int col_block_ic = filter_height * col_block_fh;     // fh*fw*oh*ow
+
+  // fill height padding
+  {
+    size_t copy_size = sizeof(T) * output_width;
+    T* col_start_l = col_data;
+    T* col_start_r = col_data + (filter_height - 1) * col_block_fh +
+                     col_matrix_width - output_width;
+    for (int ic = 0; ic < im_channels; ++ic) {
+      T* dst_data_l = col_start_l;
+      T* dst_data_r = col_start_r;
+      for (int kw = 0; kw < filter_width; ++kw) {
+        std::memset(dst_data_l, 0, copy_size);
+        std::memset(dst_data_r, 0, copy_size);
+        dst_data_l = dst_data_l + col_matrix_width;
+        dst_data_r = dst_data_r + col_matrix_width;
+      }
+      col_start_l = col_start_l + col_block_ic;
+      col_start_r = col_start_r + col_block_ic;
+    }
+  }
+
+  auto pad = static_cast<T>(0);
+  if (filter_width == 1) {
+    // fill width padding
+    T* dst_data_ic = col_data;
+    for (int ic = 0; ic < im_channels; ++ic) {
+      T* dst_data_kh = dst_data_ic;
+      for (int kh = 0; kh < filter_height; ++kh) {
+        T* dst_data = dst_data_kh;
+        for (int oh = 0; oh < output_height; ++oh) {
+          *dst_data = pad;
+          dst_data = dst_data + output_width - 1;
+          *dst_data = pad;
+          ++dst_data;
+        }
+        dst_data_kh = dst_data_kh + col_block_fh;
+      }
+      dst_data_ic = dst_data_ic + col_block_ic;
+    }
+    // fill core
+    size_t copy_size = sizeof(T) * (output_width - plw - prw);
+    for (int oh = 0; oh < output_height; ++oh) {
+      const T* im_data_start =
+          im_data + (oh - plh > 0 ? oh - plh : 0) * im_width;
+      T* dst_data = col_data + oh * output_width;
+      for (int ic = 0; ic < im_channels; ++ic) {
+        const T* src_data = im_data_start + ic * im_size;
+        for (int kh = 0; kh < filter_height; ++kh) {
+          if ((oh < plh && kh < plh) || (oh > (output_height - prh - 1) &&
+                                         kh > (filter_height - prh - 1))) {
+            dst_data = dst_data + col_matrix_width;
+            continue;
+          }
+          std::memcpy(dst_data + plw, src_data, copy_size);
+          dst_data = dst_data + col_matrix_width;
+          src_data = src_data + im_width;
+        }
+      }
+    }
+    return;
+  }
+
+  // filter_width != 1
+  // fill width padding
+  T* dst_data_ic = col_data;
+  for (int ic = 0; ic < im_channels; ++ic) {
+    T* dst_data_kh = dst_data_ic;
+    for (int kh = 0; kh < filter_height; ++kh) {
+      for (T* dst_data :
+           {dst_data_kh, dst_data_kh + (filter_width - prw) * col_matrix_width +
+                             output_width - 1}) {
+        // TODO(TJ): from plh, saving repeated assignment
+        for (int oh = 0; oh < output_height; ++oh) {
+          *dst_data = pad;
+          dst_data = dst_data + output_width;
+        }
+      }
+      dst_data_kh = dst_data_kh + col_block_fh;
+    }
+    dst_data_ic = dst_data_ic + col_block_ic;
+  }
+
+  // TODO(TJ): use array like: size_t copy_size[kw]={sizeof(T) *
+  // (output_width-1)}
+  // length of copy_size is equal kw.
+  for (int oh = 0; oh < output_height; ++oh) {
+    const T* im_data_start = im_data + (oh - plh > 0 ? oh - plh : 0) * im_width;
+    T* dst_data = col_data + oh * output_width;
+    for (int ic = 0; ic < im_channels; ++ic) {
+      const T* src_data = im_data_start + ic * im_size;
+      for (int kh = 0; kh < filter_height; ++kh) {
+        if ((oh < plh && kh < plh) || (oh > (output_height - prh - 1) &&
+                                       kh > (filter_height - prh - 1))) {
+          dst_data = dst_data + filter_width * col_matrix_width;
+          continue;
+        }
+        // TODO(TJ): reuse plw-kw outside this for
+        // try to unify
+        for (int kw = 0; kw < plw; ++kw) {
+          std::memcpy(dst_data + (plw - kw), src_data,
+                      sizeof(T) * (output_width - (plw - kw)));
+          dst_data = dst_data + col_matrix_width;
+        }
+        for (int kw = plw; kw < filter_width - prw; ++kw) {
+          std::memcpy(dst_data, src_data + (kw - plw),
+                      sizeof(T) * output_width);
+          dst_data = dst_data + col_matrix_width;
+        }
+        int i = 1;
+        for (int kw = filter_width - prw; kw < filter_width; ++kw, ++i) {
+          std::memcpy(dst_data, src_data + (kw - plw),
+                      sizeof(T) * (output_width - i));
+          dst_data = dst_data + col_matrix_width;
+        }
+        src_data = src_data + im_width;
+      }
+    }
+  }
+}
+
+}  // namespace math
+}  // namespace operators
+}  // namespace paddle
diff --git a/paddle/fluid/operators/math/im2col_test.cc b/paddle/fluid/operators/math/im2col_test.cc
