Fix Caffe2 operator schemas (#15462) (#13229) (#18109)

Summary:
Maratyszcza harouwu yinghai

This is broken since #13065. `c_str()` returns a pointer that isn't permanent.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18109

Differential Revision: D14516622

Pulled By: ezyang

fbshipit-source-id: 7113d92eac4f61479c4c7b323cf78cc8aa00b17e

diff --git a/caffe2/operators/quantized/int8_average_pool_op.cc b/caffe2/operators/quantized/int8_average_pool_op.cc
index 70df83f..89d9d7b 100644 (file)
--- a/caffe2/operators/quantized/int8_average_pool_op.cc
+++ b/caffe2/operators/quantized/int8_average_pool_op.cc
@@ -20,19 +20,11 @@ data into the output blob Y for further processing.
 std::function<void(OpSchema&)> AveragePoolDocGenerator(
     const char* dim,
     bool relu_fused = false) {
-  auto suffix = relu_fused ? " Output will go through rectified linear "
-                             "function, where y = max(0, x)."
-                           : "";
   return [=](OpSchema& schema) {
     string doc = "AveragePool{dim} {pool_doc}";
     c10::ReplaceAll(doc, "{dim}", dim);
     c10::ReplaceAll(doc, "{pool_doc}", kAveragePoolDoc_int8);
     schema.SetDoc(doc);
-    string output_doc =
-        "Output data tensor from average pooling across the input "
-        "tensor. Dimensions will vary based on various kernel, stride, and pad "
-        "sizes.{suffix}";
-    c10::ReplaceAll(output_doc, "{suffix}", suffix);
     schema.Input(
         0,
         "X",
@@ -42,7 +34,14 @@ std::function<void(OpSchema&)> AveragePoolDocGenerator(
         "size, C is the number of channels, and H and W are the height and the "
         "width of the data. The corresponding permutation of dimensions is "
         "used in the latter case.");
-    schema.Output(0, "Y", output_doc.c_str());
+    schema.Output(0, "Y", relu_fused ?
+        "Output data tensor from average pooling across the input "
+        "tensor. Dimensions will vary based on various kernel, stride, and pad "
+        "sizes. Output will go through rectified linear "
+        "function, where y = max(0, x)." :
+        "Output data tensor from average pooling across the input "
+        "tensor. Dimensions will vary based on various kernel, stride, and pad "
+        "sizes.");
   };
 }
 

diff --git a/caffe2/operators/quantized/int8_conv_op.cc b/caffe2/operators/quantized/int8_conv_op.cc
index bc02158..68ab374 100644 (file)
--- a/caffe2/operators/quantized/int8_conv_op.cc
+++ b/caffe2/operators/quantized/int8_conv_op.cc
@@ -19,9 +19,6 @@ why they are separate files.
 std::function<void(OpSchema&)> ConvDocGenerator(
     const char* dim,
     bool relu_fused = false) {
-  auto suffix = relu_fused ? " Output will go through rectified linear "
-                             "function, where y = max(0, x)."
-                           : "";
   return [=](OpSchema& schema) {
     string doc = R"DOC(
 The convolution operator consumes an input vector, a {dim}filter blob
@@ -29,11 +26,6 @@ and a bias blob and computes the output. {conv_doc})DOC";
     c10::ReplaceAll(doc, "{dim}", dim);
     c10::ReplaceAll(doc, "{conv_doc}", kConvDoc_int8);
     schema.SetDoc(doc);
-    string output_doc =
-        "Output data blob that contains the result of the "
-        "convolution. The output dimensions are functions of the kernel size, "
-        "stride size, and pad lengths.{suffix}";
-    c10::ReplaceAll(output_doc, "{suffix}", suffix);
     schema.Input(
         0,
         "X",
@@ -53,7 +45,14 @@ and a bias blob and computes the output. {conv_doc})DOC";
         "bias",
         "The 1D bias blob that is added through the "
         "convolution; has size (M).");
-    schema.Output(0, "Y", output_doc.c_str());
+    schema.Output(0, "Y", relu_fused ?
+        "Output data blob that contains the result of the "
+        "convolution. The output dimensions are functions of the kernel size, "
+        "stride size, and pad lengths. Output will go through rectified linear "
+        "function, where y = max(0, x)." :
+        "Output data blob that contains the result of the "
+        "convolution. The output dimensions are functions of the kernel size, "
+        "stride size, and pad lengths.");
   };
 }
 

diff --git a/caffe2/operators/quantized/int8_max_pool_op.cc b/caffe2/operators/quantized/int8_max_pool_op.cc
index 64a1507..d1a58ba 100644 (file)
--- a/caffe2/operators/quantized/int8_max_pool_op.cc
+++ b/caffe2/operators/quantized/int8_max_pool_op.cc
@@ -18,18 +18,10 @@ data into the output blob Y for further processing.
 std::function<void(OpSchema&)> MaxPoolDocGenerator(
     const char* dim,
     bool relu_fused = false) {
-  auto suffix = relu_fused ? " Output will go through rectified linear "
-                             "function, where y = max(0, x)."
-                           : "";
   return [=](OpSchema& schema) {
     string doc = "MaxPool{dim} {pool_doc}";
     c10::ReplaceAll(doc, "{dim}", dim);
     c10::ReplaceAll(doc, "{pool_doc}", kMaxPoolDoc_int8);
-    string output_doc =
-        "Output data tensor from max pooling across the input "
-        "tensor. Dimensions will vary based on various kernel, stride, and pad "
-        "sizes.{suffix}";
-    c10::ReplaceAll(output_doc, "{suffix}", suffix);
     schema.SetDoc(doc);
     schema.Input(
         0,
@@ -40,7 +32,14 @@ std::function<void(OpSchema&)> MaxPoolDocGenerator(
         "size, C is the number of channels, and H and W are the height and the "
         "width of the data. The corresponding permutation of dimensions is "
         "used in the latter case.");
-    schema.Output(0, "Y", output_doc.c_str());
+    schema.Output(0, "Y", relu_fused ?
+        "Output data tensor from max pooling across the input "
+        "tensor. Dimensions will vary based on various kernel, stride, and pad "
+        "sizes. Output will go through rectified linear"
+        "function, where y = max(0, x)." :
+        "Output data tensor from max pooling across the input "
+        "tensor. Dimensions will vary based on various kernel, stride, and pad "
+        "sizes. Output will go through rectified linear");
   };
 }