fix ConvTranspose spec (onnx#1566)

jcwchen · Nov 1, 2018 · 47f3ba4 · 47f3ba4
1 parent f34186b
commit 47f3ba4
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Showing 3 changed files with 3 additions and 3 deletions.
diff --git a/docs/Changelog.md b/docs/Changelog.md
@@ -787,7 +787,7 @@ This version of the operator has been available since version 1 of the default O
 <dt><tt>W</tt> : T</dt>
 <dd>The weight tensor that will be used in the convolutions; has size (C x M/group x kH x kW), where C is the number of channels, and kH and kW are the height and width of the kernel, and M is the number of feature maps. For more than 2 dimensions, the weight shape will be (C x M/group x k1 x k2 x ... x kn), where (k1 x k2 x ... x kn) is the dimension of the kernel. The number of channels in the output should be equal to W.shape[1] * group (assuming zero based indices of the shape array)</dd>
 <dt><tt>B</tt> (optional) : T</dt>
-<dd>Optional 1D bias to be added to the convolution, has size of C.</dd>
+<dd>Optional 1D bias to be added to the convolution, has size of M.</dd>
 </dl>
 
 #### Outputs

diff --git a/docs/Operators.md b/docs/Operators.md
@@ -2233,7 +2233,7 @@ This version of the operator has been available since version 1 of the default O
 <dt><tt>W</tt> : T</dt>
 <dd>The weight tensor that will be used in the convolutions; has size (C x M/group x kH x kW), where C is the number of channels, and kH and kW are the height and width of the kernel, and M is the number of feature maps. For more than 2 dimensions, the weight shape will be (C x M/group x k1 x k2 x ... x kn), where (k1 x k2 x ... x kn) is the dimension of the kernel. The number of channels in the output should be equal to W.shape[1] * group (assuming zero based indices of the shape array)</dd>
 <dt><tt>B</tt> (optional) : T</dt>
-<dd>Optional 1D bias to be added to the convolution, has size of C.</dd>
+<dd>Optional 1D bias to be added to the convolution, has size of M.</dd>
 </dl>
 
 #### Outputs

diff --git a/onnx/defs/nn/defs.cc b/onnx/defs/nn/defs.cc
@@ -879,7 +879,7 @@ output_shape can also be explicitly specified in which case pads values are auto
     schema.Input(
         2,
         "B",
-        "Optional 1D bias to be added to the convolution, has size of C.",
+        "Optional 1D bias to be added to the convolution, has size of M.",
         "T",
         OpSchema::Optional);
     schema.Output(