apaam/mlpack
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Fixed Missing Parenthesis error

Browse Source
This commit is contained in:
kartikdutt18
2020-01-18 08:38:34 +05:30
parent 32896894c5
commit 542fa9b526
3 changed files with 41 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files
COPYRIGHT.txt
+1
View File
@@ -124,6 +124,7 @@ Copyright:
Copyright 2019, Ziyang Jiang <zij004@alumni.stanford.edu>
Copyright 2019, Rohit Kartik <rohit.audrey@gmail.com>
Copyright 2019, Aditya Viki <adityaviki01@gmail.com>
Copyright 2019, Kartik Dutt <kartikdutt@live.in>
License: BSD-3-clause
All rights reserved.
src/mlpack/methods/ann/layer/transposed_convolution_impl.hpp
+6 -7
View File
@@ -114,7 +114,6 @@ TransposedConvolution<
aH + kernelHeight - 2 * padHeight)
{
Log::Fatal << "The output width / output height is not possible given "
<< outputWidth << " " << padWidth << " " << aW
<< "the other parameters of the layer." << std::endl;
}
}
@@ -449,12 +448,12 @@ void TransposedConvolution<
* K=Kernel Size
* P=Padding
*/
size_t totalPadWidth = ((strideWidth - 1) * inputWidth + kernelWidth -
strideWidth);
size_t totalPadHeight = ((strideHeight - 1) * inputHeight + kernelHeight -
strideHeight);
padWidth = totalPadWidth / 2 + totalPadWidth & 1;
padHeight = totalPadHeight / 2 + totalPadHeight & 1;
size_t totalPadWidth = (strideWidth - 1) * inputWidth + kernelWidth - \
strideWidth;
size_t totalPadHeight = (strideHeight - 1) * inputHeight + kernelHeight - \
strideHeight;
padWidth = totalPadWidth / 2 + (totalPadWidth & 1);
padHeight = totalPadHeight / 2 + (totalPadHeight & 1);
// If Padding is negative throw a fatal error.
if (padWidth < 0 || padHeight < 0)
{
src/mlpack/tests/ann_layer_test.cpp
+34
View File
@@ -2972,5 +2972,39 @@ BOOST_AUTO_TEST_CASE(TransposedConvolutionLayerPaddingTest)
BOOST_REQUIRE_EQUAL(arma::accu(output), 0);
BOOST_REQUIRE_EQUAL(output.n_rows, input.n_rows);
BOOST_REQUIRE_EQUAL(output.n_cols, input.n_cols);
TransposedConvolution<> module4(1, 1, 4, 4, 1, 1, 1, 1, 5, 5, 5, 5, "SAME");
// Test the forward function.
input = arma::linspace<arma::colvec>(0, 24, 25);
module4.Parameters() = arma::mat(16 + 1, 1, arma::fill::zeros);
module4.Reset();
module4.Forward(std::move(input), std::move(output));
// Value calculated using torch.nn.functional.conv_transpose2d()
BOOST_REQUIRE_EQUAL(arma::accu(output), 0);
BOOST_REQUIRE_EQUAL(output.n_rows, input.n_rows);
BOOST_REQUIRE_EQUAL(output.n_cols, input.n_cols);
// Output shape should equal input.
TransposedConvolution<> module5(1, 1, 3, 3, 1, 1, 2, 2, 5, 5, 5, 5, "SAME");
// Test the forward function.
input = arma::linspace<arma::colvec>(0, 24, 25);
module5.Parameters() = arma::mat(9 + 1, 1, arma::fill::zeros);
module5.Reset();
module5.Forward(std::move(input), std::move(output));
BOOST_REQUIRE_EQUAL(arma::accu(output), 0);
BOOST_REQUIRE_EQUAL(output.n_rows, input.n_rows);
BOOST_REQUIRE_EQUAL(output.n_cols, input.n_cols);
TransposedConvolution<> module6(1, 1, 3, 3, 2, 2, 0, 0, 2, 2, 2, 2, "SAME");
// Test the forward function.
input = arma::linspace<arma::colvec>(0, 3, 4);
module6.Parameters() = arma::mat(25 + 1, 1, arma::fill::zeros);
module6.Reset();
module6.Forward(std::move(input), std::move(output));
// Value calculated using torch.nn.functional.conv_transpose2d()
BOOST_REQUIRE_EQUAL(arma::accu(output), 0);
BOOST_REQUIRE_EQUAL(output.n_rows, input.n_rows);
BOOST_REQUIRE_EQUAL(output.n_cols, input.n_cols);
}
BOOST_AUTO_TEST_SUITE_END();