diff --git a/paddle/function/ConvOpTest.cpp b/paddle/function/ConvOpTest.cpp index 280aed8a5c8e4eb782b9b494a84dd3194c21266c..59c7238d218a5adc4e19c9f6df627d7e203b965d 100644 --- a/paddle/function/ConvOpTest.cpp +++ b/paddle/function/ConvOpTest.cpp @@ -20,9 +20,9 @@ limitations under the License. */ namespace paddle { enum TestType { - FORWARD_TEST = 0, - BACKWARD_INPUT_TEST = 1, - BACKWARD_FILTER_TEST = 2, + kForwardTest = 0, + kBackwardInputTest = 1, + kBackwardFilterTest = 2, }; template @@ -43,16 +43,16 @@ public: if (padding >= filterSize) break; size_t outputSize = (inputSize - filterSize + 2 * padding + stride) / stride; - LOG(INFO) << " batchSize=" << batchSize - << " inputChannels=" << inputChannels - << " inputHeight=" << inputSize - << " inputWidth=" << inputSize - << " outputChannels=" << outputChannels - << " filterHeight=" << filterSize - << " filterWidth=" << filterSize - << " outputHeight=" << outputSize - << " outputWidth=" << outputSize - << " stride=" << stride << " padding=" << padding; + VLOG(3) << " batchSize=" << batchSize + << " inputChannels=" << inputChannels + << " inputHeight=" << inputSize + << " inputWidth=" << inputSize + << " outputChannels=" << outputChannels + << " filterHeight=" << filterSize + << " filterWidth=" << filterSize + << " outputHeight=" << outputSize + << " outputWidth=" << outputSize + << " stride=" << stride << " padding=" << padding; std::vector paddings = {padding, padding}; std::vector strides = {stride, stride}; @@ -72,17 +72,17 @@ public: TensorShape output{ batchSize, outputChannels, outputSize, outputSize}; - if (type == FORWARD_TEST) { + if (type == kForwardTest) { test.addInputs(BufferArg(VALUE_TYPE_FLOAT, input)); test.addInputs(BufferArg(VALUE_TYPE_FLOAT, filter)); test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, output)); test.run(); - } else if (type == BACKWARD_INPUT_TEST) { + } else if (type == kBackwardInputTest) { test.addInputs(BufferArg(VALUE_TYPE_FLOAT, output)); test.addInputs(BufferArg(VALUE_TYPE_FLOAT, filter)); test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, input), ADD_TO); test.run(); - } else if (type == BACKWARD_FILTER_TEST) { + } else if (type == kBackwardFilterTest) { test.addInputs(BufferArg(VALUE_TYPE_FLOAT, output)); test.addInputs(BufferArg(VALUE_TYPE_FLOAT, input)); test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, filter)); @@ -100,23 +100,23 @@ public: TEST(Forward, GEMM) { ConvolutionTest test( - "NaiveConv-CPU", "GemmConv-CPU", FORWARD_TEST); + "NaiveConv-CPU", "GemmConv-CPU", kForwardTest); } #ifndef PADDLE_ONLY_CPU TEST(Forward, GEMM2) { ConvolutionTest test( - "GemmConv-CPU", "GemmConv-GPU", FORWARD_TEST); + "GemmConv-CPU", "GemmConv-GPU", kForwardTest); } TEST(BackwardInput, GEMM) { ConvolutionTest test( - "GemmConvGradInput-CPU", "GemmConvGradInput-GPU", BACKWARD_INPUT_TEST); + "GemmConvGradInput-CPU", "GemmConvGradInput-GPU", kBackwardInputTest); } TEST(BackwardFilter, GEMM) { ConvolutionTest test( - "GemmConvGradFilter-CPU", "GemmConvGradFilter-GPU", BACKWARD_FILTER_TEST); + "GemmConvGradFilter-CPU", "GemmConvGradFilter-GPU", kBackwardFilterTest); } #endif