From f2f149861a067b12035bb3c6bdaac255d26992e9 Mon Sep 17 00:00:00 2001 From: wanghailu Date: Mon, 16 Jan 2023 14:08:14 +0800 Subject: [PATCH] code format fix --- src/kernels/bang/element_wise.cc | 12 ++++++------ src/kernels/bang/pooling.cc | 14 +++++++------- src/kernels/bang/split.cc | 8 ++++---- test/kernels/bang/test_bang_pooling.cc | 4 ++-- test/kernels/bang/test_bang_round.cc | 2 +- test/kernels/bang/test_bang_split.cc | 5 ++--- test/kernels/bang/test_bang_square.cc | 2 +- test/kernels/bang/test_bang_squaredDifference.cc | 8 +++++--- 8 files changed, 28 insertions(+), 27 deletions(-) diff --git a/src/kernels/bang/element_wise.cc b/src/kernels/bang/element_wise.cc index 58314ba5..b546073b 100644 --- a/src/kernels/bang/element_wise.cc +++ b/src/kernels/bang/element_wise.cc @@ -553,14 +553,14 @@ class SquaredDifferenceCnnl : public BangKernelWithoutConfig { CNNL_DTYPE_FLOAT, 4, dim_array)); size_t wsSize; - cnnlGetSquaredDifferenceWorkspaceSize(context->cnnlHandle(), aDesc, bDesc, cDesc, - &wsSize); + cnnlGetSquaredDifferenceWorkspaceSize(context->cnnlHandle(), aDesc, + bDesc, cDesc, &wsSize); BangPtr wsData = context->getWorkspace(wsSize); cnnlStatus_t stat = - cnnlSquaredDifference(context->cnnlHandle(), aDesc, aData, bDesc, bData, - cDesc, cData, wsData, wsSize); + cnnlSquaredDifference(context->cnnlHandle(), aDesc, aData, bDesc, + bData, cDesc, cData, wsData, wsSize); if (stat != CNNL_STATUS_SUCCESS) return; @@ -675,8 +675,8 @@ REGISTER_KERNEL(Device::BANG, OpType::FloorDivTrunc, DataType::Float32, FloorDivTruncCnnl, "FloorDivTrunc_cnnl_BANG_Float32"); REGISTER_KERNEL(Device::BANG, OpType::FloorMod, DataType::Float32, FloorModCnnl, "FloorMod_cnnl_BANG_Float32"); -REGISTER_KERNEL(Device::BANG, OpType::SquaredDifference, DataType::Float32, SquaredDifferenceCnnl, - "SquaredDifference_cnnl_BANG_Float32"); +REGISTER_KERNEL(Device::BANG, OpType::SquaredDifference, DataType::Float32, + SquaredDifferenceCnnl, "SquaredDifference_cnnl_BANG_Float32"); // REGISTER_KERNEL(Device::BANG, OpType::FloorModTrunc, DataType::Float32, // FloorModTruncCnnl, // "FloorModTrunc_cnnl_BANG_Float32"); diff --git a/src/kernels/bang/pooling.cc b/src/kernels/bang/pooling.cc index 9886366a..f5d68366 100644 --- a/src/kernels/bang/pooling.cc +++ b/src/kernels/bang/pooling.cc @@ -16,26 +16,26 @@ class poolingCnnl : public BangKernelWithoutConfig { const auto [ph, pw, sh, sw, dh, dw] = op->getPadStrideDilation(); // get inputs - int inArray[4] = {n,c,h,w}; + int inArray[4] = {n, c, h, w}; cnnlTensorDescriptor_t inDesc; checkCnnlError(cnnlCreateTensorDescriptor(&inDesc)); - checkCnnlError(cnnlSetTensorDescriptor( - inDesc, CNNL_LAYOUT_NCHW, CNNL_DTYPE_FLOAT, 4, inArray)); + checkCnnlError(cnnlSetTensorDescriptor(inDesc, CNNL_LAYOUT_NCHW, + CNNL_DTYPE_FLOAT, 4, inArray)); // get maxpool descriptor cnnlPoolingDescriptor_t poolingDesc; checkCnnlError(cnnlCreatePoolingDescriptor(&poolingDesc)); checkCnnlError(cnnlSetPooling2dDescriptor_v2( - poolingDesc, getPoolingMode(), CNNL_NOT_PROPAGATE_NAN, kh, kw, ph, ph, - pw, pw, sh, sw, dh, dw, false)); + poolingDesc, getPoolingMode(), CNNL_NOT_PROPAGATE_NAN, kh, kw, ph, + ph, pw, pw, sh, sw, dh, dw, false)); // get outputs auto outVec = op->getOutput()->getDims(); - int outArray[4] = {outVec[0], outVec[1],outVec[2], outVec[3]}; + int outArray[4] = {outVec[0], outVec[1], outVec[2], outVec[3]}; cnnlTensorDescriptor_t outDesc; checkCnnlError(cnnlCreateTensorDescriptor(&outDesc)); checkCnnlError(cnnlSetTensorDescriptor(outDesc, CNNL_LAYOUT_NCHW, - CNNL_DTYPE_FLOAT, 4, outArray)); + CNNL_DTYPE_FLOAT, 4, outArray)); size_t wsSize; cnnlGetPoolingWorkspaceSize(context->cnnlHandle(), getPoolingMode(), outVec[3], outVec[2], &wsSize); diff --git a/src/kernels/bang/split.cc b/src/kernels/bang/split.cc index 77d58bd5..bfa842bc 100644 --- a/src/kernels/bang/split.cc +++ b/src/kernels/bang/split.cc @@ -35,8 +35,8 @@ class SplitCnnl : public BangKernelWithoutConfig { } int dim_array[4] = {dim[0], dim[1], dim[2], dim[3]}; checkCnnlError(cnnlCreateTensorDescriptor(&desc)); - checkCnnlError(cnnlSetTensorDescriptor( - desc, CNNL_LAYOUT_NCHW, CNNL_DTYPE_FLOAT, 4, dim_array)); + checkCnnlError(cnnlSetTensorDescriptor(desc, CNNL_LAYOUT_NCHW, + CNNL_DTYPE_FLOAT, 4, dim_array)); cnnlTensorDescriptor_t descArray[num]; for (int i = 0; i < num; ++i) { checkCnnlError(cnnlCreateTensorDescriptor(&descArray[i])); @@ -50,8 +50,8 @@ class SplitCnnl : public BangKernelWithoutConfig { BangPtr wsData = context->getWorkspace(wsSize); cnnlStatus_t stat = - cnnlSplit(context->cnnlHandle(), num, axis, desc, inputData, - wsData, wsSize, descArray, argv); + cnnlSplit(context->cnnlHandle(), num, axis, desc, inputData, wsData, + wsSize, descArray, argv); if (stat != CNNL_STATUS_SUCCESS) return; diff --git a/test/kernels/bang/test_bang_pooling.cc b/test/kernels/bang/test_bang_pooling.cc index c5172fc0..0c6d3861 100644 --- a/test/kernels/bang/test_bang_pooling.cc +++ b/test/kernels/bang/test_bang_pooling.cc @@ -10,7 +10,7 @@ namespace infini { template void testPooling(const std::function &generator, - const Shape &shape) { + const Shape &shape) { // Runtime Runtime cpuRuntime = CpuRuntimeObj::getInstance(); auto bangRuntime = make_ref(); @@ -23,7 +23,7 @@ void testPooling(const std::function &generator, // GPU Graph bangGraph = make_ref(bangRuntime); auto inputGpu = bangGraph->cloneTensor(inputCpu); - auto gpuOp = bangGraph->addOp(inputGpu, nullptr, 3,3,1,1,1,1,2,2); + auto gpuOp = bangGraph->addOp(inputGpu, nullptr, 3, 3, 1, 1, 1, 1, 2, 2); bangGraph->dataMalloc(); bangRuntime->run(bangGraph); auto outputGpu = gpuOp->getOutput(); diff --git a/test/kernels/bang/test_bang_round.cc b/test/kernels/bang/test_bang_round.cc index 0cf08955..196c526d 100644 --- a/test/kernels/bang/test_bang_round.cc +++ b/test/kernels/bang/test_bang_round.cc @@ -10,7 +10,7 @@ namespace infini { template void testRound(const std::function &generator, - const Shape &shape) { + const Shape &shape) { // Runtime Runtime cpuRuntime = CpuRuntimeObj::getInstance(); auto bangRuntime = make_ref(); diff --git a/test/kernels/bang/test_bang_split.cc b/test/kernels/bang/test_bang_split.cc index f23215f3..adee2b7c 100644 --- a/test/kernels/bang/test_bang_split.cc +++ b/test/kernels/bang/test_bang_split.cc @@ -10,7 +10,7 @@ namespace infini { template void testSplit(const std::function &generator, - const Shape &shape) { + const Shape &shape) { // Runtime Runtime cpuRuntime = CpuRuntimeObj::getInstance(); auto bangRuntime = make_ref(); @@ -23,8 +23,7 @@ void testSplit(const std::function &generator, // GPU Graph bangGraph = make_ref(bangRuntime); auto inputGpu1 = bangGraph->cloneTensor(inputCpu1); - auto gpuOp = - bangGraph->addOp(inputGpu1, std::nullopt, 3, 3); + auto gpuOp = bangGraph->addOp(inputGpu1, std::nullopt, 3, 3); bangGraph->dataMalloc(); bangRuntime->run(bangGraph); auto o0Cpu = gpuOp->getOutput(0)->clone(cpuRuntime); diff --git a/test/kernels/bang/test_bang_square.cc b/test/kernels/bang/test_bang_square.cc index ab7ccfcf..822ac5ec 100644 --- a/test/kernels/bang/test_bang_square.cc +++ b/test/kernels/bang/test_bang_square.cc @@ -10,7 +10,7 @@ namespace infini { template void testSquare(const std::function &generator, - const Shape &shape) { + const Shape &shape) { // Runtime Runtime cpuRuntime = CpuRuntimeObj::getInstance(); auto bangRuntime = make_ref(); diff --git a/test/kernels/bang/test_bang_squaredDifference.cc b/test/kernels/bang/test_bang_squaredDifference.cc index 6221b792..a963e9bb 100644 --- a/test/kernels/bang/test_bang_squaredDifference.cc +++ b/test/kernels/bang/test_bang_squaredDifference.cc @@ -9,8 +9,9 @@ namespace infini { template -void testSquaredDifference(const std::function &generator, - const Shape &shape) { +void testSquaredDifference( + const std::function &generator, + const Shape &shape) { // Runtime Runtime cpuRuntime = CpuRuntimeObj::getInstance(); auto bangRuntime = make_ref(); @@ -40,7 +41,8 @@ void testSquaredDifference(const std::function & } TEST(cnnl_SquaredDifference, run) { - testSquaredDifference(IncrementalGenerator(), Shape{1, 2, 2, 3}); + testSquaredDifference(IncrementalGenerator(), + Shape{1, 2, 2, 3}); } } // namespace infini