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Misc Windows lint

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Summary: Closes https://github.com/caffe2/caffe2/pull/1656

Differential Revision: D6633052

Pulled By: Yangqing

fbshipit-source-id: 5eeb3912fc769cfd06d252f3ed1d8d5f2a207cfc
This commit is contained in:
Yangqing Jia
2017-12-23 19:56:40 -08:00
committed by Facebook Github Bot
parent 1a0eefd5fc
commit efa7c895f6
20 changed files with 51 additions and 31 deletions
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1
.gitignore vendored
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@ -55,6 +55,7 @@
# Visual Studio Code files
.vscode
.vs
# OSX dir files
.DS_Store

3
caffe2/contrib/script/compiler.cc
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@ -108,7 +108,6 @@ struct DefCompiler {
return env[ident.name()];
}
void emitAssignment(const Assign& stmt) {
OperatorDef* op;
std::vector<std::string> outputs;
for (auto lhs : stmt.lhs()) {
std::string name = getLHS(lhs);
@ -762,7 +761,7 @@ struct CompilationUnitImpl {
}
private:
friend class DefCompiler;
friend struct DefCompiler;
SymbolTable functions;
};

3
caffe2/core/tensor.h
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@ -835,7 +835,8 @@ void TensorPrinter::Print(const Tensor<CPUContext>& tensor) {
std::stringstream values_stream;
// One most likely doesn't want to print int64-number of items for visual
// inspection, so we cast down to int here.
int total_count = std::min(tensor.size(), TIndex(limit_));
int total_count = static_cast<int>(
std::min(tensor.size(), TIndex(limit_)));
const T* tensor_data = tensor.template data<T>();
for (int i = 0; i < total_count - 1; ++i) {
values_stream << tensor_data[i] << ",";

3
caffe2/core/timer.h
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@ -39,7 +39,8 @@ class Timer {
*/
inline void Start() { start_time_ = clock::now(); }
inline float NanoSeconds() {
return std::chrono::duration_cast<ns>(clock::now() - start_time_).count();
return static_cast<float>(
std::chrono::duration_cast<ns>(clock::now() - start_time_).count());
}
/**
* @brief Returns the elapsed time in milliseconds.

2
caffe2/operators/batch_box_cox_op.cc
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@ -110,7 +110,7 @@ bool BatchBoxCoxOp<CPUContext>::DoRunWithType() {
const auto* lambda1_ptr = lambda1.template data<T>();
const auto* lambda2_ptr = lambda2.template data<T>();
const T k_eps = 1e-6;
const T k_eps = static_cast<T>(1e-6);
#ifdef CAFFE2_USE_MKL
if (min_block_size_ < 1) {

2
caffe2/operators/distance_op.cc
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@ -99,7 +99,7 @@ bool L1DistanceGradientOp<float, CPUContext>::RunOnDevice() {
for (int j = 0; j < D; ++j) {
const float temp =
(X.data<float>())[offset + j] - (Y.data<float>())[offset + j];
const float kEps = 1e-12;
const float kEps = 1e-12f;
if (temp < -kEps) {
dX->mutable_data<float>()[offset + j] = -(dDistance.data<float>())[i];
dY->mutable_data<float>()[offset + j] = (dDistance.data<float>())[i];

4
caffe2/operators/h_softmax_op.h
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@ -45,7 +45,7 @@ class HSoftmaxOpBase : public Operator<Context> {
Tensor<Context> sum_multiplier_;
Tensor<Context> bias_multiplier_;
static constexpr T kLOG_THRESHOLD() {
return 1e-20;
return 1e-20f;
}
static std::unordered_map<int, PathProto> getHierarchyForLabels(
int M,
@ -132,7 +132,7 @@ class HSoftmaxSearchOp final : public HSoftmaxOp<T, Context> {
HSoftmaxSearchOp(const OperatorDef& operator_def, Workspace* ws)
: HSoftmaxOp<T, Context>(operator_def, ws),
top_n_(OperatorBase::GetSingleArgument<int>("topN", 5)),
beam_(OperatorBase::GetSingleArgument<float>("beam", 0.01)) {
beam_(OperatorBase::GetSingleArgument<float>("beam", 0.01f)) {
CAFFE_ENFORCE(tree_.ParseFromString(
OperatorBase::GetSingleArgument<string>("tree", "")));
}

2
caffe2/operators/index_hash_ops.h
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@ -68,7 +68,7 @@ class IndexHashOp : public Operator<Context> {
for (int i = 0; i < sizeof(T) / sizeof(int8_t); i++) {
hashed = hashed * 65537 + bytes[i];
}
hashed = (modulo_ + hashed % modulo_) % modulo_;
hashed = static_cast<T>((modulo_ + hashed % modulo_) % modulo_);
return hashed;
}

4
caffe2/operators/instance_norm_op.h
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@ -29,7 +29,7 @@ class InstanceNormOp : public Operator<Context> {
USE_OPERATOR_CONTEXT_FUNCTIONS;
InstanceNormOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
epsilon_(OperatorBase::GetSingleArgument<T>("epsilon", 1e-5)),
epsilon_(OperatorBase::GetSingleArgument<T>("epsilon", 1e-5f)),
order_(StringToStorageOrder(
OperatorBase::GetSingleArgument<string>("order", "NCHW"))) {
CAFFE_ENFORCE(epsilon_ >= 0, "Must pass a nonnegative epsilon.");
@ -69,7 +69,7 @@ class InstanceNormGradientOp : public Operator<Context> {
USE_OPERATOR_CONTEXT_FUNCTIONS;
InstanceNormGradientOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
epsilon_(OperatorBase::GetSingleArgument<T>("epsilon", 1e-5)),
epsilon_(OperatorBase::GetSingleArgument<T>("epsilon", 1e-5f)),
order_(StringToStorageOrder(
OperatorBase::GetSingleArgument<string>("order", "NCHW"))) {
CAFFE_ENFORCE(epsilon_ >= 0, "Must pass a nonnegative epsilon.");

2
caffe2/operators/layer_norm_op.h
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@ -55,7 +55,7 @@ class LayerNormGradientOp : public Operator<Context> {
LayerNormGradientOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
axis_(OperatorBase::GetSingleArgument<int>("axis", 1)),
epsilon_(OperatorBase::GetSingleArgument<float>("epsilon", 0.001)) {}
epsilon_(OperatorBase::GetSingleArgument<float>("epsilon", 0.001f)) {}
~LayerNormGradientOp() {}
template <typename T>

2
caffe2/operators/lengths_reducer_rowwise_8bit_ops.h
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@ -29,7 +29,7 @@
namespace caffe2 {
namespace {
const float kEqualityThreshold = 1e-10;
const float kEqualityThreshold = 1e-10f;
}
template <

2
caffe2/operators/logit_op.cc
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@ -19,7 +19,7 @@
namespace caffe2 {
struct LogitCPUFunctor {
explicit LogitCPUFunctor(OperatorBase& op)
: eps_(op.GetSingleArgument<float>("eps", 1e-6)) {
: eps_(op.GetSingleArgument<float>("eps", 1e-6f)) {
CAFFE_ENFORCE_GT(eps_, 0.0);
CAFFE_ENFORCE_LT(eps_, 0.5);
}

2
caffe2/operators/logit_op.h
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@ -10,7 +10,7 @@ class LogitGradientOp final : public Operator<Context> {
USE_OPERATOR_CONTEXT_FUNCTIONS;
LogitGradientOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
eps_(OperatorBase::GetSingleArgument<float>("eps", 1e-6)) {}
eps_(OperatorBase::GetSingleArgument<float>("eps", 1e-6f)) {}
~LogitGradientOp() {}
bool RunOnDevice() override;

4
caffe2/operators/lpnorm_op.cc
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@ -44,7 +44,7 @@ bool LpNormGradientOp<float, CPUContext>::RunOnDevice() {
CAFFE_ENFORCE_EQ(dnorm.ndim(), 1);
CAFFE_ENFORCE_EQ(dnorm.dim32(0), 1);
dX->ResizeLike(X);
const float kEps = 1e-12;
const float kEps = 1e-12f;
if (p_ == 1) {
// Todo: implement in eigen
@ -60,7 +60,7 @@ bool LpNormGradientOp<float, CPUContext>::RunOnDevice() {
}
} else if (p_ == 2) {
EigenVectorMap<float>(dX->mutable_data<float>(), X.size()).array() =
ConstEigenVectorMap<float>(X.data<float>(), X.size()).array() * 2.0 *
ConstEigenVectorMap<float>(X.data<float>(), X.size()).array() * 2.0f *
(dnorm.data<float>())[0];
}

2
caffe2/operators/rmac_regions_op.h
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@ -28,7 +28,7 @@ class RMACRegionsOp final : public Operator<Context> {
RMACRegionsOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
scales_(OperatorBase::GetSingleArgument<int>("scales", 3)),
overlap_(OperatorBase::GetSingleArgument<float>("overlap", 0.4)) {}
overlap_(OperatorBase::GetSingleArgument<float>("overlap", 0.4f)) {}
USE_OPERATOR_CONTEXT_FUNCTIONS;

9
caffe2/operators/sequence_ops.cc
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@ -31,16 +31,22 @@ void GatherPaddingOp<CPUContext>::GatherPadding(
const int* lengths_ptr,
T* padding_start_ptr,
T* padding_end_ptr) {
CAFFE_ENFORCE(
(!std::is_same<bool, T>::value),
"GatherPadding should not be executed on an input of type bool, as "
"addition is not properly defined with booleans.");
int64_t total_length = 0;
for (int i = 0; i < lengths_size; ++i) {
// check total length consistency
const auto length = lengths_ptr[i];
total_length += length;
CAFFE_ENFORCE_LE(total_length, outer_size);
// accumulate start paddings
for (int j = 0; j < startPaddingWidth_; ++j) {
for (int k = 0; k < block_size; ++k) {
// Note: MSVC warns about unsafe use of type bool in operation.
// This is now guarded by a CAFFE_ENFORCE so we can suppress it.
#pragma warning(suppress: 4804)
padding_start_ptr[k] += in_ptr[k];
}
in_ptr += block_size;
@ -49,6 +55,7 @@ void GatherPaddingOp<CPUContext>::GatherPadding(
// accumulate end paddings
for (int j = 0; j < endPaddingWidth_; ++j) {
for (int k = 0; k < block_size; ++k) {
#pragma warning(suppress: 4804)
padding_end_ptr[k] += in_ptr[k];
}
in_ptr += block_size;

2
caffe2/operators/softmax_shared.cc
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@ -62,7 +62,7 @@ void SoftmaxCPU(
for (int i = 0; i < N; ++i) {
for (int j = 0; j < D; ++j) {
Ydata[i * D + j] =
Xdata[i * D + j] - rowmax[i] - log(fmaxf(scale[i], 1e-20));
Xdata[i * D + j] - rowmax[i] - log(fmaxf(scale[i], 1e-20f));
}
}
}

6
caffe2/operators/spatial_batch_norm_op.h
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@ -30,8 +30,8 @@ class SpatialBNOp : public Operator<Context> {
SpatialBNOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
is_test_(OperatorBase::GetSingleArgument<int>(OpSchema::Arg_IsTest, 0)),
epsilon_(OperatorBase::GetSingleArgument<float>("epsilon", 1e-5)),
momentum_(OperatorBase::GetSingleArgument<float>("momentum", 0.9)),
epsilon_(OperatorBase::GetSingleArgument<float>("epsilon", 1e-5f)),
momentum_(OperatorBase::GetSingleArgument<float>("momentum", 0.9f)),
order_(StringToStorageOrder(
OperatorBase::GetSingleArgument<string>("order", "NCHW"))) {
// TODO(jiayq): update the input and output size checks.
@ -63,7 +63,7 @@ class SpatialBNGradientOp : public Operator<Context> {
SpatialBNGradientOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
is_test_(OperatorBase::GetSingleArgument<int>(OpSchema::Arg_IsTest, 0)),
epsilon_(OperatorBase::GetSingleArgument<float>("epsilon", 1e-5)),
epsilon_(OperatorBase::GetSingleArgument<float>("epsilon", 1e-5f)),
order_(StringToStorageOrder(
OperatorBase::GetSingleArgument<string>("order", "NCHW"))) {
CAFFE_ENFORCE(InputSize() == 5);

2
caffe2/queue/queue_ops.h
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@ -228,7 +228,7 @@ class WeightedSampleDequeueBlobsOp final : public Operator<Context> {
}
std::partial_sum(cumProbs_.begin(), cumProbs_.end(), cumProbs_.begin());
// Put last value to be 1.0001 to avoid numerical issues.
cumProbs_.back() = 1.0001;
cumProbs_.back() = 1.0001f;
LOG(INFO) << "Dequeue weights: " << weights;
LOG(INFO) << "cumProbs: " << cumProbs_;

25
cmake/MiscCheck.cmake
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@ -106,16 +106,27 @@ cmake_pop_check_state()
# "THIRD_PARTY_NAME related"
if (${CMAKE_CXX_COMPILER_ID} STREQUAL "MSVC")
add_compile_options(
/wd4018 # (3): Signed/unsigned mismatch
##########################################
# Third party related. Cannot remove.
##########################################
/wd4065 # (3): switch with default but no case. Protobuf related.
/wd4244 # (2/3/4): Possible loss of precision
/wd4267 # (3): Conversion of size_t to smaller type. Possible loss of data.
/wd4503 # (1): decorated name length exceeded, name was truncated. Eigen related.
/wd4503 # (1): decorated name length exceeded, name was truncated.
# Eigen related.
/wd4506 # (1): no definition for inline function. Protobuf related.
/wd4554 # (3)： check operator precedence for possible error. Eigen related.
/wd4800 # (3): Forcing non-boolean value to true or false.
/wd4996 # (3): Use of a deprecated member
/wd4554 # (3)： check operator precedence for possible error.
# Eigen related.
##########################################
# These are directly Caffe2 related.
##########################################
/wd4018 # (3): Signed/unsigned mismatch. We've used it in many places of
# the code and it would be hard to correct all.
/wd4244 # (2/3/4): Possible loss of precision. Various cases where we
# implicitly cast TIndex to int etc. Need further cleaning.
/wd4267 # (3): Conversion of size_t to smaller type. Same reason as 4244.
/wd4996 # (3): Use of deprecated POSIX functions. Since we develop
# mainly on Linux, this is ignored.
)
# Exception handing for compiler warining C4530, see
# https://msdn.microsoft.com/en-us/library/2axwkyt4.aspx
add_definitions("/EHsc")