blob: 275691d9cece9c9498f4a2e491ef5c6258a1542a [file] [log] [blame]
#include <caffe2/ideep/operators/conv_pool_base_op.h>
using namespace caffe2;
namespace {
class IDEEPPoolOp final : public IDEEPConvPoolOpBase {
public:
USE_IDEEP_DEF_ALIASES();
USE_IDEEP_CONV_POOL_BASE_FUNCTIONS();
IDEEPPoolOp(const OperatorDef& operator_def, Workspace* ws)
: IDEEPConvPoolOpBase(operator_def, ws) {
CAFFE_ENFORCE(
(dilation_h() == 1) && (dilation_w() == 1),
"Pooling op does not support dilation right now.");
if (!global_pooling_) {
CAFFE_ENFORCE(
pad_t() < kernel_h() && pad_b() < kernel_h() &&
pad_l() < kernel_w() && pad_r() < kernel_w(),
"Pad should be smaller than kernel.");
}
bool training_mode = OperatorBase::GetSingleArgument<int>("training_mode", 1);
pk_ = training_mode ? iprop::forward_training : iprop::forward_inference;
// Figure out the pooling descriptor.
if (operator_def.type().substr(0, 7) == "MaxPool") {
algo_ = ialgo::pooling_max;
} else if (operator_def.type().substr(0, 11) == "AveragePool") {
algo_ = ialgo::pooling_avg;
} else {
LOG(FATAL) << "Unsupported pooling method: " << operator_def.type();
}
}
// NOLINTNEXTLINE(modernize-use-equals-default)
~IDEEPPoolOp() override {}
bool RunOnDeviceWithOrderNCHW() override {
auto& X = Input(INPUT);
auto* Y = Output(OUTPUT);
auto Y_dims = CalcOutputDims(X, X.get_dim(1));
if (cached_X_descriptor_ != X.get_descriptor()) {
cached_X_descriptor_ = X.dup_descriptor();
}
ideep::pooling_forward::compute(X, Y_dims, *Y,
{stride_.begin(), stride_.end()},
{kernel_.begin(), kernel_.end()},
pad_tl(), pad_br(), algo_, pk_);
return true;
}
private:
iprop pk_;
ialgo algo_;
itensor::descriptor cached_X_descriptor_;
INPUT_TAGS(INPUT);
OUTPUT_TAGS(OUTPUT);
};
class IDEEPPoolGradientOp final : public IDEEPConvPoolOpBase {
public:
USE_IDEEP_DEF_ALIASES();
USE_IDEEP_CONV_POOL_BASE_FUNCTIONS();
IDEEPPoolGradientOp(const OperatorDef& operator_def, Workspace* ws)
: IDEEPConvPoolOpBase(operator_def, ws) {
CAFFE_ENFORCE(
(dilation_h() == 1) && (dilation_w() == 1),
"Pooling op does not support dilation right now.");
if (!global_pooling_) {
CAFFE_ENFORCE(
pad_t() < kernel_h() && pad_b() < kernel_h() &&
pad_l() < kernel_w() && pad_r() < kernel_w(),
"Pad should be smaller than kernel.");
}
// Figure out the pooling descriptor.
if (operator_def.type().substr(0, 15) == "MaxPoolGradient") {
algo_ = ialgo::pooling_max;
} else if (operator_def.type().substr(0, 19) == "AveragePoolGradient") {
algo_ = ialgo::pooling_avg;
} else {
LOG(FATAL) << "Unsupported pooling method: " << operator_def.type();
}
}
// NOLINTNEXTLINE(modernize-use-equals-default)
~IDEEPPoolGradientOp() override {}
bool RunOnDeviceWithOrderNCHW() override {
const auto& X = Input(INPUT);
const auto& Y = Input(OUTPUT);
const auto& dY = Input(OUTPUT_GRAD);
auto* dX = Output(INPUT_GRAD);
ideep::pooling_backward::compute(dY, Y, X, *dX,
{stride_.begin(), stride_.end()},
{kernel_.begin(), kernel_.end()},
pad_tl(), pad_br(), algo_);
return true;
}
private:
ialgo algo_;
INPUT_TAGS(INPUT, OUTPUT, OUTPUT_GRAD);
OUTPUT_TAGS(INPUT_GRAD);
};
REGISTER_IDEEP_OPERATOR(MaxPool, IDEEPPoolOp);
REGISTER_IDEEP_OPERATOR(MaxPoolGradient, IDEEPPoolGradientOp);
REGISTER_IDEEP_OPERATOR(AveragePool, IDEEPPoolOp);
REGISTER_IDEEP_OPERATOR(AveragePoolGradient, IDEEPPoolGradientOp);
} // namespace