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Merge pull request #5608 from chengduoZH/fix_pooling_function_parameter_order

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fix pooling functor parameter order
mobile_baidu
chengduo 7 years ago committed by GitHub
parent d7319c2220 2160497786
commit feaf1e2db5
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GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 278 additions and 272 deletions
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118
paddle/operators/math/pooling.cc
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334
paddle/operators/math/pooling.cu
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50
paddle/operators/math/pooling.h
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@ -88,60 +88,62 @@ template <typename Place, typename PoolProcess, typename T>
class Pool2dFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& output,
std::vector<int>& ksize, std::vector<int>& strides,
std::vector<int>& paddings, PoolProcess pool_compute);
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_compute, framework::Tensor* output);
};
template <typename Place, typename PoolProcess, typename T>
class Pool2dGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& input_grad,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_compute);
PoolProcess pool_compute, framework::Tensor* input_grad);
};
template <typename Place, class T>
class MaxPool2dGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& input_grad,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings);
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad);
};
template <typename Place, typename PoolProcess, typename T>
class Pool3dFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& output,
std::vector<int>& ksize, std::vector<int>& strides,
std::vector<int>& paddings, PoolProcess pool_compute);
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_compute, framework::Tensor* output);
};
template <typename Place, typename PoolProcess, typename T>
class Pool3dGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& input_grad,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_compute);
PoolProcess pool_compute, framework::Tensor* input_grad);
};
template <typename Place, class T>
class MaxPool3dGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& input_grad,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings);
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad);
};
/*
@ -155,38 +157,38 @@ template <typename Place, typename T>
class MaxPool2dWithIndexFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& output,
framework::Tensor& mask, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings);
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* output, framework::Tensor* mask);
};
template <typename Place, typename T>
class MaxPool2dWithIndexGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
framework::Tensor& input_grad,
const framework::Tensor& output_grad,
const framework::Tensor& mask, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings);
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad);
};
template <typename Place, typename T>
class MaxPool3dWithIndexFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, framework::Tensor& output,
framework::Tensor& mask, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings);
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* output, framework::Tensor* mask);
};
template <typename Place, typename T>
class MaxPool3dWithIndexGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
framework::Tensor& input_grad,
const framework::Tensor& output_grad,
const framework::Tensor& mask, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings);
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad);
};
} // namespace math

32
paddle/operators/pool_op.h
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@ -75,16 +75,16 @@ class PoolKernel : public framework::OpKernel<T> {
Place, paddle::operators::math::MaxPool<T>, T>
pool2d_forward;
paddle::operators::math::MaxPool<T> pool_process;
pool2d_forward(context.device_context(), *in_x, *out, ksize, strides,
paddings, pool_process);
pool2d_forward(context.device_context(), *in_x, ksize, strides,
paddings, pool_process, out);
} else if (pooling_type == "avg") {
paddle::operators::math::Pool2dFunctor<
Place, paddle::operators::math::AvgPool<T>, T>
pool2d_forward;
paddle::operators::math::AvgPool<T> pool_process;
pool2d_forward(context.device_context(), *in_x, *out, ksize, strides,
paddings, pool_process);
pool2d_forward(context.device_context(), *in_x, ksize, strides,
paddings, pool_process, out);
}
} break;
case 3: {
@ -93,15 +93,15 @@ class PoolKernel : public framework::OpKernel<T> {
Place, paddle::operators::math::MaxPool<T>, T>
pool3d_forward;
paddle::operators::math::MaxPool<T> pool_process;
pool3d_forward(context.device_context(), *in_x, *out, ksize, strides,
paddings, pool_process);
pool3d_forward(context.device_context(), *in_x, ksize, strides,
paddings, pool_process, out);
} else if (pooling_type == "avg") {
paddle::operators::math::Pool3dFunctor<
Place, paddle::operators::math::AvgPool<T>, T>
pool3d_forward;
paddle::operators::math::AvgPool<T> pool_process;
pool3d_forward(context.device_context(), *in_x, *out, ksize, strides,
paddings, pool_process);
pool3d_forward(context.device_context(), *in_x, ksize, strides,
paddings, pool_process, out);
}
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
@ -142,30 +142,30 @@ class PoolGradKernel : public framework::OpKernel<T> {
if (pooling_type == "max") {
paddle::operators::math::MaxPool2dGradFunctor<Place, T>
pool2d_backward;
pool2d_backward(context.device_context(), *in_x, *in_x_grad, *out,
*out_grad, ksize, strides, paddings);
pool2d_backward(context.device_context(), *in_x, *out, *out_grad,
ksize, strides, paddings, in_x_grad);
} else if (pooling_type == "avg") {
paddle::operators::math::Pool2dGradFunctor<
Place, paddle::operators::math::AvgPoolGrad<T>, T>
pool2d_backward;
paddle::operators::math::AvgPoolGrad<T> pool_process;
pool2d_backward(context.device_context(), *in_x, *in_x_grad, *out,
*out_grad, ksize, strides, paddings, pool_process);
pool2d_backward(context.device_context(), *in_x, *out, *out_grad,
ksize, strides, paddings, pool_process, in_x_grad);
}
} break;
case 3: {
if (pooling_type == "max") {
paddle::operators::math::MaxPool3dGradFunctor<Place, T>
pool3d_backward;
pool3d_backward(context.device_context(), *in_x, *in_x_grad, *out,
*out_grad, ksize, strides, paddings);
pool3d_backward(context.device_context(), *in_x, *out, *out_grad,
ksize, strides, paddings, in_x_grad);
} else if (pooling_type == "avg") {
paddle::operators::math::Pool3dGradFunctor<
Place, paddle::operators::math::AvgPoolGrad<T>, T>
pool3d_backward;
paddle::operators::math::AvgPoolGrad<T> pool_process;
pool3d_backward(context.device_context(), *in_x, *in_x_grad, *out,
*out_grad, ksize, strides, paddings, pool_process);
pool3d_backward(context.device_context(), *in_x, *out, *out_grad,
ksize, strides, paddings, pool_process, in_x_grad);
}
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }

16
paddle/operators/pool_with_index_op.h
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@ -46,14 +46,14 @@ class MaxPoolWithIndexKernel : public framework::OpKernel<T> {
case 2: {
paddle::operators::math::MaxPool2dWithIndexFunctor<Place, T>
pool2d_forward;
pool2d_forward(context.device_context(), *in_x, *out, *mask, ksize,
strides, paddings);
pool2d_forward(context.device_context(), *in_x, ksize, strides,
paddings, out, mask);
} break;
case 3: {
paddle::operators::math::MaxPool3dWithIndexFunctor<Place, T>
pool3d_forward;
pool3d_forward(context.device_context(), *in_x, *out, *mask, ksize,
strides, paddings);
pool3d_forward(context.device_context(), *in_x, ksize, strides,
paddings, out, mask);
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
}
@ -89,14 +89,14 @@ class MaxPoolWithIndexGradKernel : public framework::OpKernel<T> {
case 2: {
paddle::operators::math::MaxPool2dWithIndexGradFunctor<Place, T>
pool2d_backward;
pool2d_backward(context.device_context(), *in_x_grad, *out_grad,
*mask, ksize, strides, paddings);
pool2d_backward(context.device_context(), *out_grad, *mask, ksize,
strides, paddings, in_x_grad);
} break;
case 3: {
paddle::operators::math::MaxPool3dWithIndexGradFunctor<Place, T>
pool3d_backward;
pool3d_backward(context.device_context(), *in_x_grad, *out_grad,
*mask, ksize, strides, paddings);
pool3d_backward(context.device_context(), *out_grad, *mask, ksize,
strides, paddings, in_x_grad);
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
}

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