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Merge pull request #5187 from chengduoZH/fix_pool_op
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fix pool op
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chengduo committed Oct 30, 2017
2 parents 0049ce0 + 6bdf5c1 commit 8efd087
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Showing 8 changed files with 109 additions and 75 deletions.
5 changes: 4 additions & 1 deletion paddle/operators/pool_cudnn_op.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,7 @@ class PoolCudnnOpKernel : public framework::OpKernel<T> {
std::vector<int> paddings = ctx.Attr<std::vector<int>>("paddings");
if (ctx.Attr<bool>("globalPooling")) {
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(input->dims()[i + 2]);
}
}
Expand Down Expand Up @@ -97,8 +98,10 @@ class PoolCudnnGradOpKernel : public framework::OpKernel<T> {
std::vector<int> paddings = ctx.Attr<std::vector<int>>("paddings");

if (ctx.Attr<bool>("globalPooling")) {
for (size_t i = 0; i < ksize.size(); ++i)
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(input->dims()[i + 2]);
}
}

const T *input_data = input->data<T>();
Expand Down
45 changes: 26 additions & 19 deletions paddle/operators/pool_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -39,8 +39,10 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {

if (ctx->Attrs().Get<bool>("globalPooling")) {
ksize.resize(static_cast<size_t>(in_x_dims.size()) - 2);
for (size_t i = 0; i < ksize.size(); ++i)
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(in_x_dims[i + 2]);
}
}

PADDLE_ENFORCE(in_x_dims.size() - ksize.size() == 2U,
Expand Down Expand Up @@ -84,15 +86,16 @@ Pool2dOpMaker::Pool2dOpMaker(framework::OpProto *proto,
"(string), pooling type, can be \"max\" for max-pooling "
"and \"avg\" for average-pooling.")
.InEnum({"max", "avg"});
AddAttr<std::vector<int>>(
"ksize",
"(vector ), the pooling window size(height, width) of pooling operator."
"If globalPooling = true, ksize is ignored and need not be "
"specified."); // TODO(Chengduo): Add checker. (Currently,
AddAttr<std::vector<int>>("ksize",
"(vector ), the pooling window size(height, width) "
"of pooling operator."
"If globalPooling = true, ksize and paddings will "
"be ignored."); // TODO(Chengduo): Add checker.
// (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<bool>("globalPooling",
"(bool default: false), whether to use the global pooling."
"If globalPooling = true, ksize is ignored.")
"If globalPooling = true, ksize and paddings will be ignored.")
.SetDefault(false);
AddAttr<std::vector<int>>(
"strides",
Expand All @@ -101,7 +104,8 @@ Pool2dOpMaker::Pool2dOpMaker(framework::OpProto *proto,
// TypedAttrChecker don't support vector type.)
AddAttr<std::vector<int>>(
"paddings",
"(vector defalut:{0,0}), paddings(height, width) of pooling operator.")
"(vector defalut:{0,0}), paddings(height, width) of pooling operator."
"If globalPooling = true, paddings and ksize will be ignored.")
.SetDefault({0, 0}); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)

Expand Down Expand Up @@ -145,25 +149,28 @@ Pool3dOpMaker::Pool3dOpMaker(framework::OpProto *proto,
"(string), pooling type, can be \"max\" for max-pooling "
"and \"avg\" for average-pooling.")
.InEnum({"max", "avg"});
AddAttr<std::vector<int>>(
"ksize",
"(vector ), the pooling window size(depth, height, width) of pooling "
"operator."
"If globalPooling = true, ksize is ignored and need not be "
"specified."); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<std::vector<int>>("ksize",
"(vector ), the pooling window size(depth, height, "
"width) of pooling "
"operator."
"If globalPooling = true, ksize and paddings wille "
"be ignored."); // TODO(Chengduo): Add checker.
// (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<bool>("globalPooling",
"(bool default: false), whether to use the global pooling."
"If globalPooling = true, ksize is ignored.")
"If globalPooling = true, ksize and paddings wille be ignored.")
.SetDefault(false);
AddAttr<std::vector<int>>("strides",
"(vector, default:{1,1,1}), strides(depth, height, "
"width) of pooling operator.")
.SetDefault({1, 1, 1}); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<std::vector<int>>("paddings",
"(vector defalut:{0,0,0}), paddings(depth, height, "
"width) of pooling operator.")
AddAttr<std::vector<int>>(
"paddings",
"(vector defalut:{0,0,0}), paddings(depth, height, "
"width) of pooling operator."
"If globalPooling = true, ksize and paddings wille be ignored.")
.SetDefault({0, 0, 0}); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)

Expand Down
7 changes: 6 additions & 1 deletion paddle/operators/pool_op.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -63,6 +63,7 @@ class PoolKernel : public framework::OpKernel<T> {
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");
if (context.Attr<bool>("globalPooling")) {
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(in_x->dims()[i + 2]);
}
}
Expand Down Expand Up @@ -103,6 +104,7 @@ class PoolKernel : public framework::OpKernel<T> {
paddings, pool_process);
}
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
}
}
};
Expand All @@ -123,8 +125,10 @@ class PoolGradKernel : public framework::OpKernel<T> {
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");

if (context.Attr<bool>("globalPooling")) {
for (size_t i = 0; i < ksize.size(); ++i)
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(in_x->dims()[i + 2]);
}
}

if (in_x_grad) {
Expand Down Expand Up @@ -164,6 +168,7 @@ class PoolGradKernel : public framework::OpKernel<T> {
*out_grad, ksize, strides, paddings, pool_process);
}
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
}
}
}
Expand Down
65 changes: 37 additions & 28 deletions paddle/operators/pool_with_index_op.cc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -46,8 +46,10 @@ class MaxPoolWithIndexOp : public framework::OperatorWithKernel {

if (ctx->Attrs().Get<bool>("globalPooling")) {
ksize.resize(static_cast<size_t>(in_x_dims.size()) - 2);
for (size_t i = 0; i < ksize.size(); ++i)
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(in_x_dims[i + 2]);
}
}

PADDLE_ENFORCE(in_x_dims.size() - ksize.size() == 2U,
Expand Down Expand Up @@ -87,31 +89,33 @@ class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput(
"X",
"(Tensor) The input tensor of pooling operator. "
"(Tensor), the input tensor of pooling operator. "
"The format of input tensor is NCHW. Where N is batch size, C is the "
"number of channels, H and W is the height and width of image.");
AddOutput("Out",
"(Tensor) The output tensor of pooling operator."
"(Tensor), the output tensor of pooling operator."
"The format of output tensor is also NCHW."
"Where N is batch size, C is "
"the number of channels, H and W is the height and "
"width of image.");
AddOutput("Mask",
"(Tensor) The Mask tensor of pooling operator."
"(Tensor), the Mask tensor of pooling operator."
"The format of output tensor is also NCHW."
"Where N is batch size, C is the number of channels, H and W "
"is the height and width of image."
"The value in it is the index in current feature map");

AddAttr<std::vector<int>>(
"ksize",
"(vector ), the pooling window size(height, width) of pooling operator."
"If globalPooling = true, ksize is ignored and need not be "
"specified."); // TODO(Chengduo): Add checker. (Currently,
AddAttr<std::vector<int>>("ksize",
"(vector ), the pooling window size(height, "
"width) of pooling operator."
"If globalPooling = true, ksize and paddings "
"will be ignored."); // TODO(Chengduo): Add
// checker. (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<bool>("globalPooling",
"(bool default: false), whether to use the global pooling."
"If globalPooling = true, ksize is ignored.")
AddAttr<bool>(
"globalPooling",
"(bool default: false), whether to use the global pooling."
"If globalPooling = true, ksize and paddings will be ignored.")
.SetDefault(false);
AddAttr<std::vector<int>>(
"strides",
Expand All @@ -120,7 +124,8 @@ class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
// TypedAttrChecker don't support vector type.)
AddAttr<std::vector<int>>(
"paddings",
"(vector defalut:{0,0}), paddings(height, width) of pooling operator.")
"(vector defalut:{0, 0}), paddings(height, width) of pooling operator."
"If globalPooling = true, paddings and will be ignored.")
.SetDefault({0, 0}); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)

Expand Down Expand Up @@ -153,42 +158,46 @@ class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput(
"X",
"(Tensor) The input tensor of pooling operator. "
"(Tensor), the input tensor of pooling operator. "
"The format of input tensor is NCDHW. Where N is batch size, C is "
"the number of channels, D, H and W is the depth, height and width of "
"image.");
AddOutput("Out",
"(Tensor) The output tensor of pooling operator."
"(Tensor), the output tensor of pooling operator."
"The format of output tensor is also NCDHW."
"Where N is batch size, C is "
"the number of channels, D, H and W is the depth, height and "
"width of image.");
AddOutput("Mask",
"(Tensor) The Mask tensor of pooling operator."
"(Tensor), the Mask tensor of pooling operator."
"The format of output tensor is also NCDHW."
"Where N is batch size, C is the number of channels, D, H and W "
"is the depth, height and width of image."
"The value in it is the index in current feature map");

AddAttr<std::vector<int>>(
"ksize",
"(vector ), the pooling window size(depth, height, width) of pooling "
"operator."
"If globalPooling = true, ksize is ignored and need not be "
"specified."); // TODO(Chengduo): Add checker. (Currently,
AddAttr<std::vector<int>>("ksize",
"(vector), the pooling window size(depth, "
"height, width) of pooling "
"operator."
"If globalPooling = true, ksize and paddings "
"will be ignored."); // TODO(Chengduo): Add
// checker. (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<bool>("globalPooling",
"(bool default: false), whether to use the global pooling."
"If globalPooling = true, ksize is ignored.")
AddAttr<bool>(
"globalPooling",
"(bool default: false), whether to use the global pooling."
"If globalPooling = true, ksize and paddings will be ignored.")
.SetDefault(false);
AddAttr<std::vector<int>>("strides",
"(vector, default:{1,1,1}), strides(depth, "
"height, width) of pooling operator.")
.SetDefault({1, 1, 1}); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)
AddAttr<std::vector<int>>("paddings",
"(vector defalut:{0,0,0}), paddings(depth, "
"height, width) of pooling operator.")
AddAttr<std::vector<int>>(
"paddings",
"(vector defalut:{0,0,0}), paddings(depth, "
"height, width) of pooling operator."
"If globalPooling = true, paddings and ksize will be ignored.")
.SetDefault({0, 0, 0}); // TODO(Chengduo): Add checker. (Currently,
// TypedAttrChecker don't support vector type.)

Expand Down
4 changes: 4 additions & 0 deletions paddle/operators/pool_with_index_op.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -37,6 +37,7 @@ class MaxPoolWithIndexKernel : public framework::OpKernel<T> {
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");
if (context.Attr<bool>("globalPooling")) {
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(in_x->dims()[i + 2]);
}
}
Expand All @@ -54,6 +55,7 @@ class MaxPoolWithIndexKernel : public framework::OpKernel<T> {
pool3d_forward(context.device_context(), *in_x, *out, *mask, ksize,
strides, paddings);
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
}
}
};
Expand All @@ -72,6 +74,7 @@ class MaxPoolWithIndexGradKernel : public framework::OpKernel<T> {
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");
if (context.Attr<bool>("globalPooling")) {
for (size_t i = 0; i < ksize.size(); ++i) {
paddings[i] = 0;
ksize[i] = static_cast<int>(in_x_grad->dims()[i + 2]);
}
}
Expand All @@ -95,6 +98,7 @@ class MaxPoolWithIndexGradKernel : public framework::OpKernel<T> {
pool3d_backward(context.device_context(), *in_x_grad, *out_grad,
*mask, ksize, strides, paddings);
} break;
default: { PADDLE_THROW("Pool op only supports 2D and 3D input."); }
}
}
}
Expand Down
5 changes: 4 additions & 1 deletion python/paddle/v2/framework/tests/test_pool2d_op.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -49,9 +49,12 @@ def setUp(self):
self.init_test_case()
self.init_op_type()
self.init_pool_type()
if self.global_pool:
self.paddings = [0 for _ in range(len(self.paddings))]
input = np.random.random(self.shape).astype("float32")
output = self.pool2D_forward_naive(input, self.ksize, self.strides,
self.paddings, self.global_pool)
self.paddings,
self.global_pool).astype("float32")
self.inputs = {'X': input}

self.attrs = {
Expand Down
19 changes: 11 additions & 8 deletions python/paddle/v2/framework/tests/test_pool3d_op.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -54,10 +54,13 @@ def avg_pool3D_forward_naive(x, ksize, strides, paddings=[0, 0], global_pool=0):

class TestPool3d_Op(OpTest):
def setUp(self):
self.initTestCase()
self.init_test_case()
if self.global_pool:
self.paddings = [0 for _ in range(len(self.paddings))]
input = np.random.random(self.shape).astype("float32")
output = self.pool3D_forward_naive(input, self.ksize, self.strides,
self.paddings, self.global_pool)
self.paddings,
self.global_pool).astype("float32")
self.inputs = {'X': input}

self.attrs = {
Expand All @@ -77,7 +80,7 @@ def test_check_grad(self):
if self.pool_type != "max":
self.check_grad(set(['X']), 'Out', max_relative_error=0.07)

def initTestCase(self):
def init_test_case(self):
self.global_pool = True
self.op_type = "pool3d"
self.pool_type = "avg"
Expand All @@ -89,7 +92,7 @@ def initTestCase(self):


class TestCase1(TestPool3d_Op):
def initTestCase(self):
def init_test_case(self):
self.global_pool = False
self.op_type = "pool3d"
self.pool_type = "avg"
Expand All @@ -101,7 +104,7 @@ def initTestCase(self):


class TestCase2(TestPool3d_Op):
def initTestCase(self):
def init_test_case(self):
self.global_pool = False
self.op_type = "pool3d"
self.pool_type = "avg"
Expand All @@ -113,7 +116,7 @@ def initTestCase(self):


class TestCase3(TestPool3d_Op):
def initTestCase(self):
def init_test_case(self):
self.global_pool = True
self.op_type = "pool3d"
self.pool_type = "max"
Expand All @@ -125,7 +128,7 @@ def initTestCase(self):


class TestCase4(TestPool3d_Op):
def initTestCase(self):
def init_test_case(self):
self.global_pool = False
self.op_type = "pool3d"
self.pool_type = "max"
Expand All @@ -137,7 +140,7 @@ def initTestCase(self):


class TestCase5(TestPool3d_Op):
def initTestCase(self):
def init_test_case(self):
self.global_pool = False
self.op_type = "pool3d"
self.pool_type = "max"
Expand Down
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