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fix average pooling kernel size assignment error
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modify white space and other format errors

remove wrap line whitespace format error

remove whitespace at the end of line183

change error message

add default pooling type to pool_enum::kMaxPooling

add pooling without kernel test cases

adjust pooling parameter order and add associated test points

remove wrong error test points

ignore kernel size check if global_pool is assigned to be true

modify whitespace

line length adjust

adjust linelength

finally learned to use cpplint

switch off all shape checks if global_pool is assigned

parse parameter when global_pool used

modify pooling shape inference logic

change a way to infer pooling shape

add push oshape

change kernel shape

prepare pooling parameter shapes

check lint

pooling parameters preparation

modify kernel shape computation method

modify a bit pooling_v1

more modification of pooling_v1

remove "avg pool"

tiny changes

change pooling args order back

use size_t instead of int

use changed order and only try tiny changes

try no kernel indicated to python interface with original order

useless modify for recommit
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@CoinCheung
CoinCheung committed Mar 23, 2018
1 parent 09281c7 commit d6c0da8
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Showing 4 changed files with 210 additions and 148 deletions.
37 changes: 25 additions & 12 deletions src/operator/nn/pooling-inl.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -56,11 +56,11 @@ struct PoolingParam : public dmlc::Parameter<PoolingParam> {
DMLC_DECLARE_FIELD(cudnn_off).set_default(false)
.describe("Turn off cudnn pooling and use MXNet pooling operator. ");

DMLC_DECLARE_FIELD(kernel)
DMLC_DECLARE_FIELD(kernel).set_default(TShape()) // add default value here
.enforce_nonzero()
.describe("Pooling kernel size: (y, x) or (d, y, x)");

DMLC_DECLARE_FIELD(pool_type)
DMLC_DECLARE_FIELD(pool_type).set_default(pool_enum::kMaxPooling) // add default pooling method
.add_enum("max", pool_enum::kMaxPooling)
.add_enum("avg", pool_enum::kAvgPooling)
.add_enum("sum", pool_enum::kSumPooling)
Expand Down Expand Up @@ -132,19 +132,23 @@ class PoolingOp {
using namespace mshadow;
Stream<xpu> *s = ctx.get_stream<xpu>();
const TShape& ishape = in_data.shape_;
TShape kernel = param_.kernel;
TShape padding = param_.pad;
TShape stride = param_.stride;
if (param_.global_pool) {
for (index_t i = 0; i < padding.ndim(); i++) {
kernel = TShape(ishape.data() + 2,
ishape.data() + ishape.ndim());
padding = TShape(ishape.ndim() - 2);
for (index_t i = 0; i < ishape.ndim() - 2; i++) {
padding[i] = 0;
}
stride = TShape(ishape.ndim() - 2);
}

pool(s, in_data.dptr<DType>(), in_data.shape_, out_data.shape_,
param_.global_pool?
TShape(ishape.data()+ishape.ndim()-param_.kernel.ndim(), ishape.data()+ishape.ndim())
: param_.kernel,
kernel,
padding,
param_.global_pool? TShape(param_.kernel.ndim()) : param_.stride,
stride,
param_.pool_type, req, out_data.dptr<DType>());
}

Expand All @@ -154,20 +158,24 @@ class PoolingOp {
using namespace mshadow;
Stream<xpu> *s = ctx.get_stream<xpu>();
const TShape& ishape = in_data.shape_;
TShape kernel = param_.kernel;
TShape padding = param_.pad;
TShape stride = param_.stride;
if (param_.global_pool) {
for (index_t i = 0; i < padding.ndim(); i++) {
kernel = TShape(ishape.data() + 2,
ishape.data() + ishape.ndim());
padding = TShape(ishape.ndim() - 2);
for (index_t i = 0; i < ishape.ndim() - 2; i++) {
padding[i] = 0;
}
stride = TShape(ishape.ndim() - 2);
}

unpool(s, out_grad.dptr<DType>(), in_data.dptr<DType>(), out_data.dptr<DType>(),
in_grad.shape_, out_grad.shape_,
param_.global_pool?
TShape(ishape.data()+ishape.ndim()-param_.kernel.ndim(), ishape.data()+ishape.ndim())
: param_.kernel,
kernel,
padding,
param_.global_pool? TShape(param_.kernel.ndim()) : param_.stride,
stride,
param_.pool_type, req, in_grad.dptr<DType>());
}

Expand All @@ -178,6 +186,11 @@ class PoolingOp {
template<typename xpu, typename DType>
PoolingOp<xpu, DType> &GetPoolingOp(const PoolingParam &param) {
static thread_local PoolingOp<xpu, DType> op;
// check if filter size assigned correctly
if (param.global_pool == false) {
CHECK_GT(param.kernel.ndim(), 0U)
<< "You need to set the kernel size if global pooling is not used";
}
op.Init(param);
return op;
}
Expand Down
155 changes: 76 additions & 79 deletions src/operator/nn/pooling.cc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -46,15 +46,14 @@ static void PoolingParamParser(nnvm::NodeAttrs *attrs) {
if (param.stride.ndim() == 0) param.stride = Shape2(1, 1);
if (param.pad.ndim() == 0) param.pad = Shape2(0, 0);
} else {
CHECK_EQ(param.kernel.ndim(), 3U) << param.kernel.ndim()
<< "D pooling not supported";
// ignore kernel size only if global_pool not assigned false
if (param.global_pool == false) {
CHECK_EQ(param.kernel.ndim(), 3U) << param.kernel.ndim()
<< "D pooling not supported";
}
if (param.stride.ndim() == 0) param.stride = Shape3(1, 1, 1);
if (param.pad.ndim() == 0) param.pad = Shape3(0, 0, 0);
}
CHECK_EQ(param.stride.ndim(), param.kernel.ndim())
<< "stride and kernel should have the same length";
CHECK_EQ(param.pad.ndim(), param.kernel.ndim())
<< "pad and kernel should have the same length";
attrs->parsed = std::move(param);
}

Expand Down Expand Up @@ -98,28 +97,37 @@ static bool PoolingShape(const nnvm::NodeAttrs &attrs,
<< "Pooling: Input data should be 3D in (batch, channel, x)"
<< " Or 4D in (batch, channel, y, x) "
<< " Or 5D in (batch, channel, d, y, x)";
CHECK_LE(dshape.ndim(), 5U)
<< "Pooling: Input data should be 3D in (batch, channel, x)"
<< " Or 4D in (batch, channel, y, x) "
<< " Or 5D in (batch, channel, d, y, x)";
TShape oshape = dshape;
if (dshape.ndim() == 0) return false;
if (param.kernel.ndim() == 1) {
if (param.global_pool) {
for (size_t i{2}; i < dshape.ndim(); i++)
oshape[i] = 1;
out_shape->clear();
out_shape->push_back(oshape); // save output shape
#if MXNET_USE_MKLDNN == 1
if (MKLDNNRequireWorkspace(param) && SupportMKLDNNPooling(param))
out_shape->push_back(oshape); // for workspace
#endif
} else if (param.kernel.ndim() == 1) {
CHECK_EQ(dshape.ndim(), 3U)
<< "Pooling: Input data should be 3D in (batch, channel, x)";
if (param.global_pool) {
oshape[2] = 1;
CHECK(param.kernel[0] <= dshape[2] + 2 * param.pad[0])
<< "kernel size (" << param.kernel[0] << ") exceeds input ("
<< dshape[2] << " padded to " << (dshape[2] + 2 * param.pad[0])
<< ")";
if (param.pooling_convention == pool_enum::kValid) {
oshape[2] = 1 +
(dshape[2] + 2 * param.pad[0] - param.kernel[0]) /
param.stride[0];
} else {
CHECK(param.kernel[0] <= dshape[2] + 2 * param.pad[0])
<< "kernel size (" << param.kernel[0] << ") exceeds input ("
<< dshape[2] << " padded to " << (dshape[2] + 2 * param.pad[0])
<< ")";
if (param.pooling_convention == pool_enum::kValid) {
oshape[2] = 1 +
(dshape[2] + 2 * param.pad[0] - param.kernel[0]) /
param.stride[0];
} else {
oshape[2] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[2] + 2 * param.pad[0] -
param.kernel[0]) /
param.stride[0]));
}
oshape[2] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[2] + 2 * param.pad[0] -
param.kernel[0]) /
param.stride[0]));
}
out_shape->clear();
out_shape->push_back(oshape); // save output shape
Expand All @@ -130,35 +138,30 @@ static bool PoolingShape(const nnvm::NodeAttrs &attrs,
} else if (param.kernel.ndim() == 2) {
CHECK_EQ(dshape.ndim(), 4U)
<< "Pooling: Input data should be 4D in (batch, channel, y, x)";
if (param.global_pool) {
oshape[2] = 1;
oshape[3] = 1;
CHECK(param.kernel[0] <= dshape[2] + 2 * param.pad[0])
<< "kernel size (" << param.kernel[0] << ") exceeds input ("
<< dshape[2] << " padded to " << (dshape[2] + 2 * param.pad[0])
<< ")";
CHECK(param.kernel[1] <= dshape[3] + 2 * param.pad[1])
<< "kernel size (" << param.kernel[1] << ") exceeds input ("
<< dshape[3] << " padded to " << (dshape[3] + 2 * param.pad[1])
<< ")";
if (param.pooling_convention == pool_enum::kValid) {
oshape[2] = 1 +
(dshape[2] + 2 * param.pad[0] - param.kernel[0]) /
param.stride[0];
oshape[3] = 1 +
(dshape[3] + 2 * param.pad[1] - param.kernel[1]) /
param.stride[1];
} else {
CHECK(param.kernel[0] <= dshape[2] + 2 * param.pad[0])
<< "kernel size (" << param.kernel[0] << ") exceeds input ("
<< dshape[2] << " padded to " << (dshape[2] + 2 * param.pad[0])
<< ")";
CHECK(param.kernel[1] <= dshape[3] + 2 * param.pad[1])
<< "kernel size (" << param.kernel[1] << ") exceeds input ("
<< dshape[3] << " padded to " << (dshape[3] + 2 * param.pad[1])
<< ")";
if (param.pooling_convention == pool_enum::kValid) {
oshape[2] = 1 +
(dshape[2] + 2 * param.pad[0] - param.kernel[0]) /
param.stride[0];
oshape[3] = 1 +
(dshape[3] + 2 * param.pad[1] - param.kernel[1]) /
param.stride[1];
} else {
oshape[2] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[2] + 2 * param.pad[0] -
param.kernel[0]) /
param.stride[0]));
oshape[3] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[3] + 2 * param.pad[1] -
param.kernel[1]) /
param.stride[1]));
}
oshape[2] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[2] + 2 * param.pad[0] -
param.kernel[0]) /
param.stride[0]));
oshape[3] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[3] + 2 * param.pad[1] -
param.kernel[1]) /
param.stride[1]));
}
out_shape->clear();
out_shape->push_back(oshape); // save output shape
Expand All @@ -175,35 +178,29 @@ static bool PoolingShape(const nnvm::NodeAttrs &attrs,
<< "kernel size exceeds input";
CHECK_LE(param.kernel[2], dshape[4] + 2 * param.pad[2])
<< "kernel size exceeds input";
if (param.global_pool) {
oshape[2] = 1;
oshape[3] = 1;
oshape[4] = 1;
if (param.pooling_convention == pool_enum::kValid) {
oshape[2] = 1 +
(dshape[2] + 2 * param.pad[0] - param.kernel[0]) /
param.stride[0];
oshape[3] = 1 +
(dshape[3] + 2 * param.pad[1] - param.kernel[1]) /
param.stride[1];
oshape[4] = 1 +
(dshape[4] + 2 * param.pad[2] - param.kernel[2]) /
param.stride[2];
} else {
if (param.pooling_convention == pool_enum::kValid) {
oshape[2] = 1 +
(dshape[2] + 2 * param.pad[0] - param.kernel[0]) /
param.stride[0];
oshape[3] = 1 +
(dshape[3] + 2 * param.pad[1] - param.kernel[1]) /
param.stride[1];
oshape[4] = 1 +
(dshape[4] + 2 * param.pad[2] - param.kernel[2]) /
param.stride[2];
} else {
oshape[2] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[2] + 2 * param.pad[0] -
param.kernel[0]) /
param.stride[0]));
oshape[3] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[3] + 2 * param.pad[1] -
param.kernel[1]) /
param.stride[1]));
oshape[4] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[4] + 2 * param.pad[2] -
param.kernel[2]) /
param.stride[2]));
}
oshape[2] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[2] + 2 * param.pad[0] -
param.kernel[0]) /
param.stride[0]));
oshape[3] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[3] + 2 * param.pad[1] -
param.kernel[1]) /
param.stride[1]));
oshape[4] = 1 + static_cast<int>(ceil(
static_cast<float>(dshape[4] + 2 * param.pad[2] -
param.kernel[2]) /
param.stride[2]));
}

out_shape->clear();
Expand Down
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