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[Op] Do not override specified layout in pooling (2nd PR) #9328

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merged 7 commits into from
Oct 21, 2021
Merged

[Op] Do not override specified layout in pooling (2nd PR) #9328

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b2e30b3
[Op] Do not override specified layout in pooling (2nd PR)
Oct 19, 2021
787394f
Merge branch 'apache:main' into op-pooling
ccjoechou Oct 20, 2021
8a75869
[Op] Do not override specified layout in pooling (2nd PR)
Oct 19, 2021
30bf278
[Op] Do not override specified layout in pooling (2nd PR)
Oct 19, 2021
fc9c53b
Merge branch 'apache:main' into op-pooling
ccjoechou Oct 21, 2021
c099515
[Op] Do not override specified layout in pooling (2nd PR)
Oct 19, 2021
c4a74e2
Merge branch 'apache:main' into op-pooling
ccjoechou Oct 21, 2021
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78 changes: 78 additions & 0 deletions include/tvm/relay/attrs/nn.h
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Original file line number Diff line number Diff line change
Expand Up @@ -686,6 +686,7 @@ struct MaxPool2DAttrs : public tvm::AttrsNode<MaxPool2DAttrs> {
Array<IndexExpr> padding;
Array<IndexExpr> dilation;
tvm::String layout;
tvm::String out_layout;
bool ceil_mode;

TVM_DECLARE_ATTRS(MaxPool2DAttrs, "relay.attrs.MaxPool2DAttrs") {
Expand All @@ -709,6 +710,13 @@ struct MaxPool2DAttrs : public tvm::AttrsNode<MaxPool2DAttrs> {
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCHW', 'NHWC', etc."
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(ceil_mode).set_default(false).describe(
"When true, will use ceil instead of floor to compute the output shape.");
}
Expand All @@ -721,6 +729,7 @@ struct AvgPool2DAttrs : public tvm::AttrsNode<AvgPool2DAttrs> {
Array<IndexExpr> padding;
Array<IndexExpr> dilation;
tvm::String layout;
tvm::String out_layout;
bool ceil_mode;
bool count_include_pad;

Expand All @@ -745,6 +754,13 @@ struct AvgPool2DAttrs : public tvm::AttrsNode<AvgPool2DAttrs> {
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCHW', 'NHWC', etc."
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(ceil_mode).set_default(false).describe(
"When true, will use ceil instead of floor to compute the output shape.");
TVM_ATTR_FIELD(count_include_pad)
Expand All @@ -756,20 +772,29 @@ struct AvgPool2DAttrs : public tvm::AttrsNode<AvgPool2DAttrs> {
/*! \brief Attributes for global pool operator */
struct GlobalPool2DAttrs : public tvm::AttrsNode<GlobalPool2DAttrs> {
tvm::String layout;
tvm::String out_layout;

TVM_DECLARE_ATTRS(GlobalPool2DAttrs, "relay.attrs.GlobalPool2DAttrs") {
TVM_ATTR_FIELD(layout).set_default("NCHW").describe(
"Dimension ordering of input data. Can be 'NCHW', 'NHWC', etc."
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCHW', 'NHWC', etc."
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
}
};

/*! \brief Attributes for 1d adaptive pool operator */
struct AdaptivePool1DAttrs : public tvm::AttrsNode<AdaptivePool1DAttrs> {
Array<IndexExpr> output_size;
std::string layout;
tvm::String out_layout;

TVM_DECLARE_ATTRS(AdaptivePool1DAttrs, "relay.attrs.AdaptivePool1DAttrs") {
TVM_ATTR_FIELD(output_size).set_default(Array<IndexExpr>({})).describe("Output width.");
Expand All @@ -778,13 +803,21 @@ struct AdaptivePool1DAttrs : public tvm::AttrsNode<AdaptivePool1DAttrs> {
"'N', 'C', 'W' stands for batch, channel, and width"
"dimensions respectively. Pooling is applied on the"
"'W' dimension.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCW', 'NWC', etc."
"'N', 'C', 'W' stands for batch, channel, and width"
"dimensions respectively. Pooling is applied on the"
"'W' dimension.");
}
};

/*! \brief Attributes for 2d adaptive pool operator */
struct AdaptivePool2DAttrs : public tvm::AttrsNode<AdaptivePool2DAttrs> {
Array<IndexExpr> output_size;
std::string layout;
tvm::String out_layout;

TVM_DECLARE_ATTRS(AdaptivePool2DAttrs, "relay.attrs.AdaptivePool2DAttrs") {
TVM_ATTR_FIELD(output_size)
Expand All @@ -795,13 +828,21 @@ struct AdaptivePool2DAttrs : public tvm::AttrsNode<AdaptivePool2DAttrs> {
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCHW', 'NHWC', etc."
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
"dimensions respectively. Pooling is applied on the 'H' and"
"'W' dimensions.");
}
};

/*! \brief Attributes for 3d adaptive pool operator */
struct AdaptivePool3DAttrs : public tvm::AttrsNode<AdaptivePool3DAttrs> {
Array<IndexExpr> output_size;
std::string layout;
tvm::String out_layout;

TVM_DECLARE_ATTRS(AdaptivePool3DAttrs, "relay.attrs.AdaptivePool3DAttrs") {
TVM_ATTR_FIELD(output_size)
Expand All @@ -812,6 +853,13 @@ struct AdaptivePool3DAttrs : public tvm::AttrsNode<AdaptivePool3DAttrs> {
"'N', 'C', 'D', 'H', 'W' stands for batch, channel, depth, height, and width"
"dimensions respectively. Pooling is applied on 'D', 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCDHW', 'NDHWC', etc."
"'N', 'C', 'D', 'H', 'W' stands for batch, channel, depth, height, and width"
"dimensions respectively. Pooling is applied on 'D', 'H' and"
"'W' dimensions.");
}
};

Expand All @@ -822,6 +870,7 @@ struct MaxPool1DAttrs : public tvm::AttrsNode<MaxPool1DAttrs> {
Array<IndexExpr> dilation;
Array<IndexExpr> padding;
std::string layout;
tvm::String out_layout;
bool ceil_mode;

TVM_DECLARE_ATTRS(MaxPool1DAttrs, "relay.attrs.MaxPool1DAttrs") {
Expand All @@ -844,6 +893,12 @@ struct MaxPool1DAttrs : public tvm::AttrsNode<MaxPool1DAttrs> {
"Dimension ordering of input data. Can be 'NCW', 'NWC', etc."
"'N', 'C', 'W' stands for batch, channel, and width"
"dimensions respectively. Pooling is applied on the 'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCW', 'NWC', etc."
"'N', 'C', 'W' stands for batch, channel, and width"
"dimensions respectively. Pooling is applied on the 'W' dimensions.");
TVM_ATTR_FIELD(ceil_mode).set_default(false).describe(
"When true, will use ceil instead of floor to compute the output shape.");
}
Expand All @@ -856,6 +911,7 @@ struct AvgPool1DAttrs : public tvm::AttrsNode<AvgPool1DAttrs> {
Array<IndexExpr> dilation;
Array<IndexExpr> padding;
std::string layout;
tvm::String out_layout;
bool ceil_mode;
bool count_include_pad;

Expand All @@ -879,6 +935,12 @@ struct AvgPool1DAttrs : public tvm::AttrsNode<AvgPool1DAttrs> {
"Dimension ordering of input data. Can be 'NCW', 'NHC', etc."
"'N', 'C', 'W' stands for batch, channel, and width"
"dimensions respectively. Pooling is applied on the 'W' dimension.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCW', 'NHC', etc."
"'N', 'C', 'W' stands for batch, channel, and width"
"dimensions respectively. Pooling is applied on the 'W' dimension.");
TVM_ATTR_FIELD(ceil_mode).set_default(false).describe(
"When true, will use ceil instead of floor to compute the output shape.");
TVM_ATTR_FIELD(count_include_pad)
Expand All @@ -894,6 +956,7 @@ struct MaxPool3DAttrs : public tvm::AttrsNode<MaxPool3DAttrs> {
Array<IndexExpr> dilation;
Array<IndexExpr> padding;
std::string layout;
tvm::String out_layout;
bool ceil_mode;

TVM_DECLARE_ATTRS(MaxPool3DAttrs, "relay.attrs.MaxPool3DAttrs") {
Expand All @@ -917,6 +980,13 @@ struct MaxPool3DAttrs : public tvm::AttrsNode<MaxPool3DAttrs> {
"'N', 'C', 'D', 'H', 'W' stands for batch, channel, depth, height, and width"
"dimensions respectively. Pooling is applied on the 'D', 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCDHW', 'NDHWC', etc."
"'N', 'C', 'D', 'H', 'W' stands for batch, channel, depth, height, and width"
"dimensions respectively. Pooling is applied on the 'D', 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(ceil_mode).set_default(false).describe(
"When true, will use ceil instead of floor to compute the output shape.");
}
Expand All @@ -929,6 +999,7 @@ struct AvgPool3DAttrs : public tvm::AttrsNode<AvgPool3DAttrs> {
Array<IndexExpr> dilation;
Array<IndexExpr> padding;
std::string layout;
tvm::String out_layout;
bool ceil_mode;
bool count_include_pad;

Expand All @@ -953,6 +1024,13 @@ struct AvgPool3DAttrs : public tvm::AttrsNode<AvgPool3DAttrs> {
"'N', 'C', 'D', 'H', 'W' stands for batch, channel, depth, height, and width"
"dimensions respectively. Pooling is applied on the 'D', 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(out_layout)
.set_default("")
.describe(
"Dimension ordering of output data. Can be 'NCDHW', 'NDHWC', etc."
"'N', 'C', 'D', 'H', 'W' stands for batch, channel, depth, height, and width"
"dimensions respectively. Pooling is applied on the 'D', 'H' and"
"'W' dimensions.");
TVM_ATTR_FIELD(ceil_mode).set_default(false).describe(
"When true, will use ceil instead of floor to compute the output shape.");
TVM_ATTR_FIELD(count_include_pad)
Expand Down
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