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[TOPI] Rename output tensors for better readability (apache#3006)
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@merrymercy
merrymercy authored and Wei Chen committed May 13, 2019
1 parent 1f537a6 commit 5b903ea
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Showing 7 changed files with 76 additions and 74 deletions.
54 changes: 27 additions & 27 deletions topi/include/topi/broadcast.h
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@ namespace topi {
*/
inline tvm::Tensor broadcast_to(const tvm::Tensor& t,
const tvm::Array<tvm::Expr>& output_shape,
std::string name = "tensor",
std::string name = "T_broadcast_to",
std::string tag = kBroadcast) {
CHECK_GE(output_shape.size(), t->shape.size())
<< "Not a broadcast, output dimensionality smaller than input.\noutput: "
Expand All @@ -66,35 +66,35 @@ inline tvm::Tensor broadcast_to(const tvm::Tensor& t,
tag);
}

#define TOPI_DEFINE_BCAST_OP(Name, ComputeRule) \
inline tvm::Expr Name(const tvm::Expr& a, \
const tvm::Expr& b) { \
ComputeRule; \
} \
inline tvm::Tensor Name(const tvm::Tensor& A, \
const tvm::Tensor& B, \
std::string name = "tensor", \
std::string tag = kBroadcast) { \
auto l = [](tvm::Expr a, tvm::Expr b) { ComputeRule; }; \
return detail::WithBroadcast(l, A, B, name, tag); \
} \
inline tvm::Tensor Name(const tvm::Tensor& A, \
const tvm::Expr& B, \
std::string name = "tensor", \
std::string tag = kElementWise) { \
#define TOPI_DEFINE_BCAST_OP(Name, ComputeRule) \
inline tvm::Expr Name(const tvm::Expr& a, \
const tvm::Expr& b) { \
ComputeRule; \
} \
inline tvm::Tensor Name(const tvm::Tensor& A, \
const tvm::Tensor& B, \
std::string name = "T_" #Name, \
std::string tag = kBroadcast) { \
auto l = [](tvm::Expr a, tvm::Expr b) { ComputeRule; }; \
return detail::WithBroadcast(l, A, B, name, tag); \
} \
inline tvm::Tensor Name(const tvm::Tensor& A, \
const tvm::Expr& B, \
std::string name = "T_" #Name, \
std::string tag = kElementWise) { \
auto l = [](tvm::Expr a, tvm::Expr b) { ComputeRule; }; \
return compute(A->shape, [&](const ::tvm::Array<::tvm::Var>& i) { \
return l(A(i), B); \
}, name, tag); \
} \
inline tvm::Tensor Name(const tvm::Expr& A, \
const tvm::Tensor& B, \
std::string name = "tensor", \
std::string tag = kElementWise) { \
auto l = [&](tvm::Expr a, tvm::Expr b) { ComputeRule; }; \
return l(A(i), B); \
}, name, tag); \
} \
inline tvm::Tensor Name(const tvm::Expr& A, \
const tvm::Tensor& B, \
std::string name = "T_" #Name, \
std::string tag = kElementWise) { \
auto l = [&](tvm::Expr a, tvm::Expr b) { ComputeRule; }; \
return compute(B->shape, [&](const ::tvm::Array<::tvm::Var>& i) { \
return l(A, B(i)); \
}, name, tag); \
return l(A, B(i)); \
}, name, tag); \
}


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20 changes: 10 additions & 10 deletions topi/include/topi/elemwise.h
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ using namespace tvm;
// Unary intrinsic operators
#define TOPI_DECLARE_UNARY_OP(OpName) \
inline Tensor OpName(const Tensor& x, \
std::string name = "tensor", \
std::string name = "T_" #OpName, \
std::string tag = kElementWise) { \
return compute(x->shape, [&](const Array<Var>& i) { \
return ::tvm::OpName(x(i)); \
Expand Down Expand Up @@ -66,7 +66,7 @@ TOPI_DECLARE_UNARY_OP(abs);
* \return A Tensor whose op member is the identity operation
*/
inline Tensor identity(const Tensor& x,
std::string name = "tensor",
std::string name = "T_identity",
std::string tag = kElementWise) {
return compute(x->shape, [&](const Array<Var>& i) {
return x(i);
Expand All @@ -83,7 +83,7 @@ inline Tensor identity(const Tensor& x,
* \return A Tensor whose op member is the negation operation
*/
inline Tensor negative(const Tensor& x,
std::string name = "tensor",
std::string name = "T_negative",
std::string tag = kElementWise) {
return compute(x->shape, [&](const Array<Var>& i) {
return -x(i);
Expand All @@ -100,7 +100,7 @@ inline Tensor negative(const Tensor& x,
* \return A Tensor whose op member is the logical NOT operation
*/
inline Tensor logical_not(const Tensor& x,
std::string name = "tensor",
std::string name = "T_logical_not",
std::string tag = kElementWise) {
return compute(x->shape, [&](const Array<Var>& i) {
return !x(i);
Expand All @@ -117,7 +117,7 @@ inline Tensor logical_not(const Tensor& x,
* \return A Tensor whose op member is the sign
*/
inline Tensor sign(const Tensor& x,
std::string name = "tensor",
std::string name = "T_sign",
std::string tag = kElementWise) {
return compute(x->shape, [&](const Array<Var>& i) {
Expr zero = make_zero(x->dtype);
Expand All @@ -144,7 +144,7 @@ inline Tensor sign(const Tensor& x,
inline Tensor clip(const Tensor& x,
const Expr& a_min,
const Expr& a_max,
std::string name = "tensor",
std::string name = "T_clip",
std::string tag = kElementWise) {
return compute(x->shape, [&](const Array<Var>& i) {
auto min_val = tvm::cast(x->dtype, a_min);
Expand All @@ -167,7 +167,7 @@ inline Tensor clip(const Tensor& x,
*/
inline Tensor cast(const Tensor& x,
Type type,
std::string name = "tensor",
std::string name = "T_cast",
std::string tag = kElementWise) {
return compute(x->shape, [&](const Array<Var>& i) {
auto expr = x(i);
Expand All @@ -193,7 +193,7 @@ inline Tensor cast(const Tensor& x,
* \return A Tensor whose op member is the sum operation
*/
inline Tensor elemwise_sum(const Array<Tensor>& xs,
std::string name = "tensor",
std::string name = "T_elemwise_sum",
std::string tag = kElementWise) {
CHECK_GT(xs.size(), 0) << "elemwise sum must have at least one input tensor.";
return compute(xs[0]->shape, [&](const Array<Var>& i) {
Expand All @@ -219,7 +219,7 @@ inline Tensor elemwise_sum(const Array<Tensor>& xs,
inline Tensor full(const Array<Expr>& shape,
Type dtype,
const Expr fill_value,
std::string name = "tensor",
std::string name = "T_full",
std::string tag = kElementWise) {
Expr ev = cast(dtype, fill_value);
if (!ev.defined()) {
Expand All @@ -243,7 +243,7 @@ inline Tensor full(const Array<Expr>& shape,
*/
inline Tensor full_like(const Tensor& x,
const Expr fill_value,
std::string name = "tensor",
std::string name = "T_full_like",
std::string tag = kElementWise) {
Expr ev = cast(x->dtype, fill_value);
return compute(x->shape, [&](const Array<Var>& i) {
Expand Down
18 changes: 9 additions & 9 deletions topi/include/topi/nn.h
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Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@ tvm::Expr Map(const tvm::Array<tvm::Expr>& exprs, T op) {
template <typename T>
inline tvm::Tensor relu(const tvm::Tensor& t,
T threshold = static_cast<T>(0),
std::string name = "tensor",
std::string name = "T_relu",
std::string tag = kElementWise) {
return tvm::compute(
t->shape,
Expand All @@ -87,7 +87,7 @@ inline tvm::Tensor relu(const tvm::Tensor& t,
*/
inline tvm::Tensor leaky_relu(const tvm::Tensor& t,
double alpha = 0.1,
std::string name = "tensor",
std::string name = "T_leaky_relu",
std::string tag = kElementWise) {
return tvm::compute(
t->shape,
Expand All @@ -114,7 +114,7 @@ inline tvm::Tensor leaky_relu(const tvm::Tensor& t,
inline tvm::Tensor prelu(const tvm::Tensor &x,
const tvm::Tensor &slope,
const int axis = 1,
std::string name = "tensor",
std::string name = "T_prelu",
std::string tag = kBroadcast) {
CHECK((size_t)axis < x->shape.size()) <<
"Wrong axis (" << axis << ")value. ";
Expand Down Expand Up @@ -171,7 +171,7 @@ inline tvm::Tensor pad(const tvm::Tensor& t,
const tvm::Array<tvm::Expr>& pad_before,
tvm::Array<tvm::Expr> pad_after = tvm::Array<tvm::Expr>(),
Expr pad_value = Expr(),
std::string name = "tensor",
std::string name = "T_pad",
std::string tag = kElementWise) {
if (pad_after.size() < pad_before.size()) {
for (size_t i = pad_after.size(); i < pad_before.size(); ++i) {
Expand Down Expand Up @@ -247,7 +247,7 @@ inline tvm::Tensor conv2d_nchw(const tvm::Tensor& I,
int pad_w = 0,
int stride_h = 1,
int stride_w = 1,
std::string name = "tensor",
std::string name = "T_conv2d_nchw",
std::string tag = kConv2dNCHW) {
CHECK_EQ(4, I->shape.size());
CHECK_EQ(4, W->shape.size());
Expand Down Expand Up @@ -298,7 +298,7 @@ inline tvm::Tensor conv2d_hwcn(const tvm::Tensor& I,
int pad_w = 0,
int stride_h = 1,
int stride_w = 1,
std::string name = "tensor",
std::string name = "T_conv2d_hwcn",
std::string tag = kConv2dHWCN) {
CHECK_EQ(4, I->shape.size());
CHECK_EQ(4, W->shape.size());
Expand Down Expand Up @@ -349,7 +349,7 @@ inline tvm::Tensor depthwise_conv2d_nchw(const tvm::Tensor& I,
int pad_w = 0,
int stride_h = 1,
int stride_w = 1,
std::string name = "tensor",
std::string name = "T_depthwise_conv2d_nchw",
std::string tag = kDepthwiseConv2dNCHW) {
CHECK_EQ(4, I->shape.size());
CHECK_EQ(4, W->shape.size());
Expand Down Expand Up @@ -382,7 +382,7 @@ inline tvm::Tensor depthwise_conv2d_nhwc(const tvm::Tensor& I,
int pad_w = 0,
int stride_h = 1,
int stride_w = 1,
std::string name = "tensor",
std::string name = "T_depthwise_conv2d_nhwc",
std::string tag = kDepthwiseConv2dNHWC) {
CHECK_EQ(4, I->shape.size());
CHECK_EQ(4, W->shape.size());
Expand Down Expand Up @@ -435,7 +435,7 @@ inline tvm::Tensor group_conv2d_ngchw(const tvm::Tensor& I,
int pad_w = 0,
int stride_h = 1,
int stride_w = 1,
std::string name = "tensor",
std::string name = "T_group_conv2d_ngchw",
std::string tag = kGroupConv2d) {
CHECK_EQ(5, I->shape.size());
CHECK_EQ(5, W->shape.size());
Expand Down
4 changes: 2 additions & 2 deletions topi/include/topi/nn/pooling.h
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Original file line number Diff line number Diff line change
Expand Up @@ -272,8 +272,8 @@ inline Tensor global_pool(const Tensor& x,
auto height = x->shape[height_axis];
auto width = x->shape[width_axis];

auto dheight = tvm::reduce_axis(Range(0, height));
auto dwidth = tvm::reduce_axis(Range(0, width));
auto dheight = tvm::reduce_axis(Range(0, height), "rv1");
auto dwidth = tvm::reduce_axis(Range(0, width), "rv2");

if (pool_type == kMaxPool) {
return tvm::compute(out_shape,
Expand Down
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