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Replace phi::errors to ::common::errors in cinn [fluid_ops] part2 #67114

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Merged
merged 3 commits into from
Aug 9, 2024
Merged

Replace phi::errors to ::common::errors in cinn [fluid_ops] part2 #67114

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f017db6
Fix
co63oc Aug 7, 2024
4282664
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co63oc Aug 7, 2024
9fbaf87
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co63oc Aug 8, 2024
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118 changes: 59 additions & 59 deletions paddle/cinn/hlir/op/broadcast.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -74,37 +74,37 @@ std::shared_ptr<OpStrategy> StrategyForBroadcast(
PADDLE_ENFORCE_NE(
args.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of %s compute is empty! Please check.",
op_name));
CINNValuePack pack_args = args[0];
PADDLE_ENFORCE_GE(pack_args.size(),
2U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"At least 2 input tensors for %s compute, but got %d",
op_name,
pack_args.size()));
PADDLE_ENFORCE_GE(pack_args.size(),
3U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"At least 3 input tensors for %s compute, but got %d",
op_name,
pack_args.size()));
PADDLE_ENFORCE_EQ(
pack_args[2].is_string(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required pack_args[2] must be a string. Please check."));
std::string tensor_name = pack_args[2].operator std::string();
Expr A_expr = pack_args[0];
Expr B_expr = pack_args[1];
PADDLE_ENFORCE_NOT_NULL(
A_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
PADDLE_ENFORCE_NOT_NULL(
B_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
ir::Tensor A = A_expr.as_tensor_ref();
ir::Tensor B = B_expr.as_tensor_ref();
Expand Down Expand Up @@ -143,37 +143,37 @@ std::shared_ptr<OpStrategy> StrategyForBroadcastSymbolic(
PADDLE_ENFORCE_NE(
args.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of %s compute is empty! Please check.",
op_name));
CINNValuePack pack_args = args[0];
PADDLE_ENFORCE_GE(pack_args.size(),
2U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"At least 2 input tensors for %s compute, but got %d",
op_name,
pack_args.size()));
PADDLE_ENFORCE_GE(pack_args.size(),
3U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"At least 3 input tensors for %s compute, but got %d",
op_name,
pack_args.size()));
PADDLE_ENFORCE_EQ(
pack_args[2].is_string(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required pack_args[2] must be a string. Please check."));
std::string tensor_name = pack_args[2].operator std::string();
Expr A_expr = pack_args[0];
Expr B_expr = pack_args[1];
PADDLE_ENFORCE_NOT_NULL(
A_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
PADDLE_ENFORCE_NOT_NULL(
B_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
ir::Tensor A = A_expr.as_tensor_ref();
ir::Tensor B = B_expr.as_tensor_ref();
Expand Down Expand Up @@ -206,14 +206,14 @@ std::shared_ptr<OpStrategy> StrategyForBroadcastTo(
PADDLE_ENFORCE_GE(
attrs.attr_store.count("out_shape"),
1,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The attrs.attr_store doesn't have the attribute of 'out_shape'."));
out_shape = absl::get<std::vector<int>>(attrs.attr_store.at("out_shape"));
PADDLE_ENFORCE_GE(
attrs.attr_store.count("broadcast_axes"),
1,
phi::errors::InvalidArgument("The attrs.attr_store doesn't have the "
"attribute of 'broadcast_axes'."));
::common::errors::InvalidArgument("The attrs.attr_store doesn't have the "
"attribute of 'broadcast_axes'."));
broadcast_axes =
absl::get<std::vector<int>>(attrs.attr_store.at("broadcast_axes"));
VLOG(3) << "broadcast out shape: " << utils::Join(out_shape, ", ");
Expand All @@ -224,30 +224,30 @@ std::shared_ptr<OpStrategy> StrategyForBroadcastTo(
PADDLE_ENFORCE_NE(
args.empty(),
true,
phi::errors::InvalidArgument("The input argument of broadcast_to "
"compute is empty! Please check."));
::common::errors::InvalidArgument("The input argument of broadcast_to "
"compute is empty! Please check."));
CINNValuePack pack_args = args[0];
PADDLE_ENFORCE_NE(
pack_args.empty(),
true,
phi::errors::InvalidArgument("The input tensors of broadcast_to "
"compute is empty! Please check."));
::common::errors::InvalidArgument("The input tensors of broadcast_to "
"compute is empty! Please check."));
PADDLE_ENFORCE_GE(
pack_args.size(),
2U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required at least 2 input tensors, but got %d", pack_args.size()));
PADDLE_ENFORCE_EQ(
pack_args[1].is_string(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required pack_args[1] must be a string. Please check."));
std::string tensor_name = pack_args[1].operator std::string();

Expr A_expr = pack_args[0];
PADDLE_ENFORCE_NOT_NULL(
A_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
ir::Tensor A = A_expr.as_tensor_ref();
auto out = pe::BroadcastTo(A, out_shape, broadcast_axes, tensor_name);
Expand All @@ -271,7 +271,7 @@ std::shared_ptr<OpStrategy> StrategyForBroadcastToSymbolic(
const Target &target) {
PADDLE_ENFORCE_EQ(output_shapes.size(),
1,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The size of output_shapes must be 1, but got %d.",
output_shapes.size()));
std::vector<ir::Expr> out_shape(output_shapes[0].size());
Expand All @@ -281,42 +281,42 @@ std::shared_ptr<OpStrategy> StrategyForBroadcastToSymbolic(
[](const ir::Dim &dim) { return dim->dim_expr; });
VLOG(3) << "broadcast out shape: " << utils::Join(out_shape, ", ");

framework::CINNCompute broadcast_to_compute(
[=](lang::Args args, lang::RetValue *ret) {
PADDLE_ENFORCE_NE(
args.empty(),
true,
phi::errors::InvalidArgument("The input argument of broadcast_to "
"compute is empty! Please check."));
CINNValuePack pack_args = args[0];
PADDLE_ENFORCE_NE(
pack_args.empty(),
true,
phi::errors::InvalidArgument("The input tensors of broadcast_to "
"compute is empty! Please check."));
std::string tensor_name = [&] {
if (pack_args.size() == 2) {
return pack_args[1].operator std::string();
} else {
PADDLE_ENFORCE_EQ(pack_args.size(),
3,
::common::errors::InvalidArgument(
"The number of input tensors is wrong. "
"The expected inputs is 3, but now is %d.",
pack_args.size()));
return pack_args[2].operator std::string();
}
}();

Expr A_expr = pack_args[0];
PADDLE_ENFORCE_NOT_NULL(
A_expr.as_tensor(),
phi::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
ir::Tensor A = A_expr.as_tensor_ref();
auto out = pe::BroadcastTo(A, out_shape, tensor_name);
*ret = CINNValuePack{{CINNValue(out)}};
});
framework::CINNCompute broadcast_to_compute([=](lang::Args args,
lang::RetValue *ret) {
PADDLE_ENFORCE_NE(
args.empty(),
true,
::common::errors::InvalidArgument("The input argument of broadcast_to "
"compute is empty! Please check."));
CINNValuePack pack_args = args[0];
PADDLE_ENFORCE_NE(
pack_args.empty(),
true,
::common::errors::InvalidArgument("The input tensors of broadcast_to "
"compute is empty! Please check."));
std::string tensor_name = [&] {
if (pack_args.size() == 2) {
return pack_args[1].operator std::string();
} else {
PADDLE_ENFORCE_EQ(pack_args.size(),
3,
::common::errors::InvalidArgument(
"The number of input tensors is wrong. "
"The expected inputs is 3, but now is %d.",
pack_args.size()));
return pack_args[2].operator std::string();
}
}();

Expr A_expr = pack_args[0];
PADDLE_ENFORCE_NOT_NULL(
A_expr.as_tensor(),
::common::errors::InvalidArgument(
"Required Input must be a tensor. Please check."));
ir::Tensor A = A_expr.as_tensor_ref();
auto out = pe::BroadcastTo(A, out_shape, tensor_name);
*ret = CINNValuePack{{CINNValue(out)}};
});

auto strategy = std::make_shared<framework::OpStrategy>();
strategy->AddImpl(
Expand Down
22 changes: 11 additions & 11 deletions paddle/cinn/hlir/op/contrib/argmax.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ std::vector<ir::Tensor> Argmax(const Tensor &in_tensor,
PADDLE_ENFORCE_GT(
ndim,
0,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The dimension of input tensor must be greater than 0."));

int pos_axis = axis;
Expand All @@ -61,18 +61,18 @@ std::vector<ir::Tensor> Argmax(const Tensor &in_tensor,
PADDLE_ENFORCE_LT(
pos_axis,
ndim,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The axis must be less than the dimension of input tensor."));
PADDLE_ENFORCE_GE(pos_axis,
0,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The axis must be greater than or equal to 0."));

std::vector<Expr> output_shape;
for (int i = 0; i < shape.size(); ++i) {
PADDLE_ENFORCE_EQ(shape[i].is_constant(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Input tensor's shape should be constant value."));
if (pos_axis == i) {
if (keep_dims) {
Expand Down Expand Up @@ -126,28 +126,28 @@ std::shared_ptr<framework::OpStrategy> StrategyForArgmax(
PADDLE_ENFORCE_EQ(
!args.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmax compute is empty! Please check."));
cinn::common::CINNValuePack pack_args = args[0];
std::string tensor_name = UniqName("Argmax_out");
PADDLE_ENFORCE_GE(pack_args.size(),
1U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"There should be 1 input args for argmax compute"));
Expr in_expr = pack_args[0];
PADDLE_ENFORCE_NOT_NULL(
in_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmax compute is null."));
Tensor in_tensor = in_expr.as_tensor_ref();
PADDLE_ENFORCE_EQ(pack_args.size(),
2U,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmax compute must be 2."));
PADDLE_ENFORCE_EQ(
pack_args[1].is_string(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmax compute must be string."));
tensor_name = pack_args[1].operator std::string();
std::vector<ir::Tensor> out_tensor =
Expand All @@ -164,7 +164,7 @@ std::shared_ptr<framework::OpStrategy> StrategyForArgmax(
PADDLE_ENFORCE_EQ(
!args.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmax_schedule is empty! Please check."));
cinn::common::CINNValuePack arg_pack = args[0];
std::vector<Expr> vec_ast;
Expand All @@ -177,7 +177,7 @@ std::shared_ptr<framework::OpStrategy> StrategyForArgmax(
PADDLE_ENFORCE_EQ(
!vec_ast.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmax_schedule is empty! Please check."));
ir::ModuleExpr mod_expr(vec_ast);
ir::IRSchedule ir_sch(mod_expr);
Expand Down
14 changes: 7 additions & 7 deletions paddle/cinn/hlir/op/contrib/argmin.cc
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ std::vector<Tensor> Argmin(const Tensor &in_tensor,
PADDLE_ENFORCE_GT(
ndim,
0,
phi::errors::InvalidArgument("tensor's dim must be more than 0"));
::common::errors::InvalidArgument("tensor's dim must be more than 0"));

int pos_axis = axis;
if (axis < 0) {
Expand All @@ -64,7 +64,7 @@ std::vector<Tensor> Argmin(const Tensor &in_tensor,
for (int i = 0; i < shape.size(); ++i) {
PADDLE_ENFORCE_EQ(shape[i].is_constant(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"Input tensor's shape should be constant value."));
if (pos_axis == i) {
if (keep_dims) {
Expand Down Expand Up @@ -116,22 +116,22 @@ std::shared_ptr<framework::OpStrategy> StrategyForArgmin(
PADDLE_ENFORCE_EQ(
!args.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmin compute is empty! Please check."));
cinn::common::CINNValuePack pack_args = args[0];
CHECK_GE(pack_args.size(), 1U)
<< "There should be 1 input args for argmax compute";
Expr in_expr = pack_args[0];
PADDLE_ENFORCE_NOT_NULL(
in_expr.as_tensor(),
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmin compute is not tensor."));
Tensor in_tensor = in_expr.as_tensor_ref();
CHECK_EQ(pack_args.size(), 2U);
PADDLE_ENFORCE_EQ(
pack_args[1].is_string(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmin compute is not string."));
std::string tensor_name = pack_args[1].operator std::string();
auto out_tensor = Argmin(in_tensor, target, axis, keep_dims, tensor_name);
Expand All @@ -147,7 +147,7 @@ std::shared_ptr<framework::OpStrategy> StrategyForArgmin(
PADDLE_ENFORCE_EQ(
!args.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmin schedule is empty! Please check."));
cinn::common::CINNValuePack arg_pack = args[0];
std::vector<Expr> vec_ast;
Expand All @@ -160,7 +160,7 @@ std::shared_ptr<framework::OpStrategy> StrategyForArgmin(
PADDLE_ENFORCE_EQ(
!vec_ast.empty(),
true,
phi::errors::InvalidArgument(
::common::errors::InvalidArgument(
"The input argument of argmin schedule is empty! Please check."));
ir::ModuleExpr mod_expr(vec_ast);
ir::IRSchedule ir_sch(mod_expr);
Expand Down
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