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op unittest for cbrt/ceil/cholesky/concat/constant/fill_constant (#1495)
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* op unittest for cbrt

* op unittest for ceil

* op unittest for cholesky

* op unittest for concat

* op unittest for constant

* add 4d test for constant op

* fix ci

* op unittest for fill_constant

* op unittest for fill_constant

* refine
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@zzk0
zzk0 authored Jun 8, 2023
1 parent df023dd commit c0d5079
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Showing 10 changed files with 1,047 additions and 367 deletions.
11 changes: 0 additions & 11 deletions cinn/frontend/net_builder.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -246,17 +246,6 @@ Placeholder NetBuilder::CreateInput(const Variable& var) {
return Placeholder(var);
}

Variable NetBuilder::FillConstant(
const std::vector<int>& shape, float value, const std::string& name, const std::string& dtype, bool force_cpu) {
auto out =
CustomInstr("fill_constant", {}, {{"shape", shape}, {"value", value}, {"dtype", dtype}, {"force_cpu", force_cpu}})
.front();
if (!name.empty()) {
out.set_id(cinn::utils::TransValidVarName(name));
}
return out;
}

Variable NetBuilder::FillConstant(const std::vector<int>& shape,
const std::string& str_value,
const std::string& name,
Expand Down
18 changes: 14 additions & 4 deletions cinn/frontend/net_builder.h
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Original file line number Diff line number Diff line change
Expand Up @@ -350,7 +350,7 @@ class NetBuilder {
const std::string& id_hint = "");

/**
* @brief Create constant tensor with the specific value/vector and type, the type is infered from value.
* @brief Create constant tensor with the specific value/vector and type
* @param value The constant value to be set.
* @param name The name of output variable.
* @return The result variable.
Expand Down Expand Up @@ -408,11 +408,21 @@ class NetBuilder {
* @param force_cpu Whether the variable should force placed in cpu, default in device memory. Default is false.
* @return The result variable.
*/
template <typename T = float>
Variable FillConstant(const cinn::utils::ShapeType& shape,
float value,
T value,
const std::string& name,
const std::string& dtype,
bool force_cpu = false);
bool force_cpu = false) {
auto out =
CustomInstr(
"fill_constant", {}, {{"shape", shape}, {"value", value}, {"dtype", dtype}, {"force_cpu", force_cpu}})
.front();
if (!name.empty()) {
out.set_id(cinn::utils::TransValidVarName(name));
}
return out;
}

/**
* @brief The op return a variable with the specific string value, shape and type.
Expand Down Expand Up @@ -442,7 +452,7 @@ class NetBuilder {
T value,
const std::string& name = "",
bool force_cpu = false) {
return FillConstant(shape, static_cast<float>(value), name, common::Type2Str(common::type_of<T>()), force_cpu);
return FillConstant<T>(shape, value, name, common::Type2Str(common::type_of<T>()), force_cpu);
}

/**
Expand Down
25 changes: 19 additions & 6 deletions cinn/hlir/op/elementwise.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -201,6 +201,7 @@ std::shared_ptr<OpStrategy> StrategyForConstScalar(const framework::NodeAttr &at
framework::CINNCompute const_scalar_compute([=](lang::Args args, lang::RetValue *ret) {
CHECK(!args.empty()) << "The input argument of const_float compute is empty! Please check.";
auto scalar = GetScalarExpr(attrs.attr_store.at("value"));
auto scalar_type = out_type.at(0);
CINNValuePack pack_args = args[0];
std::string tensor_name = UniqName("const_scalar_Out");
if (FLAGS_cinn_ir_schedule) {
Expand All @@ -210,7 +211,12 @@ std::shared_ptr<OpStrategy> StrategyForConstScalar(const framework::NodeAttr &at
}

auto out = lang::Compute(
{Expr(1)}, [=](const std::vector<Expr> &indice) { return scalar; }, tensor_name);
{Expr(1)},
[=](const std::vector<Expr> &indice) {
auto res = (scalar_type == scalar->type()) ? scalar : ir::Cast::Make(scalar_type, scalar);
return res;
},
tensor_name);
CHECK(out.defined()) << "can't create const scalar with the given type " << out_type[0];
auto stages = CreateStages({out});
*ret = CINNValuePack{{CINNValue(out), CINNValue(stages)}};
Expand All @@ -229,9 +235,16 @@ std::vector<shape_t> InferShapeForConstScalar(const std::vector<shape_t> &inputs
}

std::vector<Type> InferDtypeForConstScalar(const std::vector<Type> &inputs_type, const framework::AttrMapType &attrs) {
CHECK(attrs.count("value"));
auto scalar = GetScalarExpr(attrs.at("value"));
auto out_type = scalar->type();
Type out_type;
if (attrs.find("dtype") != attrs.end()) {
auto dtype_str = absl::get<std::string>(attrs.at("dtype"));
if (!dtype_str.empty()) {
out_type = common::Str2Type(dtype_str);
}
} else {
auto scalar = GetScalarExpr(attrs.at("value"));
out_type = scalar->type();
}
VLOG(3) << "scalar type: " << out_type;
return {out_type};
}
Expand Down Expand Up @@ -356,10 +369,10 @@ std::vector<std::vector<std::string>> InferLayoutForFillConstant(const std::vect

#define EXPAND_ATTR_TYPE(MACRO) \
MACRO(bool) \
MACRO(float) \
MACRO(int) \
MACRO(int64_t) \
MACRO(double)
MACRO(double) \
MACRO(float)

std::shared_ptr<OpStrategy> StrategyForAssignValue(const framework::NodeAttr &attrs,
const std::vector<ir::Tensor> &inputs,
Expand Down
36 changes: 17 additions & 19 deletions cinn/pybind/frontend.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -65,8 +65,6 @@ static const char *SnakeName(const char *name) {

#define EXPAND_CINN_SUPPORT_TYPE(EXPAND_MACRO) \
EXPAND_MACRO(bool) \
EXPAND_MACRO(float) \
EXPAND_MACRO(int) \
EXPAND_MACRO(int64_t) \
EXPAND_MACRO(double)

Expand Down Expand Up @@ -405,14 +403,23 @@ void BindFrontend(pybind11::module *m) {
#undef EXPAND_QUINTIC_VECTOR
#undef EXPAND_SEXTIC_VECTOR
#undef PY_REGISTER_CONSTANT_OP
#define PY_REGISTER_FILLCONSTANT_OP(TYPE__) \
.def("fill_constant", \
static_cast<Variable (NetBuilder::*)( \
const std::vector<int> &, TYPE__, const std::string &, bool)>( \
&NetBuilder::template FillConstant<TYPE__>), \
py::arg("shape"), \
py::arg("value"), \
py::arg("name") = "", \
#define PY_REGISTER_FILLCONSTANT_OP(TYPE__) \
.def("fill_constant", \
static_cast<Variable (NetBuilder::*)( \
const std::vector<int> &, TYPE__, const std::string &, const std::string &, bool)>( \
&NetBuilder::FillConstant<TYPE__>), \
py::arg("shape"), \
py::arg("value"), \
py::arg("name") = "", \
py::arg("dtype"), \
py::arg("force_cpu") = false) \
.def("fill_constant", \
static_cast<Variable (NetBuilder::*)( \
const std::vector<int> &, TYPE__, const std::string &, bool)>( \
&NetBuilder::template FillConstant<TYPE__>), \
py::arg("shape"), \
py::arg("value"), \
py::arg("name") = "", \
py::arg("force_cpu") = false)
EXPAND_CINN_SUPPORT_TYPE(PY_REGISTER_FILLCONSTANT_OP)
#undef PY_REGISTER_FILLCONSTANT_OP
Expand Down Expand Up @@ -462,15 +469,6 @@ void BindFrontend(pybind11::module *m) {
.def("name", &NetBuilder::name)
.def("__str__", [](NetBuilder &self) { return self.name(); })
.def("append_instruction", &NetBuilder::AppendInstruction, py::arg("instr"))
.def("fill_constant",
static_cast<Variable (NetBuilder::*)(
const std::vector<int> &, float, const std::string &, const std::string &, bool)>(
&NetBuilder::FillConstant),
py::arg("shape"),
py::arg("value"),
py::arg("name") = "",
py::arg("dtype"),
py::arg("force_cpu") = false)
.def("fill_constant",
static_cast<Variable (NetBuilder::*)(
const std::vector<int> &, const std::string &, const std::string &, const std::string &, bool)>(
Expand Down
137 changes: 97 additions & 40 deletions python/tests/ops/test_cbrt_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,26 +14,26 @@
# See the License for the specific language governing permissions and
# limitations under the License.

import unittest
import numpy as np
from op_test import OpTest, OpTestTool
import paddle
import paddle.nn.functional as F
import cinn
from cinn.frontend import *
import numpy as np
from cinn.common import *
from cinn.frontend import *
from op_test import OpTest, OpTestTool
from op_test_helper import TestCaseHelper


@OpTestTool.skip_if(not is_compiled_with_cuda(),
"x86 test will be skipped due to timeout.")
class TestCbrtOp(OpTest):
def setUp(self):
self.init_case()
print(f"\nRunning {self.__class__.__name__}: {self.case}")
self.inputs = {}
self.prepare_inputs()

def init_case(self):
def prepare_inputs(self):
self.inputs = {
"x": np.array([0, 1, 0.01, 27, 1000000,
0.970299]).astype("float32")
"x":
self.random(self.case["shape"], self.case["dtype"], -100.0, 100.0),
}

def build_paddle_program(self, target):
Expand All @@ -43,44 +43,101 @@ def build_paddle_program(self, target):

def build_cinn_program(self, target):
builder = NetBuilder("cbrt")
x = builder.create_input(Float(32), self.inputs["x"].shape, "x")
x = builder.create_input(
self.nptype2cinntype(self.inputs["x"].dtype),
self.inputs["x"].shape, "x")
out = builder.cbrt(x)

prog = builder.build()
res = self.get_cinn_output(prog, target, [x], [self.inputs["x"]],
[out])

self.cinn_outputs = [res[0]]
self.cinn_outputs = res

def test_check_results(self):
self.check_outputs_and_grads()


class TestCbrtCase1(TestCbrtOp):
def init_case(self):
self.inputs = {
"x":
np.array([0, 1, 0.01, 27, 1000000, 0.970299, 124483,
13.7396]).astype("float32")
}


class TestCbrtCase2(TestCbrtOp):
def init_case(self):
self.inputs = {
"x":
np.array([[0, 1, 0.01, 27], [1000000, 0.970299, 124483,
13.7396]]).astype("float32"),
}


class TestCbrtCase3(TestCbrtOp):
def init_case(self):
np.random.seed(0)
self.inputs = {
"x": np.random.random((32, 64)).astype("float32"),
}
self.check_outputs_and_grads(
max_relative_error=1e-3, max_absolute_error=1e-3)


class TestCbrtOpShape(TestCaseHelper):
def init_attrs(self):
self.class_name = "TestCbrtOpShape"
self.cls = TestCbrtOp
self.inputs = [
{
"shape": [10],
},
{
"shape": [8, 5],
},
{
"shape": [10, 3, 5],
},
{
"shape": [80, 40, 5, 7],
},
{
"shape": [80, 1, 5, 7],
},
{
"shape": [80, 3, 1024, 7],
},
{
"shape": [10, 5, 1024, 2048],
},
{
"shape": [1],
},
{
"shape": [512],
},
{
"shape": [1024],
},
{
"shape": [2048],
},
{
"shape": [1, 1, 1, 1],
},
]
self.dtypes = [
{
"dtype": "float32"
},
]
self.attrs = []


class TestCbrtOpDtype(TestCaseHelper):
def init_attrs(self):
self.class_name = "TestCbrtOpDtype"
self.cls = TestCbrtOp
self.inputs = [
{
"shape": [1],
},
{
"shape": [5],
},
{
"shape": [80, 40, 5, 7],
},
]
self.dtypes = [
{
"dtype": "float16"
},
{
"dtype": "float32"
},
{
"dtype": "float64"
},
]
self.attrs = []


if __name__ == "__main__":
unittest.main()
TestCbrtOpShape().run()
TestCbrtOpDtype().run()
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