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// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/vespalib/testkit/test_kit.h>
#include <vespa/vespalib/data/slime/slime.h>
#include <vespa/vespalib/data/slime/json_format.h>
#include <vespa/vespalib/objects/nbostream.h>
#include <vespa/vespalib/util/stringfmt.h>
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/eval/eval/tensor.h>
#include <vespa/eval/eval/function.h>
#include <vespa/eval/eval/interpreted_function.h>
#include <vespa/eval/eval/tensor_engine.h>
#include <vespa/eval/eval/simple_tensor_engine.h>
#include <vespa/eval/tensor/default_tensor_engine.h>
#include <vespa/eval/eval/value_type.h>
#include <vespa/eval/eval/value.h>
#include <vespa/eval/eval/test/test_io.h>
#include <unistd.h>
#include "generate.h"
using namespace vespalib;
using namespace vespalib::eval;
using namespace vespalib::eval::test;
using namespace vespalib::slime::convenience;
using slime::JsonFormat;
using tensor::DefaultTensorEngine;
//-----------------------------------------------------------------------------
uint8_t unhex(char c) {
if (c >= '0' && c <= '9') {
return (c - '0');
}
if (c >= 'A' && c <= 'F') {
return ((c - 'A') + 10);
}
TEST_ERROR("bad hex char");
return 0;
}
void extract_data_from_string(Memory hex_dump, nbostream &data) {
if ((hex_dump.size > 2) && (hex_dump.data[0] == '0') && (hex_dump.data[1] == 'x')) {
for (size_t i = 2; i < (hex_dump.size - 1); i += 2) {
data << uint8_t((unhex(hex_dump.data[i]) << 4) | unhex(hex_dump.data[i + 1]));
}
}
}
nbostream extract_data(const Inspector &value) {
nbostream data;
if (value.asString().size > 0) {
extract_data_from_string(value.asString(), data);
} else {
Memory buf = value.asData();
data.write(buf.data, buf.size);
}
return data;
}
//-----------------------------------------------------------------------------
void insert_value(Cursor &cursor, const vespalib::string &name, const TensorSpec &spec) {
nbostream data;
Value::UP value = SimpleTensorEngine::ref().from_spec(spec);
SimpleTensorEngine::ref().encode(*value, data);
cursor.setData(name, Memory(data.peek(), data.size()));
}
TensorSpec extract_value(const Inspector &inspector) {
nbostream data = extract_data(inspector);
const auto &engine = SimpleTensorEngine::ref();
return engine.to_spec(*engine.decode(data));
}
//-----------------------------------------------------------------------------
std::vector<ValueType> get_types(const std::vector<Value::UP> ¶m_values) {
std::vector<ValueType> param_types;
for (size_t i = 0; i < param_values.size(); ++i) {
param_types.emplace_back(param_values[i]->type());
}
return param_types;
}
TensorSpec eval_expr(const Inspector &test, const TensorEngine &engine, bool typed) {
Function fun = Function::parse(test["expression"].asString().make_string());
std::vector<Value::UP> param_values;
std::vector<Value::CREF> param_refs;
for (size_t i = 0; i < fun.num_params(); ++i) {
param_values.emplace_back(engine.from_spec(extract_value(test["inputs"][fun.param_name(i)])));
param_refs.emplace_back(*param_values.back());
}
NodeTypes types = typed ? NodeTypes(fun, get_types(param_values)) : NodeTypes();
InterpretedFunction ifun(engine, fun, types);
InterpretedFunction::Context ctx(ifun);
SimpleObjectParams params(param_refs);
const Value &result = ifun.eval(ctx, params);
if (typed) {
ASSERT_EQUAL(result.type(), types.get_type(fun.root()));
}
return engine.to_spec(result);
}
//-----------------------------------------------------------------------------
std::vector<vespalib::string> extract_fields(const Inspector &object) {
struct FieldExtractor : slime::ObjectTraverser {
std::vector<vespalib::string> result;
void field(const Memory &symbol, const Inspector &) override {
result.push_back(symbol.make_string());
}
} extractor;
object.traverse(extractor);
return std::move(extractor.result);
};
//-----------------------------------------------------------------------------
class MyTestBuilder : public TestBuilder {
private:
TestWriter _writer;
void make_test(const vespalib::string &expression,
const std::map<vespalib::string,TensorSpec> &input_map,
const TensorSpec *expect = nullptr)
{
Cursor &test = _writer.create();
test.setString("expression", expression);
Cursor &inputs = test.setObject("inputs");
for (const auto &input: input_map) {
insert_value(inputs, input.first, input.second);
}
if (expect != nullptr) {
insert_value(test.setObject("result"), "expect", *expect);
} else {
insert_value(test.setObject("result"), "expect",
eval_expr(test, SimpleTensorEngine::ref(), false));
}
}
public:
MyTestBuilder(Output &out) : _writer(out) {}
void add(const vespalib::string &expression,
const std::map<vespalib::string,TensorSpec> &inputs,
const TensorSpec &expect) override
{
make_test(expression, inputs, &expect);
}
void add(const vespalib::string &expression,
const std::map<vespalib::string,TensorSpec> &inputs) override
{
make_test(expression, inputs);
}
};
void generate(Output &out) {
MyTestBuilder my_test_builder(out);
Generator::generate(my_test_builder);
}
//-----------------------------------------------------------------------------
void evaluate(Input &in, Output &out) {
auto handle_test = [&out](Slime &slime)
{
insert_value(slime["result"], "cpp_prod",
eval_expr(slime.get(), DefaultTensorEngine::ref(), true));
insert_value(slime["result"], "cpp_prod_untyped",
eval_expr(slime.get(), DefaultTensorEngine::ref(), false));
insert_value(slime["result"], "cpp_ref_typed",
eval_expr(slime.get(), SimpleTensorEngine::ref(), true));
write_compact(slime, out);
};
auto handle_summary = [&out](Slime &slime)
{
write_compact(slime, out);
};
for_each_test(in, handle_test, handle_summary);
}
//-----------------------------------------------------------------------------
void dump_test(const Inspector &test) {
fprintf(stderr, "expression: '%s'\n", test["expression"].asString().make_string().c_str());
for (const auto &input: extract_fields(test["inputs"])) {
auto value = extract_value(test["inputs"][input]);
fprintf(stderr, "input '%s': %s\n", input.c_str(), value.to_string().c_str());
}
}
void verify(Input &in, Output &out) {
std::map<vespalib::string,size_t> result_map;
auto handle_test = [&result_map](Slime &slime)
{
TensorSpec reference_result = eval_expr(slime.get(), SimpleTensorEngine::ref(), false);
for (const auto &result: extract_fields(slime["result"])) {
++result_map[result];
TEST_STATE(make_string("verifying result: '%s'", result.c_str()).c_str());
if (!EXPECT_EQUAL(reference_result, extract_value(slime["result"][result]))) {
dump_test(slime.get());
}
}
};
auto handle_summary = [&out,&result_map](Slime &slime)
{
Cursor &stats = slime.get().setObject("stats");
for (const auto &entry: result_map) {
stats.setLong(entry.first, entry.second);
}
JsonFormat::encode(slime, out, false);
};
for_each_test(in, handle_test, handle_summary);
}
//-----------------------------------------------------------------------------
int usage(const char *self) {
fprintf(stderr, "usage: %s <mode>\n", self);
fprintf(stderr, " <mode>: which mode to activate\n");
fprintf(stderr, " 'generate': write test cases to stdout\n");
fprintf(stderr, " 'evaluate': read test cases from stdin, annotate them with\n");
fprintf(stderr, " results from various implementations and write\n");
fprintf(stderr, " them to stdout\n");
fprintf(stderr, " 'verify': read annotated test cases from stdin and verify\n");
fprintf(stderr, " that all results are as expected\n");
return 1;
}
int main(int argc, char **argv) {
StdIn std_in;
StdOut std_out;
if (argc != 2) {
return usage(argv[0]);
}
vespalib::string mode = argv[1];
TEST_MASTER.init(make_string("vespa-tensor-conformance-%s", mode.c_str()).c_str());
if (mode == "generate") {
generate(std_out);
} else if (mode == "evaluate") {
evaluate(std_in, std_out);
} else if (mode == "verify") {
verify(std_in, std_out);
} else {
TEST_ERROR(make_string("unknown mode: %s", mode.c_str()).c_str());
}
return (TEST_MASTER.fini() ? 0 : 1);
}
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