STT-tensorflow/tensorflow/python/util/function_parameter_canonicalizer.cc
Kibeom Kim 637d6ebbdf Fix return type of PyUnicodeAsUtf8Compat to const char* to precisely match to the return type of PyUnicode_AsUTF8.
PiperOrigin-RevId: 332504252
Change-Id: I08d5b53c6716a1195b66b93262aa190065eed053
2020-09-18 12:38:00 -07:00

165 lines
5.4 KiB
C++

/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/python/util/function_parameter_canonicalizer.h"
#include "absl/container/flat_hash_set.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/python/lib/core/py_util.h"
#include "tensorflow/python/lib/core/safe_pyobject_ptr.h"
namespace {
inline const char* PyUnicodeAsUtf8Compat(PyObject* obj) {
#if PY_MAJOR_VERSION < 3
return PyString_AS_STRING(obj);
#else
return PyUnicode_AsUTF8(obj);
#endif
}
inline PyObject* PyUnicodeInternFromStringCompat(const char* str) {
#if PY_MAJOR_VERSION < 3
return PyString_InternFromString(str);
#else
return PyUnicode_InternFromString(str);
#endif
}
inline void PyUnicodeInternInPlaceCompat(PyObject** obj) {
#if PY_MAJOR_VERSION < 3
PyString_InternInPlace(obj);
#else
PyUnicode_InternInPlace(obj);
#endif
}
} // namespace
namespace tensorflow {
FunctionParameterCanonicalizer::FunctionParameterCanonicalizer(
absl::Span<const char*> arg_names, absl::Span<PyObject*> defaults)
: positional_args_size_(arg_names.size() - defaults.size()) {
DCheckPyGilState();
DCHECK_GE(positional_args_size_, 0);
interned_arg_names_.reserve(arg_names.size());
for (const char* obj : arg_names)
interned_arg_names_.emplace_back(PyUnicodeInternFromStringCompat(obj));
DCHECK(AreInternedArgNamesUnique());
for (PyObject* obj : defaults) Py_INCREF(obj);
defaults_ = std::vector<Safe_PyObjectPtr>(defaults.begin(), defaults.end());
}
bool FunctionParameterCanonicalizer::Canonicalize(
PyObject* args, PyObject* kwargs, absl::Span<PyObject*> result) {
// TODO(kkb): Closely follow `Python/ceval.c`'s logic and error handling.
DCheckPyGilState();
DCHECK(PyTuple_CheckExact(args));
DCHECK(PyDict_CheckExact(kwargs));
DCHECK_EQ(result.size(), interned_arg_names_.size());
const int args_size = Py_SIZE(args);
int remaining_positional_args_count = positional_args_size_ - args_size;
// Check if the number of input arguments are too many.
if (TF_PREDICT_FALSE(args_size > interned_arg_names_.size())) {
// TODO(kkb): Also report the actual numbers.
PyErr_SetString(PyExc_TypeError, "Too many arguments were given");
return false;
}
// Fill positional arguments.
for (int i = 0; i < args_size; ++i) result[i] = PyTuple_GET_ITEM(args, i);
// Fill default arguments.
for (int i = std::max(positional_args_size_, args_size);
i < interned_arg_names_.size(); ++i)
result[i] = defaults_[i - positional_args_size_].get();
// Fill keyword arguments.
if (kwargs != nullptr) {
PyObject *key, *value;
Py_ssize_t pos = 0;
while (PyDict_Next(kwargs, &pos, &key, &value)) {
std::size_t index = InternedArgNameLinearSearch(key);
// Check if key object(argument name) was found in the pre-built intern
// string table.
if (TF_PREDICT_FALSE(index == interned_arg_names_.size())) {
// `key` might not be an interend string, so get the interned string
// and try again.
PyUnicodeInternInPlaceCompat(&key);
index = InternedArgNameLinearSearch(key);
// Stil not found, then return an error.
if (TF_PREDICT_FALSE(index == interned_arg_names_.size())) {
PyErr_Format(PyExc_TypeError,
"Got an unexpected keyword argument '%s'",
PyUnicodeAsUtf8Compat(key));
return false;
}
}
// Check if the keyword argument overlaps with positional arguments.
if (TF_PREDICT_FALSE(index < args_size)) {
PyErr_Format(PyExc_TypeError, "Got multiple values for argument '%s'",
PyUnicodeAsUtf8Compat(key));
return false;
}
if (TF_PREDICT_FALSE(index < positional_args_size_))
--remaining_positional_args_count;
result[index] = value;
}
}
// Check if all the arguments are filled.
// Example failure, not enough number of arguments passed: `matmul(x)`
if (TF_PREDICT_FALSE(remaining_positional_args_count > 0)) {
// TODO(kkb): Report what arguments are missing.
PyErr_SetString(PyExc_TypeError, "Missing required positional argument");
return false;
}
return true;
}
ABSL_MUST_USE_RESULT
ABSL_ATTRIBUTE_HOT
inline std::size_t FunctionParameterCanonicalizer::InternedArgNameLinearSearch(
PyObject* name) {
std::size_t result = interned_arg_names_.size();
for (std::size_t i = 0; i < interned_arg_names_.size(); ++i)
if (TF_PREDICT_FALSE(name == interned_arg_names_[i].get())) return i;
return result;
}
bool FunctionParameterCanonicalizer::AreInternedArgNamesUnique() {
absl::flat_hash_set<PyObject*> interned_arg_names_set;
for (const Safe_PyObjectPtr& obj : interned_arg_names_)
interned_arg_names_set.emplace(obj.get());
return interned_arg_names_set.size() == interned_arg_names_.size();
}
} // namespace tensorflow