| File: | .cache/bazel/_bazel_alan/39be661231df2a680c9b74265384c13c/execroot/org_tensorflow/tensorflow/python/framework/op_def_util.cc |
| Warning: | line 179, column 14 PyObject ownership leak with reference count of 1 |
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| 1 | /* Copyright 2020 The TensorFlow Authors. All Rights Reserved. | |||
| 2 | ||||
| 3 | Licensed under the Apache License, Version 2.0 (the "License"); | |||
| 4 | you may not use this file except in compliance with the License. | |||
| 5 | You may obtain a copy of the License at | |||
| 6 | ||||
| 7 | http://www.apache.org/licenses/LICENSE-2.0 | |||
| 8 | ||||
| 9 | Unless required by applicable law or agreed to in writing, software | |||
| 10 | distributed under the License is distributed on an "AS IS" BASIS, | |||
| 11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| 12 | See the License for the specific language governing permissions and | |||
| 13 | limitations under the License. | |||
| 14 | ==============================================================================*/ | |||
| 15 | #include "tensorflow/python/framework/op_def_util.h" | |||
| 16 | ||||
| 17 | #include <map> | |||
| 18 | ||||
| 19 | #include "absl/strings/str_cat.h" | |||
| 20 | #include "tensorflow/core/framework/attr_value.pb.h" | |||
| 21 | #include "tensorflow/core/framework/tensor_shape.pb.h" | |||
| 22 | #include "tensorflow/core/framework/types.pb.h" | |||
| 23 | #include "tensorflow/python/lib/core/safe_pyobject_ptr.h" | |||
| 24 | #include "tensorflow/python/util/util.h" | |||
| 25 | ||||
| 26 | using ::tensorflow::swig::GetRegisteredPyObject; | |||
| 27 | ||||
| 28 | #if PY_MAJOR_VERSION3 < 3 | |||
| 29 | // Python 2.x: | |||
| 30 | #define PY_STRING_CHECK(x)(((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 27))) != 0) || ((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 28))) != 0)) (PyString_Check(x) || PyUnicode_Check(x)((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 28))) != 0)) | |||
| 31 | #define PY_STRING_FROMSTRING(x)(PyUnicode_FromString(x)) (PyString_FromString(x)) | |||
| 32 | #define PY_INT_CHECK(x)(((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 24))) != 0)) (PyInt_Check(x)) | |||
| 33 | #define PY_INT_TYPEPyLong_Type PyInt_Type | |||
| 34 | #define PY_INT_FROM_LONG(x)(PyLong_FromLong(x)) (PyInt_FromLong(x)) | |||
| 35 | #else | |||
| 36 | // Python 3.x: | |||
| 37 | #define PY_STRING_CHECK(x)(((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 27))) != 0) || ((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 28))) != 0)) (PyBytes_Check(x)((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 27))) != 0) || PyUnicode_Check(x)((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 28))) != 0)) | |||
| 38 | #define PY_STRING_FROMSTRING(x)(PyUnicode_FromString(x)) (PyUnicode_FromString(x)) | |||
| 39 | #define PY_INT_CHECK(x)(((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 24))) != 0)) (PyLong_Check(x)((((((PyObject*)(x))->ob_type))->tp_flags & ((1UL << 24))) != 0)) | |||
| 40 | #define PY_INT_TYPEPyLong_Type PyLong_Type | |||
| 41 | #define PY_INT_FROM_LONG(x)(PyLong_FromLong(x)) (PyLong_FromLong(x)) | |||
| 42 | #endif | |||
| 43 | ||||
| 44 | namespace tensorflow { | |||
| 45 | ||||
| 46 | namespace { | |||
| 47 | ||||
| 48 | const std::map<std::string, AttributeType>* AttributeTypeNameMap() { | |||
| 49 | static auto* type_map = new std::map<std::string, AttributeType>( | |||
| 50 | {{"any", AttributeType::ANY}, | |||
| 51 | {"float", AttributeType::FLOAT}, | |||
| 52 | {"int", AttributeType::INT}, | |||
| 53 | {"string", AttributeType::STRING}, | |||
| 54 | {"bool", AttributeType::BOOL}, | |||
| 55 | {"shape", AttributeType::SHAPE}, | |||
| 56 | {"type", AttributeType::DTYPE}, | |||
| 57 | {"tensor", AttributeType::TENSOR}, | |||
| 58 | {"list(any)", AttributeType::LIST_ANY}, | |||
| 59 | {"list(float)", AttributeType::LIST_FLOAT}, | |||
| 60 | {"list(int)", AttributeType::LIST_INT}, | |||
| 61 | {"list(string)", AttributeType::LIST_STRING}, | |||
| 62 | {"list(bool)", AttributeType::LIST_BOOL}, | |||
| 63 | {"list(type)", AttributeType::LIST_DTYPE}, | |||
| 64 | {"list(shape)", AttributeType::LIST_SHAPE}, | |||
| 65 | {"list(tensor)", AttributeType::LIST_TENSOR}}); | |||
| 66 | return type_map; | |||
| 67 | } | |||
| 68 | ||||
| 69 | // Note: we define functors for converting value types (rather than simple | |||
| 70 | // functions) so we can define a generic ConvertListAttr method. These | |||
| 71 | // functors all return a new reference on success, or nullptr on failure. | |||
| 72 | // They do not (necessarily) call PyErr_SetString. | |||
| 73 | ||||
| 74 | struct ConvertAnyFunctor { | |||
| 75 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 76 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 77 | return Safe_PyObjectPtr(value); | |||
| 78 | } | |||
| 79 | }; | |||
| 80 | ||||
| 81 | struct ConvertFloatFunctor { | |||
| 82 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 83 | Safe_PyObjectPtr result; | |||
| 84 | if (PyFloat_Check(value)((((PyObject*)(value))->ob_type) == (&PyFloat_Type) || PyType_IsSubtype((((PyObject*)(value))->ob_type), (&PyFloat_Type )))) { | |||
| 85 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 86 | result.reset(value); | |||
| 87 | } else if (!PY_STRING_CHECK(value)(((((((PyObject*)(value))->ob_type))->tp_flags & (( 1UL << 27))) != 0) || ((((((PyObject*)(value))->ob_type ))->tp_flags & ((1UL << 28))) != 0))) { | |||
| 88 | result.reset(PyObject_CallFunctionObjArgs( | |||
| 89 | reinterpret_cast<PyObject*>(&PyFloat_Type), value, nullptr)); | |||
| 90 | } | |||
| 91 | return result; | |||
| 92 | } | |||
| 93 | }; | |||
| 94 | ||||
| 95 | struct ConvertIntFunctor { | |||
| 96 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 97 | Safe_PyObjectPtr result; | |||
| 98 | if (PY_INT_CHECK(value)(((((((PyObject*)(value))->ob_type))->tp_flags & (( 1UL << 24))) != 0))) { | |||
| 99 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 100 | result.reset(value); | |||
| 101 | } else if (!PY_STRING_CHECK(value)(((((((PyObject*)(value))->ob_type))->tp_flags & (( 1UL << 27))) != 0) || ((((((PyObject*)(value))->ob_type ))->tp_flags & ((1UL << 28))) != 0))) { | |||
| 102 | result.reset(PyObject_CallFunctionObjArgs( | |||
| 103 | reinterpret_cast<PyObject*>(&PY_INT_TYPEPyLong_Type), value, nullptr)); | |||
| 104 | } | |||
| 105 | return result; | |||
| 106 | } | |||
| 107 | }; | |||
| 108 | ||||
| 109 | struct ConvertStringFunctor { | |||
| 110 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 111 | Safe_PyObjectPtr result; | |||
| 112 | if (PY_STRING_CHECK(value)(((((((PyObject*)(value))->ob_type))->tp_flags & (( 1UL << 27))) != 0) || ((((((PyObject*)(value))->ob_type ))->tp_flags & ((1UL << 28))) != 0))) { | |||
| 113 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 114 | result.reset(value); | |||
| 115 | } | |||
| 116 | return result; | |||
| 117 | } | |||
| 118 | }; | |||
| 119 | ||||
| 120 | // TODO(edloper): Should we allow ints (or any other values) to be converted | |||
| 121 | // to booleans? Currently, TensorFlow does not do this conversion for attribute | |||
| 122 | // values in _MakeBool or make_bool. | |||
| 123 | struct ConvertBoolFunctor { | |||
| 124 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 125 | Safe_PyObjectPtr result; | |||
| 126 | if (PyBool_Check(value)((((PyObject*)(value))->ob_type) == &PyBool_Type)) { | |||
| 127 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 128 | result.reset(value); | |||
| 129 | } | |||
| 130 | return result; | |||
| 131 | } | |||
| 132 | }; | |||
| 133 | ||||
| 134 | struct ConvertDTypeFunctor { | |||
| 135 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 136 | Safe_PyObjectPtr result; | |||
| 137 | // The following symbols are registered in op_def_library.py | |||
| 138 | static PyObject* dtype = GetRegisteredPyObject("tf.dtypes.DType"); | |||
| 139 | static PyObject* as_dtype = GetRegisteredPyObject("tf.dtypes.as_dtype"); | |||
| 140 | if (reinterpret_cast<PyObject*>(value->ob_type) == dtype) { | |||
| 141 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 142 | result.reset(value); | |||
| 143 | } else { | |||
| 144 | result.reset(PyObject_CallFunctionObjArgs(as_dtype, value, nullptr)); | |||
| 145 | } | |||
| 146 | return result; | |||
| 147 | } | |||
| 148 | }; | |||
| 149 | ||||
| 150 | struct ConvertTensorShapeFunctor { | |||
| 151 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 152 | Safe_PyObjectPtr result; | |||
| 153 | // The following symbols are registered in op_def_library.py | |||
| 154 | static PyObject* shape = GetRegisteredPyObject("tf.TensorShape"); | |||
| 155 | static PyObject* as_shape = GetRegisteredPyObject("tf.as_shape"); | |||
| 156 | if (reinterpret_cast<PyObject*>(value->ob_type) == shape) { | |||
| 157 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 158 | result.reset(value); | |||
| 159 | } else { | |||
| 160 | result.reset(PyObject_CallFunctionObjArgs(as_shape, value, nullptr)); | |||
| 161 | } | |||
| 162 | return result; | |||
| 163 | } | |||
| 164 | }; | |||
| 165 | ||||
| 166 | struct ConvertTensorProtoFunctor { | |||
| 167 | Safe_PyObjectPtr operator()(PyObject* value) { | |||
| 168 | Safe_PyObjectPtr result; | |||
| 169 | // The following symbols are registered in op_def_library.py | |||
| 170 | static PyObject* tensor_proto = GetRegisteredPyObject("tf.TensorProto"); | |||
| 171 | static PyObject* text_format_parse = | |||
| 172 | GetRegisteredPyObject("text_format.Parse"); | |||
| 173 | if (reinterpret_cast<PyObject*>(value->ob_type) == tensor_proto) { | |||
| 174 | Py_INCREF(value)_Py_INCREF(((PyObject*)(value))); | |||
| 175 | result.reset(value); | |||
| 176 | } else if (PY_STRING_CHECK(value)(((((((PyObject*)(value))->ob_type))->tp_flags & (( 1UL << 27))) != 0) || ((((((PyObject*)(value))->ob_type ))->tp_flags & ((1UL << 28))) != 0))) { | |||
| 177 | result.reset(PyObject_CallObject(tensor_proto, nullptr)); | |||
| 178 | if (result) { | |||
| 179 | if (!PyObject_CallFunctionObjArgs(text_format_parse, value, | |||
| ||||
| 180 | result.get(), nullptr)) { | |||
| 181 | return nullptr; | |||
| 182 | } | |||
| 183 | } | |||
| 184 | } | |||
| 185 | return result; | |||
| 186 | } | |||
| 187 | }; | |||
| 188 | ||||
| 189 | // Converts `value` to a list of elements with the same type, using | |||
| 190 | // `convert_functor` to convert each element. | |||
| 191 | template <typename T> | |||
| 192 | Safe_PyObjectPtr ConvertListAttr(PyObject* value, T convert_functor) { | |||
| 193 | // Copy the list. | |||
| 194 | Safe_PyObjectPtr result(PySequence_List(value)); | |||
| 195 | if (!result) return nullptr; | |||
| 196 | ||||
| 197 | // Check the type of each item in the list. | |||
| 198 | Py_ssize_t len = PySequence_Fast_GET_SIZE(result.get())(((((((PyObject*)(result.get()))->ob_type))->tp_flags & ((1UL << 25))) != 0) ? ((static_cast<void> (0)), (((PyVarObject*)(result.get()))->ob_size)) : (((PyVarObject *)(((static_cast<void> (0)), (PyTupleObject *)(result.get ()))))->ob_size)); | |||
| 199 | PyObject** items = PySequence_Fast_ITEMS(result.get())(((((((PyObject*)(result.get()))->ob_type))->tp_flags & ((1UL << 25))) != 0) ? ((PyListObject *)(result.get()) )->ob_item : ((PyTupleObject *)(result.get()))->ob_item ); | |||
| 200 | for (Py_ssize_t i = 0; i < len; ++i) { | |||
| 201 | if (!PyFloat_Check(value)((((PyObject*)(value))->ob_type) == (&PyFloat_Type) || PyType_IsSubtype((((PyObject*)(value))->ob_type), (&PyFloat_Type )))) { | |||
| 202 | Safe_PyObjectPtr item = convert_functor(items[i]); | |||
| 203 | if (!item) return nullptr; | |||
| 204 | PySequence_SetItem(result.get(), i, item.get()); | |||
| 205 | } | |||
| 206 | } | |||
| 207 | return result; | |||
| 208 | } | |||
| 209 | ||||
| 210 | // Returns the given `value` value, converted to the indicated type. | |||
| 211 | // Returns nullptr if `value` is not convertible. | |||
| 212 | Safe_PyObjectPtr ConvertAttrOrNull(PyObject* value, AttributeType attr_type) { | |||
| 213 | switch (attr_type) { | |||
| 214 | case AttributeType::ANY: | |||
| 215 | return ConvertAnyFunctor()(value); | |||
| 216 | case AttributeType::FLOAT: | |||
| 217 | return ConvertFloatFunctor()(value); | |||
| 218 | case AttributeType::INT: | |||
| 219 | return ConvertIntFunctor()(value); | |||
| 220 | case AttributeType::STRING: | |||
| 221 | return ConvertStringFunctor()(value); | |||
| 222 | case AttributeType::BOOL: | |||
| 223 | return ConvertBoolFunctor()(value); | |||
| 224 | case AttributeType::DTYPE: | |||
| 225 | return ConvertDTypeFunctor()(value); | |||
| 226 | case AttributeType::SHAPE: | |||
| 227 | return ConvertTensorShapeFunctor()(value); | |||
| 228 | case AttributeType::TENSOR: | |||
| 229 | return ConvertTensorProtoFunctor()(value); | |||
| 230 | case AttributeType::LIST_ANY: | |||
| 231 | return ConvertListAttr(value, ConvertAnyFunctor()); | |||
| 232 | case AttributeType::LIST_FLOAT: | |||
| 233 | return ConvertListAttr(value, ConvertFloatFunctor()); | |||
| 234 | case AttributeType::LIST_INT: | |||
| 235 | return ConvertListAttr(value, ConvertIntFunctor()); | |||
| 236 | case AttributeType::LIST_STRING: | |||
| 237 | return ConvertListAttr(value, ConvertStringFunctor()); | |||
| 238 | case AttributeType::LIST_BOOL: | |||
| 239 | return ConvertListAttr(value, ConvertBoolFunctor()); | |||
| 240 | case AttributeType::LIST_DTYPE: | |||
| 241 | return ConvertListAttr(value, ConvertDTypeFunctor()); | |||
| 242 | case AttributeType::LIST_SHAPE: | |||
| 243 | return ConvertListAttr(value, ConvertTensorShapeFunctor()); | |||
| 244 | case AttributeType::LIST_TENSOR: | |||
| 245 | return ConvertListAttr(value, ConvertTensorProtoFunctor()); | |||
| 246 | default: | |||
| 247 | return nullptr; | |||
| 248 | } | |||
| 249 | } | |||
| 250 | ||||
| 251 | // Returns a new reference to Py_True or Py_False depending on b. | |||
| 252 | PyObject* PyBool_FromBool(bool b) { | |||
| 253 | PyObject* result = b ? Py_True((PyObject *) &_Py_TrueStruct) : Py_False((PyObject *) &_Py_FalseStruct); | |||
| 254 | Py_INCREF(result)_Py_INCREF(((PyObject*)(result))); | |||
| 255 | return result; | |||
| 256 | } | |||
| 257 | ||||
| 258 | Safe_PyObjectPtr AttrValueListToPyObject(AttrValue::ListValue list) { | |||
| 259 | if (list.s_size()) { | |||
| 260 | Safe_PyObjectPtr result(PyList_New(list.s_size())); | |||
| 261 | for (int i = 0; i < list.s_size(); ++i) { | |||
| 262 | PyList_SET_ITEM(result.get(), i, PY_STRING_FROMSTRING(list.s(i).c_str()))PyList_SetItem(result.get(), i, (PyUnicode_FromString(list.s( i).c_str()))); | |||
| 263 | } | |||
| 264 | return result; | |||
| 265 | } else if (list.i_size()) { | |||
| 266 | Safe_PyObjectPtr result(PyList_New(list.i_size())); | |||
| 267 | for (int i = 0; i < list.i_size(); ++i) { | |||
| 268 | PyList_SET_ITEM(result.get(), i, PY_INT_FROM_LONG(list.i(i)))PyList_SetItem(result.get(), i, (PyLong_FromLong(list.i(i)))); | |||
| 269 | } | |||
| 270 | return result; | |||
| 271 | } else if (list.f_size()) { | |||
| 272 | Safe_PyObjectPtr result(PyList_New(list.f_size())); | |||
| 273 | for (int i = 0; i < list.f_size(); ++i) { | |||
| 274 | PyList_SET_ITEM(result.get(), i, PyFloat_FromDouble(list.f(i)))PyList_SetItem(result.get(), i, PyFloat_FromDouble(list.f(i)) ); | |||
| 275 | } | |||
| 276 | return result; | |||
| 277 | } else if (list.b_size()) { | |||
| 278 | Safe_PyObjectPtr result(PyList_New(list.b_size())); | |||
| 279 | for (int i = 0; i < list.b_size(); ++i) { | |||
| 280 | PyList_SET_ITEM(result.get(), i, PyBool_FromBool(list.b(i)))PyList_SetItem(result.get(), i, PyBool_FromBool(list.b(i))); | |||
| 281 | } | |||
| 282 | return result; | |||
| 283 | } else if (list.type_size()) { | |||
| 284 | Safe_PyObjectPtr result(PyList_New(list.type_size())); | |||
| 285 | for (int i = 0; i < list.type_size(); ++i) { | |||
| 286 | Safe_PyObjectPtr item(DataTypeToPyObject(list.type(i))); | |||
| 287 | Py_INCREF(item.get())_Py_INCREF(((PyObject*)(item.get()))); | |||
| 288 | PyList_SET_ITEM(result.get(), i, item.get())PyList_SetItem(result.get(), i, item.get()); | |||
| 289 | } | |||
| 290 | return result; | |||
| 291 | } else if (list.shape_size()) { | |||
| 292 | Safe_PyObjectPtr result(PyList_New(list.shape_size())); | |||
| 293 | for (int i = 0; i < list.shape_size(); ++i) { | |||
| 294 | Safe_PyObjectPtr item(TensorShapeProtoToPyObject(list.shape(i))); | |||
| 295 | Py_INCREF(item.get())_Py_INCREF(((PyObject*)(item.get()))); | |||
| 296 | PyList_SET_ITEM(result.get(), i, item.get())PyList_SetItem(result.get(), i, item.get()); | |||
| 297 | } | |||
| 298 | return result; | |||
| 299 | } else if (list.tensor_size() || list.func_size()) { | |||
| 300 | // TODO(edloper): Add support for tensorflow::AttrValue::kTensor. | |||
| 301 | PyErr_SetString(PyExc_TypeError, "Unsupported AttrValue type"); | |||
| 302 | return nullptr; | |||
| 303 | } else { | |||
| 304 | // Empty list | |||
| 305 | return Safe_PyObjectPtr(PyList_New(0)); | |||
| 306 | } | |||
| 307 | } | |||
| 308 | ||||
| 309 | } // namespace | |||
| 310 | ||||
| 311 | AttributeType AttributeTypeFromName(const std::string& type_name) { | |||
| 312 | const auto* type_map = AttributeTypeNameMap(); | |||
| 313 | auto it = type_map->find(type_name); | |||
| 314 | return it != type_map->end() ? it->second : AttributeType::UNKNOWN; | |||
| 315 | } | |||
| 316 | ||||
| 317 | std::string AttributeTypeToName(AttributeType attr_type) { | |||
| 318 | for (const auto& pair : *AttributeTypeNameMap()) { | |||
| 319 | if (pair.second == attr_type) { | |||
| 320 | return pair.first; | |||
| 321 | } | |||
| 322 | } | |||
| 323 | return "<unknown>"; | |||
| 324 | } | |||
| 325 | ||||
| 326 | Safe_PyObjectPtr ConvertPyObjectToAttributeType(PyObject* value, | |||
| 327 | AttributeType type) { | |||
| 328 | Safe_PyObjectPtr result = ConvertAttrOrNull(value, type); | |||
| ||||
| 329 | if (!result) { | |||
| 330 | auto err = absl::StrCat("Failed to convert value of type '", | |||
| 331 | value->ob_type->tp_name, "' to type '", | |||
| 332 | AttributeTypeToName(type), "'."); | |||
| 333 | PyErr_SetString(PyExc_TypeError, err.c_str()); | |||
| 334 | } | |||
| 335 | ||||
| 336 | return result; | |||
| 337 | } | |||
| 338 | ||||
| 339 | Safe_PyObjectPtr AttrValueToPyObject(const AttrValue& attr_value) { | |||
| 340 | switch (attr_value.value_case()) { | |||
| 341 | case tensorflow::AttrValue::kS: | |||
| 342 | return Safe_PyObjectPtr(PY_STRING_FROMSTRING(attr_value.s().c_str())(PyUnicode_FromString(attr_value.s().c_str()))); | |||
| 343 | case tensorflow::AttrValue::kI: | |||
| 344 | return Safe_PyObjectPtr(PY_INT_FROM_LONG(attr_value.i())(PyLong_FromLong(attr_value.i()))); | |||
| 345 | case tensorflow::AttrValue::kF: | |||
| 346 | return Safe_PyObjectPtr(PyFloat_FromDouble(attr_value.f())); | |||
| 347 | case tensorflow::AttrValue::kB: | |||
| 348 | return Safe_PyObjectPtr(PyBool_FromBool(attr_value.b())); | |||
| 349 | case tensorflow::AttrValue::kType: | |||
| 350 | return DataTypeToPyObject(attr_value.type()); | |||
| 351 | case tensorflow::AttrValue::kShape: | |||
| 352 | return TensorShapeProtoToPyObject(attr_value.shape()); | |||
| 353 | case tensorflow::AttrValue::kList: | |||
| 354 | return AttrValueListToPyObject(attr_value.list()); | |||
| 355 | default: | |||
| 356 | // TODO(edloper): Add support for tensorflow::AttrValue::kTensor. | |||
| 357 | PyErr_SetString(PyExc_ValueError, "Unsupported AttrValue type"); | |||
| 358 | return nullptr; | |||
| 359 | } | |||
| 360 | } | |||
| 361 | ||||
| 362 | Safe_PyObjectPtr DataTypeToPyObject(const DataType& data_type) { | |||
| 363 | Safe_PyObjectPtr enum_value(PY_INT_FROM_LONG(data_type)(PyLong_FromLong(data_type))); | |||
| 364 | return ConvertDTypeFunctor()(enum_value.get()); | |||
| 365 | } | |||
| 366 | ||||
| 367 | Safe_PyObjectPtr TensorShapeProtoToPyObject( | |||
| 368 | const TensorShapeProto& tensor_shape) { | |||
| 369 | if (tensor_shape.unknown_rank()) { | |||
| 370 | return ConvertTensorShapeFunctor()(Py_None(&_Py_NoneStruct)); | |||
| 371 | } else { | |||
| 372 | Safe_PyObjectPtr dims(PyTuple_New(tensor_shape.dim_size())); | |||
| 373 | for (int i = 0; i < tensor_shape.dim_size(); ++i) { | |||
| 374 | PyTuple_SET_ITEM(dims.get(), i,PyTuple_SetItem(dims.get(), i, (PyLong_FromLong(tensor_shape. dim(i).size()))) | |||
| 375 | PY_INT_FROM_LONG(tensor_shape.dim(i).size()))PyTuple_SetItem(dims.get(), i, (PyLong_FromLong(tensor_shape. dim(i).size()))); | |||
| 376 | } | |||
| 377 | return ConvertTensorShapeFunctor()(dims.get()); | |||
| 378 | } | |||
| 379 | } | |||
| 380 | ||||
| 381 | } // namespace tensorflow |
| 1 | #ifndef PyObject_CallFunctionObjArgs |
| 2 | struct _object; |
| 3 | typedef struct _object PyObject; |
| 4 | PyObject* clang_analyzer_PyObject_New_Reference(); |
| 5 | PyObject* PyObject_CallFunctionObjArgs(PyObject *callable, ...) { |
| 6 | return clang_analyzer_PyObject_New_Reference(); |
| 7 | } |
| 8 | #else |
| 9 | #warning "API PyObject_CallFunctionObjArgs is defined as a macro." |
| 10 | #endif |