diff options
author | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
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committer | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
commit | f41959ccb2d9d4c722fe8fc3351401d53bcf4900 (patch) | |
tree | ef0ca22cb2a5ac4bdec9d080d8e0788a53ed496d /tensorflow/python/lib/core |
TensorFlow: Initial commit of TensorFlow library.
TensorFlow is an open source software library for numerical computation
using data flow graphs.
Base CL: 107276108
Diffstat (limited to 'tensorflow/python/lib/core')
-rwxr-xr-x | tensorflow/python/lib/core/__init__.py | 0 | ||||
-rw-r--r-- | tensorflow/python/lib/core/pywrap_status_test.py | 35 | ||||
-rw-r--r-- | tensorflow/python/lib/core/status.i | 116 | ||||
-rw-r--r-- | tensorflow/python/lib/core/status_helper.i | 16 | ||||
-rw-r--r-- | tensorflow/python/lib/core/strings.i | 94 |
5 files changed, 261 insertions, 0 deletions
diff --git a/tensorflow/python/lib/core/__init__.py b/tensorflow/python/lib/core/__init__.py new file mode 100755 index 0000000000..e69de29bb2 --- /dev/null +++ b/tensorflow/python/lib/core/__init__.py diff --git a/tensorflow/python/lib/core/pywrap_status_test.py b/tensorflow/python/lib/core/pywrap_status_test.py new file mode 100644 index 0000000000..000a784b6c --- /dev/null +++ b/tensorflow/python/lib/core/pywrap_status_test.py @@ -0,0 +1,35 @@ +"""Tests for SWIG wrapped brain::Status.""" + +from tensorflow.core.lib.core import error_codes_pb2 +from tensorflow.python import pywrap_tensorflow +from tensorflow.python.platform import googletest + + +class StatusTest(googletest.TestCase): + + def testDefaultOk(self): + status = pywrap_tensorflow.Status() + self.assertTrue(status.ok()) + + def testCodeAndMessage(self): + status = pywrap_tensorflow.Status(error_codes_pb2.INVALID_ARGUMENT, 'foo') + self.assertEqual(error_codes_pb2.INVALID_ARGUMENT, status.code()) + self.assertEqual('foo', status.error_message()) + + def testToString(self): + status = pywrap_tensorflow.Status() + # .ToString was remapped in the .swig file, hence will not work + # self.assertIn('OK', status.ToString()) + self.assertIn('OK', str(status)) + + def testException(self): + with self.assertRaises(pywrap_tensorflow.StatusNotOK) as context: + pywrap_tensorflow.NotOkay() + self.assertEqual(context.exception.code, error_codes_pb2.INVALID_ARGUMENT) + self.assertEqual(context.exception.error_message, 'Testing 1 2 3') + self.assertEqual(None, pywrap_tensorflow.Okay(), + 'Status wrapper should not return anything upon OK.') + + +if __name__ == '__main__': + googletest.main() diff --git a/tensorflow/python/lib/core/status.i b/tensorflow/python/lib/core/status.i new file mode 100644 index 0000000000..fddbc31e24 --- /dev/null +++ b/tensorflow/python/lib/core/status.i @@ -0,0 +1,116 @@ +// SWIG wrapper for lib::tensorflow::Status + +%include "tensorflow/python/platform/base.i" +%include "tensorflow/python/lib/core/strings.i" + +%apply int { tensorflow::error::Code }; // Treat the enum as an integer. + +%{ +#include "tensorflow/core/public/status.h" +%} + +%typemap(out, fragment="StatusNotOK") tensorflow::Status { + if ($1.ok()) { + $result = SWIG_Py_Void(); + } else { + RaiseStatusNotOK($1, $descriptor(tensorflow::Status*)); + SWIG_fail; + } +} + +%init %{ +// Setup the StatusNotOK exception class. +PyObject *pywrap_status = PyImport_ImportModuleNoBlock( + "tensorflow.python.pywrap_tensorflow"); +if (pywrap_status) { + PyObject *exception = PyErr_NewException( + "tensorflow.python.pywrap_tensorflow.StatusNotOK", + NULL, NULL); + if (exception) { + PyModule_AddObject(pywrap_status, "StatusNotOK", exception); // Steals ref. + } + Py_DECREF(pywrap_status); +} +%} + +%fragment("StatusNotOK", "header") %{ +#include "tensorflow/core/public/status.h" + +namespace { +// Initialized on the first call to RaiseStatusNotOK(). +static PyObject *StatusNotOKError = nullptr; + +inline void Py_DECREF_wrapper(PyObject *o) { Py_DECREF(o); } +typedef std::unique_ptr<PyObject, decltype(&Py_DECREF_wrapper)> SafePyObjectPtr; +SafePyObjectPtr make_safe(PyObject* o) { + return SafePyObjectPtr(o, Py_DECREF_wrapper); +} + +void RaiseStatusNotOK(const tensorflow::Status& status, swig_type_info *type) { + const int code = status.code(); + string fullmsg = status.ToString(); + + PyObject *exception = nullptr; + + // We're holding the Python GIL, so we don't need to synchronize + // access to StatusNotOKError with a Mutex of our own. + if (!StatusNotOKError) { + PyObject *cls = nullptr; + auto pywrap = make_safe(PyImport_ImportModule( + "tensorflow.python.pywrap_tensorflow")); + if (pywrap) { + cls = PyObject_GetAttrString(pywrap.get(), "StatusNotOK"); + } + if (!cls) { + cls = Py_None; + Py_INCREF(cls); + } + StatusNotOKError = cls; + } + + if (StatusNotOKError != Py_None) { + auto fullmsg_ptr = make_safe(_SwigString_FromString(fullmsg)); + auto exception_ptr = make_safe(PyObject_CallFunctionObjArgs( + StatusNotOKError, fullmsg_ptr.get(), NULL)); + exception = exception_ptr.get(); + if (exception) { + auto pycode = make_safe(PyInt_FromLong(static_cast<long>(code))); + auto pymsg = make_safe(_SwigString_FromString(status.error_message())); + auto pystatus = make_safe(SWIG_NewPointerObj( + SWIG_as_voidptr(new tensorflow::Status(status)), type, SWIG_POINTER_OWN)); + PyObject_SetAttrString(exception, "code", pycode.get()); + PyObject_SetAttrString(exception, "error_message", pymsg.get()); + PyErr_SetObject(StatusNotOKError, exception); + } + } + if (!exception) { + fullmsg = + ("could not construct StatusNotOK (original error " + " was: " + + fullmsg + ")"); + PyErr_SetString(PyExc_SystemError, fullmsg.c_str()); + } +} + +} // namespace +%} + +%ignoreall + +%unignore tensorflow; +%unignore tensorflow::lib; +%unignore tensorflow::Status; +%unignore tensorflow::Status::Status; +%unignore tensorflow::Status::Status(tensorflow::error::Code, StringPiece); +%unignore tensorflow::Status::~Status; +%unignore tensorflow::Status::code; +%unignore tensorflow::Status::ok; +%unignore tensorflow::Status::error_message; +%unignore tensorflow::Status::ToString; +%ignore tensorflow::Status::operator=; + +%rename(__str__) tensorflow::Status::ToString; + +%include "tensorflow/core/public/status.h" + +%unignoreall diff --git a/tensorflow/python/lib/core/status_helper.i b/tensorflow/python/lib/core/status_helper.i new file mode 100644 index 0000000000..2e01e79ebd --- /dev/null +++ b/tensorflow/python/lib/core/status_helper.i @@ -0,0 +1,16 @@ +// SWIG test helper for lib::tensorflow::Status + +%include "tensorflow/python/platform/base.i" +%import(module="tensorflow.python.pywrap_tensorflow") "tensorflow/python/lib/core/status.i" + +%inline %{ +#include "tensorflow/core/public/status.h" + +tensorflow::Status NotOkay() { + return tensorflow::Status(tensorflow::error::INVALID_ARGUMENT, "Testing 1 2 3"); +} + +tensorflow::Status Okay() { + return tensorflow::Status(); +} +%} diff --git a/tensorflow/python/lib/core/strings.i b/tensorflow/python/lib/core/strings.i new file mode 100644 index 0000000000..c88e426a54 --- /dev/null +++ b/tensorflow/python/lib/core/strings.i @@ -0,0 +1,94 @@ +// Wrapper functions to provide a scripting-language-friendly interface +// to our string libraries. +// +// NOTE: as of 2005-01-13, this SWIG file is not used to generate a pywrap +// library for manipulation of various string-related types or access +// to the special string functions (Python has plenty). This SWIG file +// should be %import'd so that other SWIG wrappers have proper access +// to the types in //strings (such as the StringPiece object). We may +// generate a pywrap at some point in the future. +// +// NOTE: (Dan Ardelean) as of 2005-11-15 added typemaps to convert Java String +// arguments to C++ StringPiece& objects. This is required because a +// StringPiece class does not make sense - the code SWIG generates for a +// StringPiece class is useless, because it releases the buffer set in +// StringPiece after creating the object. C++ StringPiece objects rely on +// the buffer holding the data being allocated externally. + +// NOTE: for now, we'll just start with what is needed, and add stuff +// as it comes up. + +%{ +#include "tensorflow/core/lib/core/stringpiece.h" +%} + +%typemap(typecheck) tensorflow::StringPiece = char *; +%typemap(typecheck) const tensorflow::StringPiece & = char *; + +// "tensorflow::StringPiece" arguments can be provided by a simple Python 'str' string +// or a 'unicode' object. If 'unicode', it's translated using the default +// encoding, i.e., sys.getdefaultencoding(). If passed None, a tensorflow::StringPiece +// of zero length with a NULL pointer is provided. +%typemap(in) tensorflow::StringPiece { + if ($input != Py_None) { + char * buf; + Py_ssize_t len; +%#if PY_VERSION_HEX >= 0x03030000 + /* Do unicode handling as PyBytes_AsStringAndSize doesn't in Python 3. */ + if (PyUnicode_Check($input)) { + buf = PyUnicode_AsUTF8AndSize($input, &len); + if (buf == NULL) + SWIG_fail; + } else { +%#elif PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION < 3 +%# error "Unsupported Python 3.x C API version (3.3 or later required)." +%#endif + if (PyBytes_AsStringAndSize($input, &buf, &len) == -1) { + // Python has raised an error (likely TypeError or UnicodeEncodeError). + SWIG_fail; + } +%#if PY_VERSION_HEX >= 0x03030000 + } +%#endif + $1.set(buf, len); + } +} + +// "const tensorflow::StringPiece&" arguments can be provided the same as +// "tensorflow::StringPiece", whose typemap is defined above. +%typemap(in) const tensorflow::StringPiece & (tensorflow::StringPiece temp) { + if ($input != Py_None) { + char * buf; + Py_ssize_t len; +%#if PY_VERSION_HEX >= 0x03030000 + /* Do unicode handling as PyBytes_AsStringAndSize doesn't in Python 3. */ + if (PyUnicode_Check($input)) { + buf = PyUnicode_AsUTF8AndSize($input, &len); + if (buf == NULL) + SWIG_fail; + } else { +%#elif PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION < 3 +%# error "Unsupported Python 3.x C API version (3.3 or later required)." +%#endif + if (PyBytes_AsStringAndSize($input, &buf, &len) == -1) { + // Python has raised an error (likely TypeError or UnicodeEncodeError). + SWIG_fail; + } +%#if PY_VERSION_HEX >= 0x03030000 + } +%#endif + temp.set(buf, len); + } + $1 = &temp; +} + +// C++ functions returning tensorflow::StringPiece will simply return bytes in Python, +// or None if the StringPiece contained a NULL pointer. +%typemap(out) tensorflow::StringPiece { + if ($1.data()) { + $result = PyString_FromStringAndSize($1.data(), $1.size()); + } else { + Py_INCREF(Py_None); + $result = Py_None; + } +} |