1 | /* Copyright 2022 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 | |
16 | #include <string> |
17 | #include <vector> |
18 | |
19 | #include "pybind11/pybind11.h" |
20 | #include "pybind11/stl.h" |
21 | #include "tensorflow/c/eager/c_api.h" |
22 | #include "tensorflow/dtensor/cc/dtensor_device.h" |
23 | #include "tensorflow/python/eager/pywrap_tensor.h" |
24 | #include "tensorflow/python/eager/pywrap_tfe.h" |
25 | #include "tensorflow/python/lib/core/pybind11_lib.h" |
26 | #include "tensorflow/python/lib/core/pybind11_status.h" |
27 | #include "tensorflow/python/lib/core/safe_pyobject_ptr.h" |
28 | #include "tensorflow/python/util/util.h" |
29 | |
30 | namespace py = ::pybind11; |
31 | using tensorflow::dtensor::AddMesh; |
32 | using tensorflow::dtensor::AllocateDTensorDevice; |
33 | using tensorflow::dtensor::ClearTPUCoreIDs; |
34 | using tensorflow::dtensor::ExperimentalClearDefaultLayout; |
35 | using tensorflow::dtensor::ExperimentalClearDefaultMesh; |
36 | using tensorflow::dtensor::ExperimentalSetDefaultLayout; |
37 | using tensorflow::dtensor::ExperimentalSetDefaultMesh; |
38 | using tensorflow::dtensor::FetchLayout; |
39 | using tensorflow::dtensor::GetFunctionCacheHitAndMissCount; |
40 | using tensorflow::dtensor::IsSparseDTensor; |
41 | using tensorflow::dtensor::Pack; |
42 | using tensorflow::dtensor::SetSameShapePolicy; |
43 | using tensorflow::dtensor::SetTPUCoreIDs; |
44 | using tensorflow::dtensor::SparsePack; |
45 | using tensorflow::dtensor::TPUCoreIDsToLocations; |
46 | using tensorflow::dtensor::TPUCoreLocationsToIDs; |
47 | using tensorflow::dtensor::Unpack; |
48 | |
49 | void PyXDecref(PyObject* obj) { Py_XDECREF(obj); } |
50 | |
51 | void CallDelete_Device(PyObject* capsule) { |
52 | delete reinterpret_cast<TFE_CustomDevice*>( |
53 | PyCapsule_GetPointer(capsule, "TFE_CustomDevice" )); |
54 | } |
55 | |
56 | void CallDelete_DeviceInfo(PyObject* capsule) { |
57 | void (*destructor)(void*) = |
58 | reinterpret_cast<void (*)(void*)>(PyCapsule_GetContext(capsule)); |
59 | destructor(PyCapsule_GetPointer(capsule, "TFE_CustomDevice_DeviceInfo" )); |
60 | } |
61 | |
62 | // Supports 2 cases: |
63 | // i) input is an EagerTensor. |
64 | // ii) input is an arbitrary python list/tuple. |
65 | void ConvertToTensor(TFE_Context* ctx, PyObject* input, |
66 | tensorflow::Safe_PyObjectPtr* output_handle, |
67 | TF_Status* status) { |
68 | if (EagerTensor_CheckExact(input)) { |
69 | // Input is already a EagerTensor so increment the reference, since the |
70 | // caller will use it through output_handle. |
71 | Py_INCREF(input); |
72 | output_handle->reset(input); |
73 | return; |
74 | } |
75 | TFE_TensorHandle* handle = |
76 | tensorflow::ConvertToEagerTensor(ctx, input, tensorflow::DT_INVALID); |
77 | if (handle == nullptr) { |
78 | TF_SetStatus(status, TF_INTERNAL, "Failure converting to eager tensor." ); |
79 | return; |
80 | } |
81 | output_handle->reset(EagerTensorFromHandle(handle)); |
82 | } |
83 | |
84 | PYBIND11_MODULE(_pywrap_dtensor_device, m) { |
85 | m.def("Allocate" , [](const std::string& name) { |
86 | TFE_CustomDevice* device = new TFE_CustomDevice; |
87 | std::unique_ptr<PyObject, decltype(&PyXDecref)> device_capsule( |
88 | PyCapsule_New(device, "TFE_CustomDevice" , &CallDelete_Device), |
89 | PyXDecref); |
90 | void* device_info; |
91 | AllocateDTensorDevice(name, device, &device_info); |
92 | std::unique_ptr<PyObject, decltype(&PyXDecref)> device_info_capsule( |
93 | PyCapsule_New(device_info, "TFE_CustomDevice_DeviceInfo" , |
94 | &CallDelete_DeviceInfo), |
95 | PyXDecref); |
96 | // The PyCapsule destructor needs a pointer to the destructor for |
97 | // DeviceInfo. |
98 | PyCapsule_SetContext(device_info_capsule.get(), |
99 | reinterpret_cast<void*>(device->delete_device)); |
100 | if (PyErr_Occurred()) throw py::error_already_set(); |
101 | return pybind11::reinterpret_steal<pybind11::object>( |
102 | PyTuple_Pack(2, device_capsule.get(), device_info_capsule.get())); |
103 | }); |
104 | m.def("AddMesh" , [](const py::capsule& device_info, |
105 | const std::string& serialized_mesh, bool is_async, |
106 | bool is_host_mesh) { |
107 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
108 | TF_NewStatus(), TF_DeleteStatus); |
109 | AddMesh( |
110 | serialized_mesh, |
111 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" ), |
112 | is_async, is_host_mesh, status.get()); |
113 | if (TF_GetCode(status.get()) != TF_OK) { |
114 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
115 | throw py::error_already_set(); |
116 | } |
117 | }); |
118 | m.def( |
119 | "ExperimentalSetDefaultLayout" , |
120 | [](const py::capsule& device_info, const std::string& serialized_layout) { |
121 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
122 | TF_NewStatus(), TF_DeleteStatus); |
123 | ExperimentalSetDefaultLayout( |
124 | serialized_layout, |
125 | PyCapsule_GetPointer(device_info.ptr(), |
126 | "TFE_CustomDevice_DeviceInfo" ), |
127 | status.get()); |
128 | if (TF_GetCode(status.get()) != TF_OK) { |
129 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
130 | throw py::error_already_set(); |
131 | } |
132 | }); |
133 | m.def("ExperimentalClearDefaultLayout" , [](const py::capsule& device_info) { |
134 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
135 | TF_NewStatus(), TF_DeleteStatus); |
136 | ExperimentalClearDefaultLayout( |
137 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" ), |
138 | status.get()); |
139 | if (TF_GetCode(status.get()) != TF_OK) { |
140 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
141 | throw py::error_already_set(); |
142 | } |
143 | }); |
144 | m.def("ExperimentalSetDefaultMesh" , [](const py::capsule& device_info, |
145 | const std::string& serialized_mesh) { |
146 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
147 | TF_NewStatus(), TF_DeleteStatus); |
148 | ExperimentalSetDefaultMesh( |
149 | serialized_mesh, |
150 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" ), |
151 | status.get()); |
152 | if (TF_GetCode(status.get()) != TF_OK) { |
153 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
154 | throw py::error_already_set(); |
155 | } |
156 | }); |
157 | m.def("ExperimentalClearDefaultMesh" , [](const py::capsule& device_info) { |
158 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
159 | TF_NewStatus(), TF_DeleteStatus); |
160 | ExperimentalClearDefaultMesh( |
161 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" ), |
162 | status.get()); |
163 | if (TF_GetCode(status.get()) != TF_OK) { |
164 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
165 | throw py::error_already_set(); |
166 | } |
167 | }); |
168 | m.def("SetSameShapePolicy" , [](const py::capsule& device_info, bool enabled) { |
169 | SetSameShapePolicy( |
170 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" ), |
171 | enabled); |
172 | }); |
173 | m.def("SetTPUCoreIDs" , [](const py::capsule& device_info, |
174 | const std::string& mesh_name, |
175 | const std::vector<int>& tpu_core_ids) { |
176 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
177 | TF_NewStatus(), TF_DeleteStatus); |
178 | SetTPUCoreIDs( |
179 | mesh_name, tpu_core_ids, |
180 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" ), |
181 | status.get()); |
182 | if (TF_GetCode(status.get()) != TF_OK) { |
183 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
184 | throw py::error_already_set(); |
185 | } |
186 | }); |
187 | m.def("ClearTPUCoreIDs" , [](const py::capsule& device_info) { |
188 | ClearTPUCoreIDs( |
189 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" )); |
190 | }); |
191 | m.def("TPUCoreIDsToLocations" , [](const py::handle& context, |
192 | const py::capsule& device_info, |
193 | const std::vector<int>& tpu_core_ids) { |
194 | return TPUCoreIDsToLocations( |
195 | static_cast<TFE_Context*>(PyCapsule_GetPointer(context.ptr(), nullptr)), |
196 | tpu_core_ids, |
197 | PyCapsule_GetPointer(device_info.ptr(), "TFE_CustomDevice_DeviceInfo" )); |
198 | }); |
199 | m.def("TPUCoreLocationsToIDs" , |
200 | [](const py::handle& context, const py::capsule& device_info, |
201 | const std::vector<std::vector<int>>& tpu_core_locations) { |
202 | return TPUCoreLocationsToIDs( |
203 | static_cast<TFE_Context*>( |
204 | PyCapsule_GetPointer(context.ptr(), nullptr)), |
205 | tpu_core_locations, |
206 | PyCapsule_GetPointer(device_info.ptr(), |
207 | "TFE_CustomDevice_DeviceInfo" )); |
208 | }); |
209 | m.def("Pack" , [](const py::handle& context, const py::handle& input_tensors, |
210 | const std::string& string_layout, |
211 | const py::capsule& device_info, const bool is_sparse) { |
212 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
213 | TF_NewStatus(), TF_DeleteStatus); |
214 | TFE_Context* ctx = |
215 | static_cast<TFE_Context*>(PyCapsule_GetPointer(context.ptr(), nullptr)); |
216 | // Convert each python object to safe py eagertensors. |
217 | std::vector<tensorflow::Safe_PyObjectPtr> py_eager_tensor_handles; |
218 | Py_ssize_t len = PyList_Size(input_tensors.ptr()); |
219 | py_eager_tensor_handles.resize(len); |
220 | |
221 | for (Py_ssize_t i = 0; i < len; ++i) { |
222 | PyObject* elem = PyList_GetItem(input_tensors.ptr(), i); |
223 | ConvertToTensor(ctx, elem, &py_eager_tensor_handles[i], status.get()); |
224 | |
225 | if (tensorflow::MaybeRaiseExceptionFromTFStatus(status.get(), nullptr)) |
226 | return tensorflow::PyoOrThrow(nullptr); |
227 | } |
228 | std::vector<TFE_TensorHandle*> input_vector; |
229 | input_vector.resize(len); |
230 | for (int i = 0; i < len; ++i) |
231 | input_vector[i] = EagerTensor_Handle(py_eager_tensor_handles[i].get()); |
232 | TFE_TensorHandle* packed_tensor; |
233 | if (is_sparse) { |
234 | auto size = input_vector.size() / 3; |
235 | packed_tensor = SparsePack( |
236 | ctx, |
237 | /*num_inputs=*/input_vector.size() / 3, |
238 | /*indices=*/ |
239 | std::vector<TFE_TensorHandle*>(input_vector.begin(), |
240 | input_vector.begin() + size) |
241 | .data(), |
242 | /*values=*/ |
243 | std::vector<TFE_TensorHandle*>(input_vector.begin() + size, |
244 | input_vector.begin() + 2 * size) |
245 | .data(), |
246 | /*shapes=*/ |
247 | std::vector<TFE_TensorHandle*>(input_vector.begin() + 2 * size, |
248 | input_vector.end()) |
249 | .data(), |
250 | string_layout, device_info, status.get()); |
251 | } else { |
252 | packed_tensor = Pack(ctx, input_vector.size(), input_vector.data(), |
253 | string_layout, device_info, status.get()); |
254 | } |
255 | if (tensorflow::MaybeRaiseExceptionFromTFStatus(status.get(), nullptr)) |
256 | return tensorflow::PyoOrThrow(nullptr); |
257 | // Convert c++ packed tensor handle into a python eager tensor object. |
258 | tensorflow::Safe_PyObjectPtr flat_result(PyList_New(1)); |
259 | PyList_SET_ITEM(flat_result.get(), 0, EagerTensorFromHandle(packed_tensor)); |
260 | auto* result = PyList_GET_ITEM(flat_result.get(), 0); |
261 | Py_INCREF(result); |
262 | return tensorflow::PyoOrThrow(result); |
263 | }); |
264 | m.def("Unpack" , [](const py::handle& context, |
265 | const py::handle& dtensor_handle, |
266 | const py::capsule& device_info) { |
267 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
268 | TF_NewStatus(), TF_DeleteStatus); |
269 | |
270 | TFE_TensorHandle* input_handle = EagerTensor_Handle(dtensor_handle.ptr()); |
271 | std::vector<TFE_TensorHandle*> unpacked_handles = Unpack( |
272 | static_cast<TFE_Context*>(PyCapsule_GetPointer(context.ptr(), nullptr)), |
273 | input_handle, device_info, status.get()); |
274 | |
275 | if (tensorflow::MaybeRaiseExceptionFromTFStatus(status.get(), nullptr)) |
276 | return tensorflow::PyoOrThrow(nullptr); |
277 | // Convert all TFE_TensorHandles to py EagerTensor and |
278 | // return a python list of them. |
279 | int num_outputs = unpacked_handles.size(); |
280 | PyObject* result(PyList_New(num_outputs)); |
281 | for (int i = 0; i < num_outputs; ++i) { |
282 | PyList_SET_ITEM(result, i, EagerTensorFromHandle(unpacked_handles[i])); |
283 | } |
284 | return tensorflow::PyoOrThrow(result); |
285 | }); |
286 | m.def( |
287 | "FetchLayout" , |
288 | [](const py::handle& context, const py::handle& dtensor_handle, |
289 | const py::capsule& device_info) -> py::object { |
290 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
291 | TF_NewStatus(), TF_DeleteStatus); |
292 | |
293 | std::string layout_string = |
294 | FetchLayout(static_cast<TFE_Context*>( |
295 | PyCapsule_GetPointer(context.ptr(), nullptr)), |
296 | EagerTensor_Handle(dtensor_handle.ptr()), device_info, |
297 | status.get()); |
298 | if (tensorflow::MaybeRaiseExceptionFromTFStatus(status.get(), nullptr)) |
299 | return tensorflow::PyoOrThrow(nullptr); |
300 | return tensorflow::PyoOrThrow( |
301 | PyUnicode_FromString(layout_string.c_str())); |
302 | }); |
303 | m.def("IsSparseDTensor" , [](const py::handle& context, |
304 | const py::handle& dtensor_handle, |
305 | const py::capsule& device_info) { |
306 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
307 | TF_NewStatus(), TF_DeleteStatus); |
308 | |
309 | TFE_TensorHandle* input_handle = EagerTensor_Handle(dtensor_handle.ptr()); |
310 | bool is_sparse = IsSparseDTensor( |
311 | static_cast<TFE_Context*>(PyCapsule_GetPointer(context.ptr(), nullptr)), |
312 | input_handle, device_info, status.get()); |
313 | |
314 | if (TF_GetCode(status.get()) != TF_OK) { |
315 | PyErr_SetString(PyExc_ValueError, TF_Message(status.get())); |
316 | throw py::error_already_set(); |
317 | } |
318 | return is_sparse; |
319 | }); |
320 | m.def("GetFunctionCacheHitAndMissCount" , [](const py::handle& context, |
321 | const py::capsule& device_info) { |
322 | std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( |
323 | TF_NewStatus(), TF_DeleteStatus); |
324 | return GetFunctionCacheHitAndMissCount( |
325 | static_cast<TFE_Context*>(PyCapsule_GetPointer(context.ptr(), nullptr)), |
326 | device_info, status.get()); |
327 | }); |
328 | } |
329 | |