- functions and classes in `tf.contrib` - functions and classes whose names start with `_` (as these are private) Note that the code in the `examples/` and `tools/` directories is not reachable through the `tensorflow` Python module and is thus not covered by the compatibility guarantee...
必须使用 TensorFlow2.0 的代码升级工具进行转换：tensorflow/tensorflow/tools/compatibility/tf_upgrade_v2...
The team is working to reduce the time window between a Python version and the time TF supports it, but support cannot be added after the branch was cut. 👍1👀1 mihaimaruseacmentioned this on Oct 5, 2023 Compatibility with Python 3.12.0 #62049 plopresti commented on Oct 5, 2023 ...
TensorFlow v2.0 is compatible with Python 3.5 - 3.7. For more information, please take a look at the tested build configurations. . Please verify with this [comment](Please post output of python --version, python -m pip --version and python -m pip install -vvv tensorflow) for compatibilit...
Only steps 1-4 in the TensorRT Tar File installation instructions are required for compatibility with TensorFlow; the Python package installation in steps 5 and 6 can be omitted. Detailed installation instructions can be found at [package documentataion](https://github.com/tensorflow/tensorflow/tree...
3.6/site-packages/tensorflow_core/python/framework/importer.py in _import_graph_def_internal(graph_def, input_map, return_elements, validate_colocation_constraints, name, op_dict, producer_op_list) 503 except errors.InvalidArgumentError as e: 504 # Convert to ValueError for backwards compatibility...
{ "name": "TfFoldConstants", "status": "effective", "speedup": "na", "pre_run": "na", "post_run": "na" } ], "overall": { "baseline": "6.98 ms", "optimized": "2.11 ms", "speedup": "3.31" }, "model_info": { "input_format": "frozen_pb" }, "compatibility_list": ...
TensorFlow provides stable Python API and C APIs as well as without API backwards compatibility guarantee like C++, Go, Java, JavaScript and Swift. Keep up to date with release announcements and security updates by subscribing toannounce@tensorflow.org. ...
断点兼容性 Checkpoint compatibility TensorFlow 2.0 使用了基于对象的断点。 旧版本的基于name的断点仍旧可以被加载,如果你在意的话。代码迁移过程也许会造成变量名的变动,但是这里有一些变通的解决之道。 最简单的方法是列出新模型的 names 和断点中的 names: 变量们仍旧有着可设置的name参数 Keras 模型接受name参数...
TensorFlow 1.15 has been patched for compatibility with numpy 1.21.1, and the numpy version has been updated to that version. With older numpy releases, certain matrix operations resulted in NaN and Inf values on ARM SBSA. Announcements NVIDIA Deep Learning Profiler (DLProf) v1.8, which wa...