//tensorflow/python:extra_py_tests_deps
//tensorflow/python:mixed_precision
//tensorflow/python:tf_optimizer
//tensorflow/python:compare_test_proto_py
//tensorflow/python/framework:test_ops_2
//tensorflow/python/framework:test_file_system.so
//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib

```bash
clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc
diff <my_cc_file> /tmp/my_cc_file.cc
```

#### Python coding style

Changes to TensorFlow Python code should conform to
[Google Python Style Guide](https://github.com/google/styleguide/blob/gh-pages/pyguide.md)

Use `pylint` to check your Python changes. To install `pylint` and check a file
with `pylint` against TensorFlow's custom style definition:

```bash

# Install Python 3.
RUN Invoke-WebRequest "https://www.python.org/ftp/python/3.10.4/python-3.10.4-amd64.exe" \
        -OutFile C:/TEMP/python_install.exe -UseBasicParsing; \
    Start-Process C:/TEMP/python_install.exe -ArgumentList "/quiet", "/log", "C:/TEMP/python_install_log.txt", \
        "InstallAllUsers=1", "PrependPath=1" -wait; \
    Remove-Item C:/TEMP/python_install.exe; \

//tensorflow/core/kernels/cloud:bigquery_reader_ops
//tensorflow/python:extra_py_tests_deps
//tensorflow/python:mixed_precision
//tensorflow/python:tf_optimizer
//tensorflow/python:compare_test_proto_py
//tensorflow/python/framework:test_file_system.so
//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib

    ],
)

# -----------------------------------------------------------------------------
# Python API target

tf_cuda_library(
    name = "python_api",
    srcs = ["python_api.cc"],
    hdrs = ["python_api.h"],
    visibility = ["//tensorflow/python:__pkg__"],
    deps = [
        ":c_api",
        ":c_api_internal",
        "//tensorflow/core:protos_all_cc",

commands.

*Nightly binaries are available for testing using the
[tf-nightly](https://pypi.python.org/pypi/tf-nightly) and
[tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) packages on PyPi.*

#### *Try your first TensorFlow program*

```shell
$ python
```

```python
>>> import tensorflow as tf
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')

// "vspace" because a subset of these are related to a vector space, such as
// adding gradients, getting zeroes, etc. Currently cannot be implemented
// without using tensorflow python code, hence left unspecified here.
//
// Gradient is the type returned by gradient functions. In Python TF it's either
// Tensor or IndexedSlices or None, which here we map to nullptr. Gradients need
// to allow their size to be computed and they need to be passable to a backward

namex==0.0.7 \
    --hash=sha256:84ba65bc4d22bd909e3d26bf2ffb4b9529b608cb3f9a4336f776b04204ced69b \
    --hash=sha256:8a4f062945f405d77cb66b907f16aa2fd83681945e998be840eb6c4154d40108
    # via keras-nightly
numpy==1.23.5 ; python_version <= "3.11" \
    --hash=sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d \
    --hash=sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07 \

          "GraphOperation::Reset must be called before calling SetOpName.");
    }
    // TODO(b/145674566): We use Graph::NewName to get a unique name here but
    // this may not be consistent with python's naming policy.
    mutex_lock l(g_->mu);
    op_.reset(new TF_OperationDescription(g_, op_type_.c_str(),
                                          g_->graph.NewName(op_name).c_str()));
    return absl::OkStatus();
  }

                                                    TF_Status* status);
// Get an attribute type given an op name; a fusion of TFE_NewOp and
// TFE_OpGetAttrType for use from Python without the overhead of the individual
// calls and memory management of TFE_Op.
TF_CAPI_EXPORT extern TF_AttrType TFE_OpNameGetAttrType(
    TFE_Context* ctx, const char* op_or_function_name, const char* attr_name,