absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in
astunparse==1.6.3 \

navigate to the
[GitHub "issues" tab](https://github.com/tensorflow/tensorflow/issues) and start
looking through interesting issues. If you are not sure of where to start, then
start by trying one of the smaller/easier issues here i.e.
[issues with the "good first issue" label](https://github.com/tensorflow/tensorflow/labels/good%20first%20issue)
and then take a look at the

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in
astunparse==1.6.3 \

*   <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

*  Support for Python 3.12 has been added.
*  [tensorflow-tpu](https://pypi.org/project/tensorflow-tpu/) package is now
   available for easier TPU based installs.
*  TensorFlow pip packages are now built with CUDA 12.3 and cuDNN 8.9.7


### Bug Fixes and Other Changes

* <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>

      // TODO(nareshmodi): TFE_OpSetAttrFunction and TFE_OpSetAttrFunctionList
      // require TFE_Op* and just convert it internally a NameAttrValue, so
      // consider adding an overload to the C API to make this case easier.
      TFE_OpSetAttrFunction(op, attr_name, func_op);
      TFE_DeleteOp(func_op);
    } break;
    case tensorflow::AttrValue::kList: {
      // String

        ":with_tpu_support_define",
        ":with_tpu_support_flag",
    ],
    visibility = ["//visibility:public"],
)

# Specifies via a config setting if this is a mobile build or not, makes
# it easier to combine settings later.
selects.config_setting_group(
    name = "mobile",
    match_any = [
        ":android",
        ":chromiumos",

// does various checks while doing so. `input_nodes` will contain the same
// information as input_tensors just in a different structure to make
// following processing easier. TODO(iga): Simplify this nested structure.
Status ProcessInputs(
    const TF_Graph* fn_body, const char* fn_name, int ninputs,
    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in
astunparse==1.6.3 \

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in
astunparse==1.6.3 \