---

### 🛠 **Seamless IDE & CI Integration**

Gradle is built to work smoothly with a variety of Integrated Development Environments (IDEs) and Continuous Integration (CI) systems, providing extensive support for a streamlined workflow:

just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After

        `tf.config.experimental.enable_tensor_float_32_execution(False)`.
    *   The byte layout for string tensors across the C-API has been updated to
        match TF Core/C++; i.e., a contiguous array of
        `tensorflow::tstring`/`TF_TString`s.
    *   C-API functions `TF_StringDecode`, `TF_StringEncode`, and
        `TF_StringEncodedSize` are no longer relevant and have been removed; see

# LINUX ARM64 PYCPP
# In Linux Arm64 presubmit/continuous build, we cross-compile the binaries on
# Linux x86 so that we can use RBE. Since tests still need to run on the single
# host Arm64 machine, the build becomes too slow (~30 min) to be a presubmit.

Capitalized}`]);\n  const popperBorderSide = parseFloat(css[`border${sideCapitalized}Width`]);\n  let sideValue =\n    center - data.offsets.popper[side] - popperMarginSide - popperBorderSide;\n\n  // prevent arrowElement from being placed not contiguously to its popper\n  sideValue = Math.max(Math.min(popper[len] - arrowElementSize, sideValue), 0);\n\n  data.arrowElement = arrowElement;\n  data.offsets.arrow = {\n    [side]: Math.round(sideValue),\n    [altSide]: '', // make sure to unset any eventual...