America/Ojinaga America/Panama America/Pangnirtung America/Paramaribo America/Phoenix America/Port-au-Prince America/Port_of_Spain America/Porto_Acre America/Porto_Velho America/Puerto_Rico America/Punta_Arenas America/Rainy_River America/Rankin_Inlet America/Recife America/Regina America/Resolute America/Rio_Branco America/Rosario America/Santa_Isabel America/Santarem America/Santiago America/Santo_Domingo America/Sao_Paulo America/Scoresbysund America/Shiprock America/Sitka America/St_Barthelemy America/St_Johns...

if [[ "${TFCI_MACOS_BAZEL_TEST_DIR_ENABLE}" == 1 ]]; then
  mkdir -p "${TFCI_MACOS_BAZEL_TEST_DIR_PATH}"
  export TEST_TMPDIR="${TFCI_MACOS_BAZEL_TEST_DIR_PATH}"
fi

# "TFCI_MACOS_INSTALL_BAZELISK_ENABLE" is used to decide if we need to install
# Bazelisk manually. We enable this for macOS x86 builds as those VMs do not
# have Bazelisk pre-installed. "TFCI_MACOS_INSTALL_BAZELISK_URL" contains the

        // Test user boost
        item.setUserBoost(2.0f);
        assertEquals(2.0f, item.getUserBoost(), 0.001f);

        // Test readings
        String[][] newReadings = { { "read1", "read2" }, { "read3" } };
        item.setReadings(newReadings);
        assertArrayEquals(newReadings, item.getReadings());

        // Test fields
        String[] fields = { "field1", "field2" };

T0, $2, T0 XXPERMDI T1, T1, $2, T1 // First round VPERM T1, T0, SEL1, RED2 // d1 d0 d1 d0 VPERM ZER, RED2, SEL2, RED1 // 0 d1 d0 0 VSUBUQM RED2, RED1, RED2 // VSQ RED1, RED2, RED2 // Guaranteed not to underflow VSLDOI $8, T1, T0, T0 // VSLDB $8, T1, T0, T0 VSLDOI $8, T2, T1, T1 // VSLDB $8, T2, T1, T1 VADDCUQ T0, RED1, CAR1 // VACCQ T0, RED1, CAR1 VADDUQM T0, RED1, T0 // VAQ T0, RED1, T0 VADDECUQ T1, RED2, CAR1, CAR2 // VACCCQ T1, RED2, CAR1, CAR2 VADDEUQM T1, RED2, CAR1, T1 // VACQ T1, RED2, CAR1,...

These are issues that we believe are particularly well suited for outside
contributions, often because we probably won't get to them right now. If you
decide to start on an issue, leave a comment so that other people know that
you're working on it. If you want to help out, but not alone, use the issue
comment thread to coordinate.

### Contribution guidelines and standards

# the pip package on Windows without an intermediate data-file archive, as the
# build_pip_package script in its current form (as of Aug 2023) uses the
# runfiles symlink tree to decide what to put into the Python wheel.
startup --windows_enable_symlinks
build:windows --enable_runfiles
build:windows --nobuild_python_zip
build:windows --dynamic_mode=off

# Default paths for TF_SYSTEM_LIBS

	XVMODW		X3, X2, X1	// 410ce374
	XVMODV		X3, X2, X1	// 418ce374
	XVMODBU		X3, X2, X1	// 410ce674
	XVMODHU		X3, X2, X1	// 418ce674
	XVMODWU		X3, X2, X1	// 410ce774
	XVMODVU		X3, X2, X1	// 418ce774

	// [X]VF{SQRT/RECIP/RSQRT}{F/D} instructions
	VFSQRTF		V1, V2		// 22e49c72
	VFSQRTD		V1, V2		// 22e89c72
	VFRECIPF	V1, V2		// 22f49c72
	VFRECIPD	V1, V2		// 22f89c72
	VFRSQRTF	V1, V2		// 22049d72
	VFRSQRTD	V1, V2		// 22089d72

package, such as C.puts. It collects all such identifiers. The next
step is to determine each kind of name. In C.xxx the xxx might refer
to a type, a function, a constant, or a global variable. Cgo must
decide which.

The obvious thing for cgo to do is to process the preamble, expanding
#includes and processing the corresponding C code. That would require
a full C parser and type checker that was also aware of any extensions

    # Overriding eigen strong inline speeds up the compiling of
    # conv_grad_ops_3d.cc and conv_ops_3d.cc by 20 minutes,
    # but this also hurts the performance. Let users decide what they want.
    write_to_bazelrc('build --define=override_eigen_strong_inline=true')


def config_info_line(name, help_text):
  """Helper function to print formatted help text for Bazel config options."""

    change, but please check the
    [API doc](https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/experimental)
    if any API used in your workflow is changed or deprecated, and make
    adaptations. If you decide to keep using the old optimizer, please
    explicitly change your optimizer to `tf.keras.optimizers.legacy.Optimizer`.
*   RNG behavior change for `tf.keras.initializers`. Keras initializers will now