// If we don't clean that up there might be leftover json files from other report builds running on the same machine.
                                    """
                                    results/performance/build/test-results-*.zip!performance-tests/report/css/*.css => $performanceResultsDir/

  fi
fi
# VERY basic check to ensure the [and-cuda] package variant is installable.
# Checks TFCI_BAZEL_COMMON_ARGS for "gpu" or "cuda", implying that the test is
# relevant. All of the GPU test machines have CUDA installed via other means,
# so I am not sure how to verify that the dependencies themselves are valid for
# the moment.
if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then

{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)

		Can be repeated to define multiple symbols.
	-I dir1 -I dir2
		Search for #include files in dir1, dir2, etc,
		after consulting $GOROOT/pkg/$GOOS_$GOARCH.
	-S
		Print assembly and machine code.
	-V
		Print assembler version and exit.
	-debug
		Dump instructions as they are parsed.
	-dynlink
		Support references to Go symbols defined in other shared libraries.
	-e

	flag.BoolVar(&DebugV, "v", false, "print debug output")
	flag.Var(objabi.NewDebugFlag(&DebugFlags, nil), "d", "enable debugging settings; try -d help")
	objabi.AddVersionFlag() // -V
	objabi.Flagcount("S", "print assembly and machine code", &PrintOut)
}

// MultiFlag allows setting a value multiple times to collect a list, as in -I=dir1 -I=dir2.
type MultiFlag []string

func (m *MultiFlag) String() string {
	if len(*m) == 0 {
		return ""

    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

These "env" files match up with an environment matrix that roughly covers:

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

## How to Test Your Changes to TensorFlow

			// spurious blank caused by Split on "\n"
			output = output[1:]
			continue
		}
		t.Errorf("unexpected output: %q", output[0])
		output = output[1:]
	}

	// Checked printing.
	// Now check machine code layout.

	top := pList.Firstpc
	var text *obj.LSym
	ok = true
	ctxt.DiagFunc = func(format string, args ...interface{}) {
		t.Errorf(format, args...)
		ok = false
	}

# 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.
# For testing purposes, we want to see the runtime performance of an
# experimental job that is build-only, i.e, we only build the test targets and

    "article"
);
suggester.indexer().indexFromDocument(reader, 4, 50);
```

### Search Analytics

```java
// Track user queries for analytics
QueryLog userQuery = new QueryLog("machine learning tutorials", "user456");
suggester.indexer().indexFromQueryLog(userQuery);

// Get trending searches
PopularWordsResponse trending = suggester.popularWords()
    .setSize(10)
    .execute()