go build -compiler=gccgo -overlay overlay.json -o main_call_asm_gccgo$GOEXE ./call_asm
exec ./main_call_asm_gccgo$GOEXE
! stdout .


-- m/go.mod --
// TODO(matloob): how do overlays work with go.mod (especially if mod=readonly)
module m

go 1.16

-- m/dir2/h.go --
package dir2

func PrintMessage() {
	printMessage()
}
-- m/dir/foo.txt --

func TestReadGCStats(t *testing.T) {
	defer SetGCPercent(SetGCPercent(-1))

	var stats GCStats
	var mstats runtime.MemStats
	var min, max time.Duration

	// First ReadGCStats will allocate, second should not,
	// especially if we follow up with an explicit garbage collection.
	stats.PauseQuantiles = make([]time.Duration, 10)
	ReadGCStats(&stats)
	runtime.GC()

	// Assume these will return same data: no GC during ReadGCStats.

        Without this option being set they are stored in a static list using soft references which can lead to memory pressure and performance deterioration
        when using the daemon, especially when using small heap and building a large project.
        Due to a bug (https://builds.gradle.org/viewLog.html?buildId=284033&tab=buildResultsDiv&buildTypeId=Gradle_Master_Performance_PerformanceExperimentsLinux) no instances of

convolutions._

## Background

For image models, the first layer is usually not MXU friendly as it has a
feature size of 3. This results in poor performance especially with small batch.

One way to address this issue is to use the `space-to-depth` transform. This
optimization tiles the 2x2 space dimensions to the feature dimension so that the

}

public typealias KtEnumEntrySymbol = KaEnumEntrySymbol

/**
 * An initializer for enum entries with a body. The initializer may contain its own declarations (especially overrides of members declared
 * by the enum class), and is [similar to an object declaration](https://kotlinlang.org/spec/declarations.html#enum-class-declaration).
 *
 * #### Example
 *
 * ```kotlin

			// actual go.mod files. If we find actual examples of this form and a
			// reasonable theory of how they came into existence, it seems fine to
			// treat them as equivalent to vX.0.0 (especially since the invalid
			// pseudo-versions have lower precedence than the real ones). For now, we
			// reject them.
			return "", &InvalidVersionError{
				Version: v,
				Pseudo:  true,

#         * functions;
#         * expansions «$var», «${var}», «${var:-default}», «${var+SET}»,
#           «${var#prefix}», «${var%suffix}», and «$( cmd )»;
#         * compound commands having a testable exit status, especially «case»;
#         * various built-in commands including «command», «set», and «ulimit».
#
#   Important for patching:
#
#   (2) This script targets any POSIX shell, so it avoids extensions provided

* `read(size)`: Reads `size` (`int`) bytes/characters of the file.
* `seek(offset)`: Goes to the byte position `offset` (`int`) in the file.
    * E.g., `await myfile.seek(0)` would go to the start of the file.
    * This is especially useful if you run `await myfile.read()` once and then need to read the contents again.
* `close()`: Closes the file.

As all these methods are `async` methods, you need to "await" them.

  // Used in MLIR dynamic range quantizer.
  bool weight_only_quantization = false;

  // The minimum number of elements in a weights array required to apply
  // quantization. This is especially useful not to quantize small tensors as
  // it is hard to get performance benefits from them with quantization. Used
  // in MLIR dynamic range quantizer with int8 weight data type.
  int64_t minimum_elements_for_weights = 1024;

# Recommended: use a local+remote cache.
#
#   Bazel will cache your builds in tensorflow/build_output/cache,
#   and will also try using public build cache results to speed up
#   your builds. This usually saves a lot of time, especially when
#   re-running tests. However, note that:
#
#    - New environments like new CUDA versions, changes to manylinux,
#      compilers, etc. can cause undefined behavior such as build failures