integrity sha512-On2N+BpYJ15xIC974QNVuYGMOlEVt4s0EOI3wwMqOmK1fdDY+FN/zltPV8vosq4ad4c/gJ1KHScUn/6AWIgiow==

fill-range@^7.0.1:
  version "7.0.1"
  resolved "https://registry.yarnpkg.com/fill-range/-/fill-range-7.0.1.tgz#1919a6a7c75fe38b2c7c77e5198535da9acdda40"
  integrity sha512-qOo9F+dMUmC2Lcb4BbVvnKJxTPjCm+RRpe4gDuGrzkL7mEVl/djYSu2OdQ2Pa302N4oqkSg9ir6jaLWJ2USVpQ==
  dependencies:

	ERROR_SERVICE_START_HANG                                                  syscall.Errno = 1070
	ERROR_INVALID_SERVICE_LOCK                                                syscall.Errno = 1071
	ERROR_SERVICE_MARKED_FOR_DELETE                                           syscall.Errno = 1072
	ERROR_SERVICE_EXISTS                                                      syscall.Errno = 1073

- Kubernetes cannot distinguish between GCE Zonal PDs and Regional PDs with the same name. To workaround this issue, precreate PDs with unique names. PDs that are dynamically provisioned do not encounter this issue. ([#70716](https://github.com/kubernetes/kubernetes/pull/70716), [@msau42](https://github.com/msau42))

## Known Issues

			t.Errorf("stdin.Close: %v", err)
		}
	}()

	if err := cmd.Wait(); err == nil {
		t.Fatalf("Wait: succeeded unexpectedly")
	}
}

// Issue 5071
func TestPipeLookPathLeak(t *testing.T) {
	if runtime.GOOS == "windows" {
		t.Skip("we don't currently suppore counting open handles on windows")
	}
	// Not parallel: checks for leaked file descriptors

	{"1.1µs", 1100 * Nanosecond},
	{"2.2ms", 2200 * Microsecond},
	{"3.3s", 3300 * Millisecond},
	{"4m5s", 4*Minute + 5*Second},
	{"4m5.001s", 4*Minute + 5001*Millisecond},
	{"5h6m7.001s", 5*Hour + 6*Minute + 7001*Millisecond},
	{"8m0.000000001s", 8*Minute + 1*Nanosecond},
	{"2562047h47m16.854775807s", 1<<63 - 1},
	{"-2562047h47m16.854775808s", -1 << 63},
}

func TestDurationString(t *testing.T) {

  // Test Rank 3.
  // CHECK: %[[SHAPE1:.*]] = "tf.Shape"
  %7 = "tf.Shape"(%arg1) : (tensor<?x1x2xf32>) -> tensor<3xi32>
  %8 = "tf.StridedSlice"(%7, %0, %1, %1) {shrink_axis_mask = 1 : i64} : (tensor<3xi32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<i32>
  %9 = "tf.Pack"(%8, %d1, %d2) {axis = 0 : i64} : (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<3xi32>

	{1.4932076393918112, -2.2248022430460833e-308, 4.449875571054211e-308, 1.127783865601762e-308},

	// Overflow
	{-2.288020632214759e+38, -8.98846570988901e+307, 1.7696041796300924e+308, Inf(0)},
	{1.4888652783208255e+308, -9.007199254742012e+15, -6.807282911929205e+38, Inf(-1)},
	{9.142703268902826e+192, -1.3504889569802838e+296, -1.9082200803806996e-89, Inf(-1)},

	MOVD	$700, R12
	B	runtime·callbackasm1(SB)
	MOVD	$701, R12
	B	runtime·callbackasm1(SB)
	MOVD	$702, R12
	B	runtime·callbackasm1(SB)
	MOVD	$703, R12
	B	runtime·callbackasm1(SB)
	MOVD	$704, R12
	B	runtime·callbackasm1(SB)
	MOVD	$705, R12
	B	runtime·callbackasm1(SB)
	MOVD	$706, R12
	B	runtime·callbackasm1(SB)
	MOVD	$707, R12
	B	runtime·callbackasm1(SB)
	MOVD	$708, R12

	MOVW	$700, R12
	B	runtime·callbackasm1(SB)
	MOVW	$701, R12
	B	runtime·callbackasm1(SB)
	MOVW	$702, R12
	B	runtime·callbackasm1(SB)
	MOVW	$703, R12
	B	runtime·callbackasm1(SB)
	MOVW	$704, R12
	B	runtime·callbackasm1(SB)
	MOVW	$705, R12
	B	runtime·callbackasm1(SB)
	MOVW	$706, R12
	B	runtime·callbackasm1(SB)
	MOVW	$707, R12
	B	runtime·callbackasm1(SB)
	MOVW	$708, R12

func.func @dot_general_srq_arg_transpose_rhs(%arg0: tensor<1x3x!quant.uniform<i8:f32, 5.000000e+00:-128>>, %arg1: tensor<2x3x!quant.uniform<i8:f32, 3.000000e+00>>) -> tensor<1x2x!quant.uniform<i8:f32, 4.000000e+00:7>> {
  %1 = stablehlo.transpose %arg1, dims = [1, 0] : (tensor<2x3x!quant.uniform<i8:f32, 3.000000e+00>>) -> tensor<3x2x!quant.uniform<i8:f32, 3.000000e+00>>