{file: "myobject", offset: 2, length: 100, algorithm: SHA256, expError: errFileCorrupt},     // 6
	{file: "myobject", offset: 1000, length: 1001, algorithm: SHA256, expError: nil},            // 7
	{file: "myobject", offset: 0, length: 100, algorithm: BLAKE2b512, expError: errFileCorrupt}, // 8

func.func @prepareStatistics(%arg0: tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
  %0 = "quantfork.stats"(%arg0) {
    layerStats = dense<[-1.0, 1.0]> : tensor<2xf32>
  } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
  %1 = "quantfork.stats"(%0) {
    layerStats = dense<[-1.0, 1.0]> : tensor<2xf32>,
    axisStats = dense<[
      [-1.0, 1.0],
      [-8.0, 8.0],
      [-0.5, 0.5]
    ]> : tensor<3x2xf32>, axis = 2 : i64

  auto my_create_func = [](TF_OpKernelConstruction* ctx) {
    struct MyCustomKernel* s = new struct MyCustomKernel;
    s->created = true;
    s->compute_called = false;

    const unsigned char list[] = {1, 0, 1, 0};
    const size_t list_size = TF_ARRAYSIZE(list);
    unsigned char values[list_size];

    TF_Status* status = TF_NewStatus();
    EXPECT_TF_SIZE(/*attr_name*/ "Attr", /*expected_list_size*/ list_size,

      dilations: Sequence[int] = None,
      has_func_alias: bool = False,
  ):
    input_shape = (None, 3, 4, 3) if input_shape_dynamic else (1, 3, 4, 3)
    filter_shape = (2, 3, 3, 2)
    strides = (1, 1, 1, 1)
    model = self._create_conv2d_model(
        input_shape,
        filter_shape,
        self._input_saved_model_path,
        bias_fn,
        activation_fn,
        has_batch_norm,
        strides,

				},
			},
			ContainerStatuses: []corev1.ContainerStatus{
				{
					Name: "container-1",
				},
				{
					Name: "container-2",
				},
			},
			PodIP:  "1.1.1.1",
			HostIP: "1.1.1.1",
			Phase:  corev1.PodRunning,
		},
	}

	expectPod := &corev1.Pod{
		TypeMeta: metav1.TypeMeta{
			Kind:       "Pod",
			APIVersion: "v1",
		},

// Copyright 2011 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

//go:build !js

package pprof

import (
	"bytes"
	"context"
	"fmt"
	"internal/abi"
	"internal/profile"
	"internal/syscall/unix"
	"internal/testenv"
	"io"
	"math"
	"math/big"
	"os"
	"regexp"
	"runtime"
	"runtime/debug"
	"strings"
	"sync"

	rc, _ = newReplicationController(t, 1)
	rc.Name = "rc 2"
	for i := 0; i < podCount; i++ {
		updatePodOwnerToRc(t, pods[i], rc)
	}
	add(t, dc.rcStore, rc)
	dc.sync(ctx, pdbName)

	// 100%>1% healthy BUT two RCs => no disruption allowed
	// TODO: Find out if this assert is still needed
	//ps.VerifyDisruptionAllowed(t, pdbName, 0)
}

func TestReplicationController(t *testing.T) {

        background-color: var(--navbar-text-color);
    }
    button#navbar-toggle-button.expanded span.nav-bar-toggle-icon:nth-child(1) {
        transform: rotate(45deg);
        transform-origin: 10% 10%;
        width: 26px;
    }
    button#navbar-toggle-button.expanded span.nav-bar-toggle-icon:nth-child(2) {
        opacity: 0;
    }

//   original_input -> reshape -> strided_slice -> output
//
// And the new shape is computed based on the masks.
//
// An example for new_axis_mask. say the new_axis_mask is 9 which represents
// [1 0 0 1], and that means we're inserting two new axes at 0 & 3 dim, so
// if original shape is [2, 3], now we reshape that into [1, 2, 3, 1].
struct ConvertTFStridedSlice : public RewritePattern {

	{"-1", 0, 1},
	{"-1", 200, 1},
	{"0x2000000000000000000000000000", 108, 0},
	{"0x2000000000000000000000000000", 109, 1},
	{"0x2000000000000000000000000000", 110, 0},
	{"-0x2000000000000000000000000001", 108, 1},
	{"-0x2000000000000000000000000001", 109, 0},
	{"-0x2000000000000000000000000001", 110, 1},
}

func TestBitSet(t *testing.T) {
	for _, test := range bitwiseTests {
		x := new(Int)