@app.route('/logout', methods=['GET'])
def logout():
    response = app.make_response(redirect(request.referrer))
    session.pop('user', None)
    return response

# a helper function for asyncio.gather, does not return a value


async def getProductReviewsIgnoreResponse(product_id, headers):
    getProductReviews(product_id, headers)

        def projectLock = workerLeaseService.getProjectLock(path("root"), path(":project"))
        def otherBuildAllProjectsLock = workerLeaseService.getAllProjectsLock(path("other"))
        def otherBuildProjectLock = workerLeaseService.getProjectLock(path("other"), path(":project"))

        given:
        assert !lockIsHeld(allProjectsLock)
        assert workerLeaseService.currentProjectLocks.empty

        when:

            if (lockingState.mustValidateLockState() && !lockingState.getLockedDependencies().isEmpty()) {
                // Invalid lock state, need to do a real resolution to gather locking failures
                return delegate.resolveGraph(resolveContext);
            }

    return %0 : tensor<2x3x2x2xf32>
  }
// CHECK: %[[GATHER:.+]] = "stablehlo.gather"(%[[ARG_0]], %[[ARG_1]]) {{.*}} : (tensor<3x4x2x!quant.uniform<i8:f32, {{.*}}>>, tensor<2x3x2xi32>) -> tensor<2x3x2x2x!quant.uniform<i8:f32, {{.*}}>>
// CHECK: %[[UNIFORM_QUANTIZE_0:.+]] = stablehlo.uniform_quantize %[[GATHER]] : tensor<2x3x2x2x!quant.uniform<i8:f32, {{.*}}>>

// (only `type` and one other matching field should be set at once).
type MetricSpec struct {
	// type is the type of metric source.  It should be one of "ContainerResource",
	// "External", "Object", "Pods" or "Resource", each mapping to a matching field in the object.
	// Note: "ContainerResource" type is available on when the feature-gate
	// HPAContainerMetrics is enabled

  // user-provided specs are appended.
  //
  // It should look like:
  //
  // specs {matcher {function_name {regex: ".*"}} method {static_range_ptq {}}}
  // specs {
  //   matcher {function_name {regex: "composite_conv.*"}}
  //   method {static_range_ptq {...}}}
  // }
  // specs {
  //   matcher {function_name {regex: "composite_dot_general_fn_1"}}
  //   method {no_quantization {}}
  // }

type DebugWriter struct {
	Writer                 io.Writer
	Namespace              string
	InternalDebugAllIstiod bool
}

func (s *DebugWriter) PrintAll(drs map[string]*discovery.DiscoveryResponse) error {
	// Gather the statuses before printing so they may be sorted
	mappedResp := map[string]string{}
	for id, dr := range drs {
		for _, resource := range dr.Resources {
			if s.InternalDebugAllIstiod {

// CHECK: return %[[XLA_CALL_MODULE:.*]] : tensor<2x3x2x2xi32>
// CHECK: }

// CHECK-LABEL: private @composite_gather_fn_1
// CHECK: %[[GATHER:.*]] = "stablehlo.gather"(%arg0, %arg1)
// CHECK: return %[[GATHER]] : tensor<2x3x2x2xi32>
// CHECK: }

// -----

// Test that the name of composite functions are deterministic. There are 3

  }
};

// Lowers ResizeNearestNeighbor to an indices computations with a gather along
// the combined spatial dimensions. Generating the indices along the
// width/height index could be used to gather along each of W and H dimension
// of the input image array. To reduce to a single gather, these indices are
// combined, so a single gather can be performed along the combined spatial
// dimensions.
//

// CHECK:            %[[VAL_0:.*]] = "tf.GatherNd"(%[[ARG_0]], %[[ARG_1]]) <{bad_indices_policy = ""}> : {{.*}} -> tensor<192x256xf16>
// CHECK:            return %[[VAL_0]]
// CHECK:         }
func.func @convert_gather(%arg0: tensor<147456xf16>, %arg1: tensor<192x256x1xi32>) -> tensor<192x256xf16> {
  %0 = "mhlo.gather"(%arg0, %arg1) {
    dimension_numbers = #mhlo.gather<
      collapsed_slice_dims = [0],