mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],

    {{- end }}
  {{ end -}}
  {{- if eq (annotation .ObjectMeta `sidecar.istio.io/enableCoreDump` .Values.global.proxy.enableCoreDump) "true" }}
  - name: enable-core-dump
    args:
    - -c
    - sysctl -w kernel.core_pattern=/var/lib/istio/data/core.proxy && ulimit -c unlimited
    command:
      - /bin/sh
  {{- if contains "/" (annotation .ObjectMeta `sidecar.istio.io/proxyImage` .Values.global.proxy_init.image) }}

    {{- end }}
  {{ end -}}
  {{- if eq (annotation .ObjectMeta `sidecar.istio.io/enableCoreDump` .Values.global.proxy.enableCoreDump) "true" }}
  - name: enable-core-dump
    args:
    - -c
    - sysctl -w kernel.core_pattern=/var/lib/istio/data/core.proxy && ulimit -c unlimited
    command:
      - /bin/sh
  {{- if contains "/" (annotation .ObjectMeta `sidecar.istio.io/proxyImage` .Values.global.proxy_init.image) }}

#include "tensorflow/core/framework/cpp_shape_inference.pb.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/kernel_def.pb.h"
#include "tensorflow/core/framework/log_memory.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/partial_tensor_shape.h"
#include "tensorflow/core/framework/shape_inference.h"

//tensorflow/lite
//tensorflow/compiler/mlir/lite
//tensorflow/compiler/mlir/tfrt
//tensorflow/core/runtime_fallback
//tensorflow/core/tfrt
//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks
EOF

  # grep patterns for files and targets which don't need to be in the pip
  # package, ever.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/ heal drive_workers=100` .


```
~ mc admin config set alias/ heal

  gci-beta-55-8872-47-0:
  Date:           Nov 11, 2016
  Kernel:         ChromiumOS-4.4
  Kubernetes:     v1.4.5
  Docker:         v1.11.2
  Changelog (vs 55-8872-18-0)
    * Cherry-pick runc PR#608: Eliminate redundant parsing of mountinfo
    * Updated kubernetes to v1.4.5

Care should be taken when using vector instructions to ensure that they are available at
runtime.
To use vector instructions a machine must have both the vector facility (bit 129 in the
facility list) and kernel support.
Without kernel support a vector instruction will have no effect (it will be equivalent
to a <code>NOP</code> instruction).
</p>

<p>
Addressing modes:
</p>

<ul>

<li>

      [ -s "${CLUSTER_KUBECONFIG}" ] && break
      sleep 3
    done

    # Enable core dumps
    retry docker exec "${CLUSTER_NAME}"-control-plane bash -c "sysctl -w kernel.core_pattern=/var/lib/istio/data/core.proxy && ulimit -c unlimited"
  }

  # Now deploy the specified number of KinD clusters and
  # wait till they are provisioned successfully.
  declare -a DEPLOY_KIND_JOBS

reproducing the executable from it.  However, as a special exception,
the materials to be distributed need not include anything that is
normally distributed (in either source or binary form) with the major
components (compiler, kernel, and so on) of the operating system on
which the executable runs, unless that component itself accompanies
the executable.

  It may happen that this requirement contradicts the license