if (VLOG_IS_ON(2)) {
      tensorflow::tf2xla::internal::EnablePassIRPrinting(bridge,
                                                         kBridgeComponent);
    }
  }
  LogicalResult result = bridge.run(module);
  (void)result;
  if (enable_logging || VLOG_IS_ON(1))
    tensorflow::DumpMlirOpToFile(kStandardPipelineAfter, module, "", &bridge);
  return diag_handler.ConsumeStatus();
}

{
  "cniVersion": "0.4.0",
  "name": "dbnet",
  "type": "bridge",
  "bridge": "cni0",
  "ipam": {
    "type": "host-local",
    "subnet": "10.1.0.0/16",
    "gateway": "10.1.0.1"
  },
  "dns": {
    "nameservers": [ "10.1.0.1" ]
  }

Mason Chang <******@****.***> 1698187099 -0700

{
  "cniVersion": "0.3.1",
  "name": "k8s-pod-network",
  "plugins": [
    {
      "bridge": "cni0",
      "dns": {
        "nameservers": [
          "10.1.0.1"
        ]
      },
      "ipam": {
        "gateway": "10.1.0.1",
        "subnet": "10.1.0.0/16",
        "type": "host-local"
      },
      "name": "dbnet",
      "type": "bridge"
    },
    {
      "ambient_enabled": false,
      "cni_event_address": "",

        "hook registration library.");
  }

  PassManager bridge(module.getContext());
  bridge.enableVerifier();
  ::tensorflow::applyTensorflowAndCLOptions(bridge);

  // Populate a passmanager with the list of passes that implement the bridge.
  pipeline_builder(bridge);

  mlir::StatusScopedDiagnosticHandler diag_handler(
      module.getContext(), /*propagate=*/false,
      /*filter_stack=*/!VLOG_IS_ON(1));

# Enable MLIR-Based new TPU Bridge

**MLIR-Based new TPU Bridge is an experimental feature, tread lightly.**

## For TF 1.x-Based Models

In tf.ConfigProto.Experimental, there is a knob controlling whether the new TPU
Bridge is enabled or not. You can set it by using the following example code:

```
session_config = tf.ConfigProto(
  ......
  experimental=tf.ConfigProto.Experimental(
    enable_mlir_bridge=True,
  ),
  ......
)
```

			chainedCNIPlugin:  true,
			specifiedConfName: "bridge.conflist",
			expectedConfName:  "bridge.conf",
			existingConfFiles: []string{"bridge.conf", "list.conflist"},
		},
		{
			name:              "specified delayed CNI config file",
			chainedCNIPlugin:  true,
			specifiedConfName: "bridge.conf",
			delayedConfName:   "bridge.conf",
			expectedConfName:  "bridge.conf",
		},
		{

        XcodePropertyAdapter.adapterCommandLine == [
                '-Porg.gradle.internal.xcode.bridge.ACTION="${ACTION}"',
                '-Porg.gradle.internal.xcode.bridge.PRODUCT_NAME="${PRODUCT_NAME}"',
                '-Porg.gradle.internal.xcode.bridge.CONFIGURATION="${CONFIGURATION}"',
                '-Porg.gradle.internal.xcode.bridge.BUILT_PRODUCTS_DIR="${BUILT_PRODUCTS_DIR}"',
        ]
    }

enum class MlirBridgeRolloutPolicy {
  // The MLIR bridge is explicitly disabled by the user and must not be run.
  kDisabledByUser = 0,
  // The MLIR bridge is explicitly enabled by the user and must be run. If the
  // MLIR bridge errors, the fallback path should NOT be used.
  kEnabledByUser,
  // The bridge was not explicitly enabled or disabled by the user. Based on the
  // features in the model, the MLIR bridge should not be run.

        "hook registration library.");
  }

  PassManager bridge(module.getContext());
  bridge.enableVerifier();
  ::tensorflow::applyTensorflowAndCLOptions(bridge);

  // Populate a passmanager with the list of passes that implement the bridge.
  pipeline_builder(bridge);

  mlir::StatusScopedDiagnosticHandler diag_handler(
      module.getContext(), /*propagate=*/false,
      /*filter_stack=*/!VLOG_IS_ON(1));

  if (VLOG_IS_ON(1) ||