Tfsa 2022 161

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,)