tf.contrib.layers.safe_embedding_lookup_sparse()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.safe_embedding_lookup_sparse(embedding_weights, sparse_ids, sparse_weights=None, combiner=None, default_id=None, name=None, partition_strategy='div')

2025-01-10 15:47:30
tf.contrib.layers.avg_pool2d()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.avg_pool2d(*args, **kwargs) Adds a 2D average pooling op. It is assumed that

2025-01-10 15:47:30
tf.contrib.layers.one_hot_encoding()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.one_hot_encoding(*args, **kwargs) Transform numeric labels into onehot_labels using tf.one_hot.

2025-01-10 15:47:30
tf.contrib.layers.summarize_tensor()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.summarize_tensor(tensor, tag=None) Summarize a tensor using a suitable summary type. This

2025-01-10 15:47:30
tf.contrib.layers.repeat()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.repeat(inputs, repetitions, layer, *args, **kwargs) Applies the same layer with the same arguments repeatedly

2025-01-10 15:47:30
tf.contrib.layers.apply_regularization()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.apply_regularization(regularizer, weights_list=None) Returns the summed penalty by applying regularizer

2025-01-10 15:47:30
tf.contrib.layers.separable_convolution2d()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.separable_convolution2d(*args, **kwargs) Adds a depth-separable 2D convolution with optional batch_norm layer

2025-01-10 15:47:30
tf.contrib.layers.unit_norm()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.unit_norm(*args, **kwargs) Normalizes the given input across the specified dimension to unit length.

2025-01-10 15:47:30
tf.contrib.layers.flatten()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.flatten(*args, **kwargs) Flattens the input while maintaining the batch_size. Assumes

2025-01-10 15:47:30
tf.contrib.layers.l1_regularizer()
  • References/Big Data/TensorFlow/TensorFlow Python/Layers

tf.contrib.layers.l1_regularizer(scale, scope=None) Returns a function that can be used to apply L1 regularization to weights

2025-01-10 15:47:30