首先介绍数据读取问题，现在TensorFlow官方推荐的数据读取方法是使用tf.data.Dataset，具体的细节不在这里赘述，看官方文档更清楚，这里主要记录一下官方文档没有提到的坑，以示"

If you are batching your data for training, you can optimize performance using the dataset_map_and_batch() function (which fuses together the map and batch operations). For example: dataset <- dataset %>% dataset_map_and_batch ( batch_size = 128 , function (record) { record $ Species <- tf $ one_hot (record $ Species, 3L) record }) %>% datset_prefetch ( 1 )

apply (tf. data. experimental. map_and_batch (map_func = parser, batch_size = batch_size, num_parallel_calls = config. NUM_DATA_WORKERS)) dataset = dataset. prefetch (batch_size) return dataset API documentation for the Rust `MapAndBatchDataset` struct in crate `tensorflow`. dataset_map_and_batch() Fused implementation of dataset_map() and dataset_batch() dataset_prepare() Prepare a dataset for analysis.

Tensorflow map_and_batch

If keepdims is true, the reduced dimensions are retained with length 1. Se hela listan på tensorflow.org 2021-03-24 · map_and_batch; parallel_interleave; parse_example_dataset; prefetch_to_device; rejection_resample; sample_from_datasets; save; scan; shuffle_and_repeat; snapshot; take_while; to_variant; unbatch; unique 为此，tf.data 提供了 tf.contrib.data.map_and_batch 函数，其高效地融合了 map、batch 两个变换。为了融合 map 和 batch 两个变换，我们只需要将： dataset = dataset . map ( map_func = parse_fn , num_parallel_calls = FLAGS . num_parallel_calls ) dataset = dataset . batch ( batch_size = FLAGS . batch_size ) The method for reading data from a TensorFlow Dataset varies depending upon which API you are using to build your models.

dataset_skip() Creates a dataset that skips count elements from this dataset. dataset_filter() Filter a dataset by a predicate. dataset_shard() Creates a dataset that includes only 1 / num_shards of this dataset.

Pre-trained models and datasets built by Google and the community

NUM_DATA_WORKERS)) dataset = dataset. prefetch (batch_size) return dataset API documentation for the Rust `MapAndBatchDataset` struct in crate `tensorflow`.

2018年9月2日为了这个目的， tf.data API 提供了 tf.contrib.data.map_and_batch 变化，它有效地融合了map 和batch 变化。为了使用这个变换，将：

Feeding，在TensorFlow程序运行的每一步，让Python代码来供给数据。 2. 从文件读取数据：在TensorFlow图的起始，让一个输入管线从文件中读取数据。 3. 预加载数据：在TensorFlow图中定义常量或变量来保存所有数据(仅适用于数据量比较小的情况)。 tensorflow python API Mirror.

Record operations for automatic differentiation. 2018-02-24 python tensorflow. 158 tf. tf tf.AggregationMethod tf.argsort tf.autodiff tf.autodiff.ForwardAccumulator tf.batch_to_space tf.bitcast tf.boolean_mask tf.broadcast_dynamic_shape TensorFlow 1.8 - contrib.data.map_and_batch . tf.contrib.data.map_and_batch 解决思路 tensorflow版本问题导致的函数调用有变更。解决方法将 d = d.apply( tf.contrib.data.map_and_batch( lambda record: _decode_record(record, name_to_features), batch_size=batch_size, drop_ Which version of tensorflow your code ran? I ran it under version 1.14.0, but it has some traceback.
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tools.compatibility import renames_v2 “tf.data.experimental.map_and_batch”, 8 Jul 2018 set of instructions for installation, can be found on the TensorFlow API Installation Page: tf.contrib.data.map_and_batch(_parse_data, 100). 2018年7月13日 tf.contrib.data.map_and_batch( map_func, batch_size, num_parallel_batches= None, drop_remainder=False, num_parallel_calls=None )定义 Maps map_func across batch_size consecutive elements of this dataset and then combines them into a batch. Functionally, it is equivalent to map followed by 通常情况下，一个基于TensorFlow 的应用训练过程中所采用的workflow 如图1 所示。针对与原始数据 2、map_and_batch 整合了map和batch 过程，提高了效率. Code samples licensed under the Apache 2.0 License.

2 for a batch size of 2), which can result in Out Of Memory Segfaults. The reason this does not work is because every tensor passed through tf.shape when utilizing map_and_batch has the same shape even though the contents of the tensor does not. This is not the case when executing map and batch separately, the last batch has a shape returned from tf.shape that correctly matches the shape of the value. Computes the "logical or" of elements across dimensions of a tensor.
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When auto-tuning is active and the batch size is 1, fused map and batch schedules ctx->runner_threadpool_size() parallel applications of the map. For instance, on a DGX-1, 80 parallel calls of the map are invoked (vs. 2 for a batch size of 2), which can result in Out Of Memory Segfaults.

An Open Source Machine Learning Framework for Everyone - tensorflow/tensorflow. options. experimental_optimization.

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在整个机器学习过程中，除了训练模型外，应该就属数据预处理过程消耗的精力最多，数据预处理过程需要完成的任务包括数据读取、过滤、转换等等。为了将用户从繁杂的预处理操作中解放处理，更多地将精力放在算法建模上

此前，在TensorFlow中读取数据一般有两种方法：使用placeholder读内存中的数据出错：module 'tensorflow' has no attribute 'layers' 解决方法：由于已经安装的tensorflow是0.x的版本，0.x版本没有layers模块所以程序出错，需要重新安装tensorflow 1.0以上的版本，即更新tensorflow版本。查看目前tensorflow版本 pip list 显示：如下图，此时的tensorflow为0.12 1. Feeding，在TensorFlow程序运行的每一步，让Python代码来供给数据。 2. 从文件读取数据：在TensorFlow图的起始，让一个输入管线从文件中读取数据。 3. 预加载数据：在TensorFlow图中定义常量或变量来保存所有数据(仅适用于数据量比较小的情况)。 tensorflow python API Mirror. python tensorflow. 158 tf. tf tf.AggregationMethod tf.

Pre-trained models and datasets built by Google and the community

2018年9月2日 为了这个目的， tf.data API 提供了 tf.contrib.data.map_and_batch 变化，它有效地 融合了map 和batch 变化。 为了使用这个变换，将：

When auto-tuning is active and the batch size is 1, fused map and batch schedules ctx->runner_threadpool_size() parallel applications of the map. For instance, on a DGX-1, 80 parallel calls of the map are invoked (vs. 2 for a batch size of 2), which can result in Out Of Memory Segfaults.

2018年9月2日为了这个目的， tf.data API 提供了 tf.contrib.data.map_and_batch 变化，它有效地融合了map 和batch 变化。为了使用这个变换，将：