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Update generated Python Op docs.

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Change: 132225803
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A. Unique TensorFlower 2016-09-05 01:33:12 -08:00 committed by TensorFlower Gardener
parent 79fd8f205d
commit ecf5c9cd0d
2 changed files with 8 additions and 8 deletions
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8
tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.train.batch.md
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@ -15,7 +15,7 @@ with shape `[batch_size, x, y, z]`.
If `enqueue_many` is `True`, `tensors` is assumed to represent a batch of
examples, where the first dimension is indexed by example, and all members of
`tensor_list` should have the same size in the first dimension. If an input
`tensors` should have the same size in the first dimension. If an input
tensor has shape `[*, x, y, z]`, the output will have shape `[batch_size, x,
y, z]`. The `capacity` argument controls the how long the prefetching is
allowed to grow the queues.
@ -51,11 +51,11 @@ operations that depend on fixed batch_size would fail.
* <b>`tensors`</b>: The list or dictionary of tensors to enqueue.
* <b>`batch_size`</b>: The new batch size pulled from the queue.
* <b>`num_threads`</b>: The number of threads enqueuing `tensor_list`.
* <b>`num_threads`</b>: The number of threads enqueuing `tensors`.
* <b>`capacity`</b>: An integer. The maximum number of elements in the queue.
* <b>`enqueue_many`</b>: Whether each tensor in `tensor_list` is a single example.
* <b>`enqueue_many`</b>: Whether each tensor in `tensors` is a single example.
* <b>`shapes`</b>: (Optional) The shapes for each example. Defaults to the
inferred shapes for `tensor_list`.
inferred shapes for `tensors`.
* <b>`dynamic_pad`</b>: Boolean. Allow variable dimensions in input shapes.
The given dimensions are padded upon dequeue so that tensors within a
batch have the same shapes.

8
tensorflow/g3doc/api_docs/python/io_ops.md
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@ -2434,7 +2434,7 @@ with shape `[batch_size, x, y, z]`.
If `enqueue_many` is `True`, `tensors` is assumed to represent a batch of
examples, where the first dimension is indexed by example, and all members of
`tensor_list` should have the same size in the first dimension. If an input
`tensors` should have the same size in the first dimension. If an input
tensor has shape `[*, x, y, z]`, the output will have shape `[batch_size, x,
y, z]`. The `capacity` argument controls the how long the prefetching is
allowed to grow the queues.
@ -2470,11 +2470,11 @@ operations that depend on fixed batch_size would fail.
* <b>`tensors`</b>: The list or dictionary of tensors to enqueue.
* <b>`batch_size`</b>: The new batch size pulled from the queue.
* <b>`num_threads`</b>: The number of threads enqueuing `tensor_list`.
* <b>`num_threads`</b>: The number of threads enqueuing `tensors`.
* <b>`capacity`</b>: An integer. The maximum number of elements in the queue.
* <b>`enqueue_many`</b>: Whether each tensor in `tensor_list` is a single example.
* <b>`enqueue_many`</b>: Whether each tensor in `tensors` is a single example.
* <b>`shapes`</b>: (Optional) The shapes for each example. Defaults to the
inferred shapes for `tensor_list`.
inferred shapes for `tensors`.
* <b>`dynamic_pad`</b>: Boolean. Allow variable dimensions in input shapes.
The given dimensions are padded upon dequeue so that tensors within a
batch have the same shapes.