Runs a list of tensors to conditionally fill a queue to create batches. (deprecated)
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tf.train.maybe_batch_join(
tensors_list, keep_input, batch_size, capacity=32, enqueue_many=False,
shapes=None, dynamic_pad=False, allow_smaller_final_batch=False,
shared_name=None, name=None
)
See docstring in batch_join
for more details.
Args | |
---|---|
tensors_list
|
A list of tuples or dictionaries of tensors to enqueue. |
keep_input
|
A bool Tensor. This tensor controls whether the input is
added to the queue or not. If it is a scalar and evaluates True , then
tensors are all added to the queue. If it is a vector and enqueue_many
is True , then each example is added to the queue only if the
corresponding value in keep_input is True . This tensor essentially
acts as a filtering mechanism.
|
batch_size
|
An integer. The new batch size pulled from the queue. |
capacity
|
An integer. The maximum number of elements in the queue. |
enqueue_many
|
Whether each tensor in tensor_list_list is a single
example.
|
shapes
|
(Optional) The shapes for each example. Defaults to the
inferred shapes for tensor_list_list[i] .
|
dynamic_pad
|
Boolean. Allow variable dimensions in input shapes. The given dimensions are padded upon dequeue so that tensors within a batch have the same shapes. |
allow_smaller_final_batch
|
(Optional) Boolean. If True , allow the final
batch to be smaller if there are insufficient items left in the queue.
|
shared_name
|
(Optional) If set, this queue will be shared under the given name across multiple sessions. |
name
|
(Optional) A name for the operations. |
Returns | |
---|---|
A list or dictionary of tensors with the same number and types as
tensors_list[i] .
|
Raises | |
---|---|
ValueError
|
If the shapes are not specified, and cannot be
inferred from the elements of tensor_list_list .
|