Batches all input tensors nondeterministically.
When many instances of this Op are being run concurrently with the same container/shared_name in the same device, some will output zero-shaped Tensors and others will output Tensors of size up to max_batch_size.
All Tensors in in_tensors are batched together (so, for example, labels and features should be batched with a single instance of this operation.
Each invocation of batch emits an `id` scalar which will be used to identify this particular invocation when doing unbatch or its gradient.
Each op which emits a non-empty batch will also emit a non-empty batch_index Tensor, which, is a [K, 3] matrix where each row contains the invocation's id, start, and length of elements of each set of Tensors present in batched_tensors.
Batched tensors are concatenated along the first dimension, and all tensors in in_tensors must have the first dimension of the same size.
in_tensors: The tensors to be batched. num_batch_threads: Number of scheduling threads for processing batches of work. Determines the number of batches processed in parallel. max_batch_size: Batch sizes will never be bigger than this. batch_timeout_micros: Maximum number of microseconds to wait before outputting an incomplete batch. allowed_batch_sizes: Optional list of allowed batch sizes. If left empty, does nothing. Otherwise, supplies a list of batch sizes, causing the op to pad batches up to one of those sizes. The entries must increase monotonically, and the final entry must equal max_batch_size. grad_timeout_micros: The timeout to use for the gradient. See Unbatch. batched_tensors: Either empty tensors or a batch of concatenated Tensors. batch_index: If out_tensors is non-empty, has information to invert it. container: Controls the scope of sharing of this batch. id: always contains a scalar with a unique ID for this invocation of Batch. shared_name: Concurrently running instances of batch in the same device with the same container and shared_name will batch their elements together. If left empty, the op name will be used as the shared name. T: the types of tensors to be batched.
Nested Classes
| class | Batch.Options | Optional attributes for Batch
|
|
Constants
| String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
| static Batch.Options |
allowedBatchSizes(List<Long> allowedBatchSizes)
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| Output<TInt64> | |
| List<Output<?>> | |
| static Batch.Options |
batchingQueue(String batchingQueue)
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| static Batch.Options |
container(String container)
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| static Batch |
create(Scope scope, Iterable<Operand<?>> inTensors, Long numBatchThreads, Long maxBatchSize, Long batchTimeoutMicros, Long gradTimeoutMicros, Options... options)
Factory method to create a class wrapping a new Batch operation.
|
| Output<TInt64> |
id()
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| static Batch.Options |
maxEnqueuedBatches(Long maxEnqueuedBatches)
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| static Batch.Options |
sharedName(String sharedName)
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Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public static Batch create (Scope scope, Iterable<Operand<?>> inTensors, Long numBatchThreads, Long maxBatchSize, Long batchTimeoutMicros, Long gradTimeoutMicros, Options... options)
Factory method to create a class wrapping a new Batch operation.
Parameters
| scope | current scope |
|---|---|
| options | carries optional attributes values |
Returns
- a new instance of Batch