@Namespace(value="tensorflow::ops") @NoOffset public static class tensorflow.Fill extends Pointer
dims and fills it with value.
For example:
# Output tensor has shape [2, 3].
fill([2, 3], 9) ==> [[9, 9, 9]
[9, 9, 9]]
tf.fill differs from tf.constant in a few ways:
* tf.fill only supports scalar contents, whereas tf.constant supports
Tensor values.
* tf.fill creates an Op in the computation graph that constructs the actual
Tensor value at runtime. This is in contrast to tf.constant which embeds
the entire Tensor into the graph with a Const node.
* Because tf.fill evaluates at graph runtime, it supports dynamic shapes
based on other runtime Tensors, unlike tf.constant.
Arguments:
* scope: A Scope object
* dims: 1-D. Represents the shape of the output tensor.
* value: 0-D (scalar). Value to fill the returned tensor.
\compatibility(numpy)
Equivalent to np.full
\end_compatibility
Returns:
* Output: The output tensor.Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator| Constructor and Description |
|---|
Fill(Pointer p)
Pointer cast constructor.
|
Fill(tensorflow.Scope scope,
tensorflow.Input dims,
tensorflow.Input value) |
| Modifier and Type | Method and Description |
|---|---|
tensorflow.Input |
asInput() |
tensorflow.Output |
asOutput() |
tensorflow.Node |
node() |
tensorflow.Operation |
operation() |
tensorflow.Fill |
operation(tensorflow.Operation operation) |
tensorflow.Output |
output() |
tensorflow.Fill |
output(tensorflow.Output output) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zeropublic Fill(Pointer p)
Pointer.Pointer(Pointer).public Fill(@Const @ByRef tensorflow.Scope scope, @ByVal tensorflow.Input dims, @ByVal tensorflow.Input value)
@ByVal @Name(value="operator tensorflow::Output") public tensorflow.Output asOutput()
@ByVal @Name(value="operator tensorflow::Input") public tensorflow.Input asInput()
public tensorflow.Node node()
@ByRef public tensorflow.Operation operation()
public tensorflow.Fill operation(tensorflow.Operation operation)
@ByRef public tensorflow.Output output()
public tensorflow.Fill output(tensorflow.Output output)
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