object Writer
Serializes tensors
This format is similar to the ONNX external tensor serialization format, but it uses JSON rather then protobuf.
Format specification
Sequences of tensors are serialized into a JSON descriptor and a data blob. The schema of the descriptor is the case class lamp.data.schemas.TensorList. The location field in this schema holds a path to the data blob. If this the location a relative POSIX then it is relative to the file path where the descriptor itself is written.
The descriptor may be embedded into larger JSON structures.
The data blob itself is the raw data in little endian byte order. Floating point is IEEE-754. The descriptor specifies the byte offset and byte length of the tensors inside the data blob. As such, the data blob contains no framing or other control bytes, but it may contain padding bytes between tensors.
Linear Supertypes
Ordering
- Alphabetic
- By Inheritance
Inherited
- Writer
- AnyRef
- Any
- Hide All
- Show All
Visibility
- Public
- All
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
equals(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- AnyRef → Any
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
- def writeCheckpoint[A, B](file: File, model: GenericModule[A, B], bufferSize: Int = 16384): IO[Either[String, Unit]]
- def writeTensorDataAndMakeDescriptor(tensors: Seq[STen], location: String, dataChannel: WritableByteChannel, bufferSize: Int): Either[String, TensorList]
-
def
writeTensorDataIntoChannel(tensors: Seq[STen], channel: WritableByteChannel, bufferSize: Int): Either[String, Seq[(Long, Long)]]
Returns list of (offset, length) in bytes
- def writeTensorsIntoFile(tensors: Seq[STen], file: File, bufferSize: Int = 16384): IO[Either[String, Unit]]