3. Poplar API reference¶
3.1. Utility classes¶
3.1.1. poplar/ArrayRef.hpp¶
References to arrays.
-
namespace
poplar
¶ Poplar classes and functions.
Functions
-
template<class
T
>
classArrayRef
¶ Subclassed by poplar::StringRef
Public Types
Public Functions
-
constexpr
ArrayRef
()¶
-
constexpr bool
empty
() const¶
-
const_iterator
begin
() const¶
-
const_iterator
end
() const¶
-
const_iterator
cbegin
() const¶
-
const_iterator
cend
() const¶
-
constexpr
-
template<class
3.1.2. poplar/Interval.hpp¶
-
namespace
poplar
Poplar classes and functions.
Typedefs
-
typedef GenericInterval<std::size_t>
Interval
¶
Functions
-
template<class
T
>
booloperator==
(const GenericInterval<T> &a, const GenericInterval<T> &b)¶
-
template<class
T
>
booloperator<
(const GenericInterval<T> &a, const GenericInterval<T> &b)¶
-
template<class
T
>
booloperator!=
(const GenericInterval<T> &a, const GenericInterval<T> &b)¶
-
template<class
T
>
booloperator>=
(const GenericInterval<T> &a, const GenericInterval<T> &b)¶
-
template<class
T
>
booloperator>
(const GenericInterval<T> &a, const GenericInterval<T> &b)¶
-
template<class
T
>
booloperator<=
(const GenericInterval<T> &a, const GenericInterval<T> &b)¶
-
template<class
T
>
std::ostream &operator<<
(std::ostream &os, const GenericInterval<T> &b)¶
-
template<class
T
>
structGenericInterval
¶ - #include <Interval.hpp>
This class represents an interval that is closed at its lower bound and open at its upper bound.
It is almost always used with T = std::size_t, for which there is a convenient Interval typedef.
Public Functions
-
GenericInterval
() = default¶ Initialise with begin and end set to their default value of 0.
-
-
typedef GenericInterval<std::size_t>
3.1.3. poplar/OptionFlags.hpp¶
-
namespace
poplar
Poplar classes and functions.
Functions
-
ProfileValue
getAsProfileValue
(const OptionFlags &flags)¶
-
void
readJSON
(StringRef string, OptionFlags &flags)¶ Read options from a string in JSON format.
- Parameters
string
: The string to parse.flags
: The OptionFlags to update.
- Exceptions
parse_error
: if the input cannot be parsed.
-
void
readJSON
(std::istream &stream, OptionFlags &flags)¶ Read options from a stream in JSON format.
- Parameters
stream
: The input stream to read from.flags
: The OptionFlags to update.
- Exceptions
parse_error
: if the input cannot be parsed.
-
std::ostream &
operator<<
(std::ostream &ostream, const OptionFlags &flags)¶ Write the contents of the given flags to an ostream in JSON format.
- Parameters
ostream
: The stream to write to.flags
: The OptionFlags to write.
-
class
OptionFlags
¶ - #include <OptionFlags.hpp>
A set of option/value string flags to be used in various APIs.
Public Types
-
using
initializer_list
= std::initializer_list<OptionFlag>¶
Public Functions
-
OptionFlags
()¶ Construct a set of option flags.
The default constructor creates an empty set of flags.
-
~OptionFlags
()¶
-
OptionFlags
(const OptionFlags &other)¶
-
OptionFlags
(OptionFlags &&other)¶
-
OptionFlags &
operator=
(const OptionFlags &other)¶
-
OptionFlags &
operator=
(OptionFlags &&other)¶
-
bool
operator==
(const OptionFlags &other) const¶ Option flags are an exact match.
Each collection contains the same keys, and both collections have the same values for each key
-
OptionFlags
(initializer_list &&list)¶ Construct a set of option flags from an initializer list of string pairs.
Flags are set in the order they appear in the constructor.
Setting a flag more than once will result in the previous value for that option being overwritten.
- Parameters
initializer
: A list of option/value string pairs to set in the flags.
-
void
set
(initializer_list &&list)¶ Set option flags from an initializer list of string pairs.
Flags are set in the order they appear in the list.
Setting a flag more than once will result in the previous value for that option being overwritten. If the option was already set in these flags then the previous value will be overwritten.
- Parameters
initializer
: A list of option/value string pairs to set in the flags.
-
void
set
(StringRef option, StringRef value)¶ Set a single option to a value.
If the option was already set in these flags then the previous value will be over- written.
- Parameters
option
: The option to set in the flags.value
: The value to set the option to in the flags.
-
StringRef
at
(StringRef option) const¶ Retrieves the value of the given option.
If the option does not exist, then an exception is thrown.
- Parameters
option
: The option to retrieve in the flags.
-
void
clear
()¶ Remove all set flags.
-
class
iterator
: public std::iterator<std::forward_iterator_tag, OptionFlag>¶ Public Functions
-
~iterator
()¶
-
const OptionFlag &
operator*
() const¶
-
const OptionFlag *
operator->
() const¶
Friends
- friend class OptionFlags
-
-
using
-
namespace
core
¶
-
ProfileValue
3.1.4. poplar/RandomSeed.hpp¶
-
namespace
poplar
Poplar classes and functions.
Functions
-
Tensor
getHwSeeds
(Graph &graph, program::Sequence &prog, const DebugContext &debugContext = {})¶ Gets a snapshot of the h/w seeds for each worker in device.
- Return
A tensor of shape {number of tiles, number of worker contexts, 4}, containing seed values for each of the 4
PRNG_x_y
registers for each worker context on each tile.- Parameters
graph
: The Poplar graph.prog
: The program sequence to be extended.debugPrefix
: The prefix prepended to debugging info.
-
void
setHwSeeds
(Graph &graph, const Tensor &hwSeeds, program::Sequence &prog, const DebugContext &debugContext = {})¶ Sets the hw seeds for each worker in a device from a snapshot of the seeds.
- Parameters
graph
: The Poplar graph.hwSeeds
: A tensor of shape {number of tiles, number of worker contexts, 4} containing seed values for each of the 4PRNG_x_y
registers for each worker context on each tile.prog
: The program sequence to be extended.debugPrefix
: The prefix prepended to debugging info.
-
Tensor
3.1.5. poplar/ReplicatedStreamMode.hpp¶
-
namespace
poplar
Poplar classes and functions.
3.1.6. poplar/SerializationFormat.hpp¶
-
namespace
poplar
Poplar classes and functions.
3.1.7. poplar/StringRef.hpp¶
3.1.8. poplar/SyncType.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
SyncType
¶ An enumeration used to state what type of synchronisation a Sync program represents.
Values:
-
enumerator
INTERNAL
¶ Each tile waits until all the other tiles in the same IPU reach the Sync program before continuing.
-
enumerator
EXTERNAL
¶ Each tile waits until all the other tiles in all IPUs in the device reach the Sync program before continuing.
-
enumerator
GLOBAL
¶ Each tile waits until all the other tiles in all IPUs globally reach the Sync program before continuing.
-
enumerator
-
enum
3.1.9. poplar/TypeTraits.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
struct
TypeTraits
¶ - #include <TypeTraits.hpp>
A structure to provide information about arithmetic (integer and floating point) types.
Public Functions
-
bool
isSimpleType
() const¶
-
template<>
TypeTraitsmake
()¶
-
template<>
constexpr boolisSimpleType
()¶
Public Static Functions
-
template<typename
T
>
TypeTraitsmake
()¶
-
template<typename
T
>
constexpr boolisSimpleType
()¶ Return true if it is a basic numeric type, i.e.
std::is_integral<> or std::is_floating_point<> is true, or it is IeeeHalf.
-
bool
-
struct
3.1.10. poplar/CSRFunctions.hpp¶
Functions to configure the floating behaviour of the tiles by programming the Control and Status Registers (CSR).
-
namespace
poplar
Poplar classes and functions.
Functions
-
void
setFloatingPointBehaviour
(poplar::Graph &graph, poplar::program::Sequence &prog, const FloatingPointBehaviour &behaviour, const DebugContext &debugContext = {})¶ Set the floating point behaviour of a tile.
Configures the floating point behaviour of a tile, affecting the treatment of exceptions and selecting stochastic rounding according to the passed
behaviour
structure.Note that, in Poplar, stochastic rounding is disabled by default until either this function, setStochasticRounding() or the Engine options are used to enable it.
- Parameters
graph
: The Poplar graphprog
: The program to be extendedbehaviour
: A structure of type floatingPointBehaviourdebugPrefix
: The prefix prepended to debugging info
-
void
setFloatingPointBehaviour
(poplar::Graph &graph, poplar::program::Sequence &prog, const poplar::Tensor &behaviour, const DebugContext &debugContext = {})¶ Set the floating point behaviour of a tile.
Configures the floating point behaviour of a tile, affecting the treatment of exceptions and selecting stochastic rounding according to the passed
behaviour
tensor.The behaviour tensor must be one returned by getAndModifyFloatingPointBehaviour.
- Parameters
graph
: The Poplar graphprog
: The program to be extendedbehaviour
: A tensor containing representation of floatingPointBehaviourdebugPrefix
: The prefix prepended to debugging info
-
void
setStochasticRounding
(poplar::Graph &graph, poplar::program::Sequence &prog, bool behaviour, const DebugContext &debugContext = {})¶ Set stochastic rounding on or off for the selected tile.
Configures the stochastic rounding operation of a tile according to the passed
behaviour
parameter.Note that, in Poplar, stochastic rounding is disabled by default until either this function, setFloatingPointBehaviour() or the Engine options are used to enable it.
- Parameters
graph
: The Poplar graphprog
: The program to be extendedbehaviour
: Select stochastic rounding: true or falsedebugPrefix
: The prefix prepended to debugging info
-
poplar::Tensor
getAndModifyFloatingPointBehaviour
(poplar::Graph &graph, poplar::program::Sequence &prog, const FloatingPointBehaviour &clear, const FloatingPointBehaviour &set, const DebugContext &debugContext = {})¶ Get state and and modify floating point behaviour on every tile that belongs to the target in the graph.
Returns the previous state and modifies behaviour. Behaviour modification first clears behaviour set in
clear
followed by setting behaviour set inset
.The recommended usage of this function should be as follows to avoid unexpected numerical behaviour:
… auto state = getAndModifyFloatingPointBehaviour(…) // operations that require the modified FP behaviour … setFloatingPointBehaviour(state)
- Return
State before FP behaviour is modified
- Parameters
graph
: The Poplar graphprog
: The program to be extendedclear
: Select behaviour to clear with fields set being ones cleared. Eg: if set.inv is true, that is cleared and if not set, behaviour is unchanged.set
: Select behaviour to set. The behaviour to set always followsclear
. Only set if field is true.debugPrefix
: The prefix prepended to debugging info
-
struct
FloatingPointBehaviour
¶ - #include <CSRFunctions.hpp>
Structure to specify floating point behaviour.
- Parameters
inv
: If true, a floating-point invalid operation (defined by IEEE 754) will cause an exception.The invalid operations are:
Addition or subtraction where the operands are + or - infinity (inf) and the operation results in the subtraction of two infs; for example: (-inf)+(+inf) or (+inf)-(+inf).
Divisions: (+/-0)/(+/-0) and (+/-inf)/(+/-inf).
Multiplications: (+/-0)*(+/-inf) and (+/-inf)*(+/-0).
Remainder: x REM y where y=0 or x=(+/-inf).
Real operations with complex results such as the square root or logarithm of a negative number.
Operations with Not-a-Number as at least one operand.
Comparisons where one of the operands is Not-a-Number.
See also nanoo below.
div
: If true a floating point divide by zero operation will cause an exception.oflo
: If true a floating point overflow will cause an exception.esr
: Enable stochastic rounding.nanoo
: Enable Not-a-Number on overflow mode. When enabled, half precision calculations that have overflowed will produce a Not-a-Number result, rather than saturating to the half precision max/min value, and the invalid operation (inv
) flag will be set.
Public Functions
-
FloatingPointBehaviour
(bool inv, bool div0, bool oflo, bool esr, bool nanoo)¶
-
FloatingPointBehaviour
() = default¶
-
FloatingPointBehaviour
operator!
() const¶
-
void
3.2. Exceptions¶
3.2.1. poplar/exceptions.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
struct
control_program_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when the construction of a graph program is invalid.
-
struct
file_load_error
: public poplar::poplar_error¶
-
struct
graph_connection_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown during construction of an Engine object if there is an error in the structure of graph, for example, if there are no edges to a vertex input or if there are multiple edges to a vertex input.
-
struct
graph_cycle_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown during the construction is an Engine object if there are any cycles in the graph that are not broken by recurrent edges.
-
struct
graph_memory_allocation_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an memory allocation fails.
Public Functions
-
graph_memory_allocation_error
(const char *s)¶
Public Members
-
ProfileValue
graphProfile
¶
-
-
struct
graph_object_creation_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown in the construction of a GraphProgEnv object if there was an error in the creation of the graph program object file.
-
struct
graph_object_load_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown in the construction of a GraphProgEnv object if there was an error in loading the graph program object file.
-
struct
graph_program_compilation_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown in the construction of a GraphProgEnv object if there are any compilation errors in the graph program.
-
struct
graph_replication_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an invalid operation is carried out on a replicated graph.
-
struct
index_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown if the index of a subscript is out of the bounds of the field it is accessing or if a index of a tensor is invalid.
-
struct
invalid_machine_model
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an invalid model of the IPU (for performance model profiling) has been specified.
-
struct
invalid_option
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an unrecognised or invalid option is passed to a Poplar API.
-
struct
invalid_tile_mapping
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when the tile mapping passed to the UserTilePartitioner is invalid.
-
struct
link_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when the linking stage for codelets fails.
output is the output from the linker command.
Public Functions
-
link_error
(const char *s, const char *out = "")¶
-
-
struct
memory_elem_constraints_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an invalid memory element constraint has been provided in a codelet.
-
struct
missing_perf_estimate
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an Engine is constructed with profiling enabled but a vertex does not have a getPerfEstimate method specified.
-
struct
no_environment
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown, in the construction of a GraphProgEnv object, in mixed-mode compilation, if there is no graph-programming environment available, in particular if the program has not been compiled with the ‘popc’ command-line tool.
-
struct
no_size_specified
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown if the size of a field is not specified in a Graph object when an EngineBuilder object is constructed.
-
struct
overflow_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an arithmetic overflow occurs within Poplar.
-
struct
parse_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an input file or string cannot be parsed.
-
struct
poplar_error
: public runtime_error¶ - #include <exceptions.hpp>
Base class for Poplar exceptions.
Subclassed by poplar::control_program_error, poplar::file_load_error, poplar::graph_connection_error, poplar::graph_cycle_error, poplar::graph_memory_allocation_error, poplar::graph_object_creation_error, poplar::graph_object_load_error, poplar::graph_program_compilation_error, poplar::graph_replication_error, poplar::index_error, poplar::invalid_machine_model, poplar::invalid_option, poplar::invalid_tile_mapping, poplar::link_error, poplar::memory_elem_constraints_error, poplar::missing_perf_estimate, poplar::no_environment, poplar::no_size_specified, poplar::overflow_error, poplar::parse_error, poplar::profiling_disabled, poplar::runtime_error, poplar::stream_connection_error, poplar::stream_memory_allocation_error, poplar::symbol_error, poplar::tensor_creation_error, poplar::tensor_io_state_error, poplar::type_error, poplar::unknown_field, poplar::unknown_vertex_type
-
struct
profiling_disabled
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown if profiling information is requested from an Engine but that Engine has not been constructed with profiling enabled.
Public Functions
-
profiling_disabled
()¶
-
-
struct
runtime_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when the interaction with the device via graphcore device access fails.
-
struct
stream_connection_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an invalid attempt is made to connect a data stream.
-
struct
stream_memory_allocation_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when allocation of stream buffers fails.
-
struct
symbol_error
: public poplar::poplar_error¶
-
struct
tensor_creation_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown in the construction of a tensor if invalid arguments are provided to the tensor creation function or method.
-
struct
tensor_io_state_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when an attempt is made to mark a tensor as an input or output, but the argument references a view of a tensor, rather than a whole tensor.
-
struct
type_error
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when there is an error related to the field types of vertices, for example, when the source of an edge contains an input, the types of inputs and source field between an edge do not match, or when a field cannot be subscripted.
-
struct
unknown_field
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when a field name is specified that does not exist in the graph-programming environment.
-
struct
unknown_vertex_type
: public poplar::poplar_error¶ - #include <exceptions.hpp>
This exception is thrown when a vertex type name is specified that does not exist in the graph programming environment.
-
struct
3.3. Graph classes¶
3.3.1. poplar/CodeletFileType.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
CodeletFileType
¶ Values:
-
enumerator
PreprocessedAsmSource
¶ A graph assembly language source file.
-
enumerator
AsmSource
¶ A graph assembly language file with preprocessor macros.
-
enumerator
CSource
¶ A graph C source file.
-
enumerator
CppSource
¶ A graph C++ source file.
-
enumerator
IrSource
¶ A graph LLVM IR source file.
-
enumerator
Object
¶ A graph program object file.
-
enumerator
Auto
¶ Auto detect based on file name.
-
enumerator
Functions
-
CodeletFileType
getCodeletFileType
(const char *path)¶
-
std::string
getExtensionFromFileType
(CodeletFileType type)¶
-
enum
3.3.2. poplar/DataStream.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
DataStream
¶ - #include <DataStream.hpp>
An object representing a stream for communicating between the host and the device.
A stream is a unidirectional communication from the host to the device, or from the device to the host.
The maximum buffer size for each stream is 128 MBytes.
Public Functions
-
DataStream
()¶
-
DataStream
(const DataStream&)¶
-
DataStream
(DataStream&&)¶
-
~DataStream
()¶
-
DataStream &
operator=
(const DataStream&)¶
-
DataStream &
operator=
(DataStream&&)¶
-
unsigned
replicationFactor
() const¶
-
ReplicatedStreamMode
replicatedMode
() const¶
-
DataStreamType
type
() const¶
-
-
class
RemoteBuffer
¶ - #include <DataStream.hpp>
A remote buffer is a region of remote (meaning not on the IPU) memory that is used as a cache.
It is implemented as two DataStreams: one to write to the remote memory, the other to read the data back to the IPU.
Public Functions
-
RemoteBuffer
()¶
-
RemoteBuffer
(const RemoteBuffer&)¶
-
RemoteBuffer
(RemoteBuffer&&)¶
-
~RemoteBuffer
()¶
-
RemoteBuffer &
operator=
(const RemoteBuffer&)¶
-
RemoteBuffer &
operator=
(RemoteBuffer&&)¶
-
DataStream
getIpuToHostStream
() const¶
-
DataStream
getHostToIpuStream
() const¶
-
size_t
numElements
() const¶
-
size_t
getRepeats
() const¶
-
bool
isRearrangeOnHost
() const¶
-
bool
isOptimisedForMemory
() const¶
-
bool
operator==
(const RemoteBuffer &b) const¶
-
bool
operator!=
(const RemoteBuffer &b) const¶
-
-
namespace
core
-
class
3.3.3. poplar/DataStreamType.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
DataStreamType
¶ An enumeration to represent the different types of DataStream or stream components of a RemoteBuffer.
Values:
-
enumerator
HostToDeviceFIFO
¶ A DataStream from host to device.
-
enumerator
DeviceToHostFIFO
¶ A DataStream from device to host.
-
enumerator
HostToDeviceBuffer
¶ A stream from host to device in a remote buffer.
-
enumerator
DeviceToHostBuffer
¶ A stream from device to host in a remote buffer.
-
enumerator
Functions
-
bool
isDeviceToHost
(DataStreamType type)¶
-
bool
isHostToDevice
(DataStreamType type)¶
-
bool
isRemoteBuffer
(DataStreamType type)¶
-
enum
3.3.4. poplar/Graph.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
Graph
¶ - #include <Graph.hpp>
This class represents a graph program to be executed on the IPU.
Public Types
Public Functions
-
Graph
(const Target &target, replication_factor r = replication_factor(1))¶ Construct a graph object.
This constructor creates a Graph object using the given graph programming environment.
- Parameters
target
: The target the graph is being constructed to work with.r
: Number of times graph is to be replicated (default is no replication)
-
Graph
(const Device &device, replication_factor r = replication_factor(1))¶ Construct a graph object.
This constructor creates a Graph object using the given graph programming environment.
- Parameters
device
: The device the graph is being constructed to work with.r
: Number of times graph is to be replicated (default is no replication)
-
~Graph
()¶
-
bool
addCodelets
(StringRef src, CodeletFileType type = CodeletFileType::Auto, StringRef compileFlags = "")¶ Add a codelet to the graph.
A codelet is either a C, C++, or assembly source file, or a .gp object file. If a source file is given it is compiled for the graph’s target and then loaded into the graph. If it is an object file then it is loaded into the graph.
Symbols that codelets use are not resolved until the engine is built, so codelets can use symbols from each other by calling addCodelets() for each source or object file (or passing a list of files as a vector).
- Return
True if the codelet is added to the graph successfully, or false if the codelet already existed in the graph.
- Parameters
src
: The path to a source or object file containing codelets.type
: Specify the type of the codelet (source or precompiled). If Auto is used, the type is determined from the filename extension.compileFlags
: Additional flags to pass to the compiler if using source code. For example,-g
to generate debug info.
-
bool
addCodelets
(StringRef src, CodeletFileType type, StringRef compileFlags, std::ostream &compileOutput)¶ Add a codelet to the graph and write error messages from the compilation process to the given output stream.
By default they are printed to cerr.
-
bool
addCodelets
(ArrayRef<std::string> xs, StringRef compileFlags = "")¶ Add a set of codelets to the graph.
These codelets can depend on each other, for example symbols defined in one can be used by any other. The order is not important.
- Return
True if all the codelets are added successfully, or false if any of the codelets are not added because they already exist in the graph.
-
void
addCodelets
(std::stringstream &stream, StringRef compileFlags = "", CodeletFileType type = CodeletFileType::CppSource)¶
-
void
addCodelets
(std::stringstream &stream, StringRef compileFlags, std::ostream &compileOutput, CodeletFileType type = CodeletFileType::CppSource)¶
-
VertexRef
addVertex
(ComputeSet cs, StringRef vertexType)¶ Add a vertex to the graph.
- Parameters
cs
: The compute set to add the vertex to.vertexType
: The name of the type of the vertex. This must be a declared vertex type in the graph programming environment used to create the graph builder.
-
VertexRef
addVertex
(ComputeSet cs, StringRef vertexType, ArrayRef<ConnectionDesc> connections)¶ Add a vertex to the graph and connect graph elements to some of its fields.
This variant of add vertex allows you to pass in a list of connection descriptions to connect graph elements to fields of the newly created vertex. The connection descriptions can be initialized with:
{ string, Tensor } - connect a tensor to a field.
{ string, FieldRef, bool } - connect a vertex field to a field.
{ string, T v } - connect a constant value to an input field.
For example, the following:
addVertex(cs, "MyVertex", {{"x", tensor[4]}, {"y", v["z"], false}});
Will create a vertex and connect a tensor to its x field and the vertex field v[“z”] to its y field.
- Parameters
cs
: The compute set to add the vertex to.vertexType
: The name of the type of the vertex. This must be a declared vertex type in the graph programming environment used to create the graph builder.connections
: A list of connection descriptions
-
VertexRef
addExternalExchangeVertex
(ComputeSet cs, StringRef vertexType, unsigned incomingDownCount, bool usesEastEdge, bool sendsXReq)¶ Add an external exchange vertex to the graph.
A compute set can contain at most one external exchange vertex per tile. External exchange vertices cannot be mixed with non external exchange vertices in the same compute set. Before an external vertex is called we set the INCOMING_DCOUNT and INCOMING_MUX mux registers and synchronize all tiles containing external exchange vertices.
- Parameters
cs
: The compute set to add the vertex to.vertexType
: The name of the type of the vertex. This must be a declared vertex type in the graph programming environment used to create the graph builder.incomingDownCount
: The value to set the INCOMING_DCOUNT register to.usesEastEdge
: Whether the vertex uses an east edge exchange block. The INCOMING_MUX register is set to point to either the east edge or west edge depending on this argument.sendsXReq
: Whether this vertex is responsible for sending the XREQ packet. There must be at most one tile per exchange block context that sends the XREQ and the tile must be the same in every compute set containing external exchange vertices.
-
Tensor
addVariable
(const Type &type, ArrayRef<std::size_t> shape, const DebugContext &debugContext = {})¶ Add a variable to the graph.
If using this function with a target with multiple tiles then the variable will initially have no tile mapping under the expectation that the tile mapping will be set later with
Graph::setTileMapping. If the target of the graph has only one tile then the tensor will be automatically mapped to that tile.- Parameters
type
: The type of the elements of the variable.shape
: The shape of the variable.name
: An optional name to identify the variable for debugging/profiling purposesreturns
: A Tensor referring to the variable in the graph.
-
Tensor
addVariable
(const Type &type, ArrayRef<std::size_t> shape, VariableMappingMethod mappingMethod, const DebugContext &debugContext = {})¶ Add a variable to the graph.
- Return
A Tensor referring to the variable in the graph.
- Parameters
type
: The type of the elements of the variable.shape
: The shape of the variable.mappingMethod
: The method to use to initially map the variable to tiles.name
: An optional name to identify the variable for debugging/profiling purposes
-
template<typename
T
>
TensoraddConstant
(const Type &type, ArrayRef<std::size_t> shape, ArrayRef<T> values, const DebugContext &debugContext = {"<const>"})¶ Add a constant to the graph.
A constant tensor is a tensor with every element initialized.
- Parameters
type
: The type of the elements of the constant.shape
: The shape of the constant.values
: Vector of values to initialize tensor elements to.name
: An optional name to identify the variable for debugging/profiling purposes
-
template<typename
T
>
TensoraddConstant
(const Type &type, ArrayRef<std::size_t> shape, T val, const DebugContext &debugContext = {"<const>"}, typename std::enable_if<TypeTraits::isSimpleType<T>()>::type* = nullptr)¶ Add a constant to the graph.
A constant tensor is a tensor with every element initialized to the same value. It cannot be connected to a vertex output.
- Parameters
type
: The type of the elements of the constant.shape
: The shape of the constant.val
: The value to initialize tensor elements to.name
: An optional name to identify the variable for debugging/profiling purposes
-
template<typename
T
>
TensoraddConstant
(const Type &type, ArrayRef<std::size_t> shape, const T *val, const DebugContext &debugContext = {"<const>"}, typename std::enable_if<TypeTraits::isSimpleType<T>()>::type* = nullptr)¶ Add a constant to the graph with multiple cell values.
A constant tensor is a tensor with every element initialized to the same value. It cannot be connected to a vertex output.
- Parameters
type
: The type of the elements of the constant.shape
: The shape of the constant.val
: The value to initialize tensor elements to.name
: An optional name to identify the variable for debugging/profiling purposes
-
Tensor
addConstant
(const Type &type, ArrayRef<std::size_t> shape, const void *val, const TypeTraits &traits, bool broadcast, const DebugContext &debugContext = {"<const>"})¶
-
Tensor
addConstantHalf
(const Type &type, ArrayRef<std::size_t> shape, uint16_t val, const DebugContext &debugContext = {"<const>"})¶ Add a constant to the graph, where the host data is type IEEE half.
A constant tensor is a tensor with every element initialized to the same value. It cannot be connected to a vertex output.
- Parameters
type
: The type of the elements of the constant.shape
: The shape of the constant.val
: The value to initialize tensor elements to.
-
Tensor
addConstantHalf
(const Type &type, ArrayRef<std::size_t> shape, const uint16_t *val, const DebugContext &debugContext = {"<const>"})¶ Add a constant to the graph with multiple cell values, where the host data is type IEEE half.
A constant tensor is a tensor with every element initialized to the same value. It cannot be connected to a vertex output.
- Parameters
type
: The type of the elements of the constant.shape
: The shape of the constant.val
: The value to initialize tensor elements to.
-
Tensor
clone
(const Type &type, const Tensor &t, const DebugContext &debugContext = {}, TensorCloneMethod method = TensorCloneMethod::PRESERVE_ORDER_UNLESS_ALIASES)¶ Add a tensor to the graph that has the same size and tile mapping as Tensor t.
- Parameters
type
: The element type of the new tensor.t
: The tensor to be cloned.name
: A debug name to give to any new tensors allocated in the graph during the clone. If this is empty then the debug names will be derived from existing tensor debug names.method
: The method to use for the cloning (decides whether to preserve ordering/aliasing in the new tensor).
-
Tensor
cloneN
(const Type &type, const Tensor &t, std::size_t N, const DebugContext &debugContext = {}, TensorCloneMethod method = TensorCloneMethod::PRESERVE_ORDER_UNLESS_ALIASES, TensorCloneDuplicationMethod duplicationMethod = TensorCloneDuplicationMethod::DUPLICATE_BY_OUTER_DIMENSION)¶ Clone a tensor N times.
Given a tensor of shape [D1, D2, … Dn], this function will create a new tensor of shape [N, D1, D2, …, Dn] where each of the N sub-tensors is a clone of the original tensor (i.e. has the same layout and tile mapping).
- See
- Parameters
type
: The element type of the new tensor.t
: The tensor to cloneN
: The replication factor to clone withname
: The name for the new variables createdmethod
: The tensor cloning method (see Graph::clone)duplicationMethod
: The behaviour used when a Tensor is cloned.
-
Tensor
clone
(const Tensor &t, const DebugContext &debugContext = {}, TensorCloneMethod method = TensorCloneMethod::PRESERVE_ORDER_UNLESS_ALIASES)¶ Add a tensor to the graph that has the same size and tile mapping as Tensor t.
- Parameters
t
: The tensor to be cloned.name
: A debug name to give to any new tensors allocated in the graph during the clone. If this is empty then the debug names will be derived from existing tensor debug names.method
: The method to use for the cloning (decides whether to preserve ordering/aliasing in the new tensor).
-
Tensor
cloneN
(const Tensor &t, std::size_t N, const DebugContext &debugContext = {}, TensorCloneMethod method = TensorCloneMethod::PRESERVE_ORDER_UNLESS_ALIASES, TensorCloneDuplicationMethod duplicationMethod = TensorCloneDuplicationMethod::DUPLICATE_BY_OUTER_DIMENSION)¶ Clone a tensor N times.
Given a tensor of shape [D1, D2, … Dn], this function will create a new tensor of shape [N, D1, D2, …, Dn] where each of the N sub-tensors is a clone of the original tensor (i.e. has the same layout and tile mapping).
- See
- Parameters
t
: The tensor to cloneN
: The replication factor to clone withname
: The name for the new variables createdmethod
: The tensor cloning method (see Graph::clone)duplicationMethod
: The behaviour used when a Tensor is cloned.
-
void
connect
(FieldRef field, const Tensor &tensor)¶ Connect a tensor to a vertex field.
This function connects an a tensor with a vertex field. If the vertex field is an scalar input/output then a simple edge is added (and the tensor must be of zero dimension; in other words, a scalar). If the vertex field is an input/output of a vector then a vector edge is added (and the tensor must be of dimension 1). If the vertex field is a vector of inputs or outputs then the size of the field is set to the correct size and edges are added for every element of the tensor tensor (and the tensor must be of dimension 1). If the vertex field is a vector of input or output vectors then the tensor must be 2-dimensional. In this case, the size of the vector field is set to the size of the first dimension and vector edges are added for every sub-vector of the two dimensional tensor.
- Parameters
tensor
: The tensor.field
: Reference to the vertex field to connect.
-
template<typename
T
>
voidconnect
(FieldRef field, T v, typename std::enable_if<TypeTraits::isSimpleType<T>()>::type* = nullptr)¶ Connect a constant value to an input field.
This method creates a single-element tensor containing a specified value and connects that tensor element to an input field.
- Parameters
v
: The value to connect.field
: The field to connect to.
-
void
connect
(FieldRef field, ArrayRef<Tensor> tensors)¶ Connect a vector of tensors to a vertex field.
This function connects an vector a tensors with a vertex field. The field must be a vector of inputs or outputs. The field will be sized to the provided vector and each element will be connect to the corresponding element of the field.
- Parameters
tensors
: The vector of tensors.field
: Reference to the vertex field to connect.
-
void
setPerfEstimate
(const VertexRef &v, std::uint64_t cycles, std::uint64_t flops = 0)¶ Set the performance estimate for a vertex.
- Parameters
v
: The vertex to set the estimate for.cycles
: The number of cycles that this vertex will use when run.flops
: The number of flops that this vertex will use when run.
-
void
setPerfEstimate
(const VertexRef &v, const VertexPerfEstimate &estimate)¶ Set the performance estimate for a vertex.
- Parameters
v
: The vertex to set the estimate for.estimate
: The performance estimates for this vertex when run.
-
VertexPerfEstimate
getPerfEstimate
(const VertexRef &v) const¶ Get the performance estimate for the specified vertex.
- Return
The performance estimates used when this vertex is run.
- Parameters
v
: The vertex to get the estimate for.
- Exceptions
missing_perf_estimate
: if the performance estimate is not available (for example, because the graph hasn’t been executed yet).
-
void
registerPerfEstimator
(StringRef vertexTypeName, PerfEstimateFunc f)¶ - Parameters
vertexTypeName
: Type of vertex to register the estimator for.f
: Callback function that will compute a performance estimate for all vertices of this type.
-
unsigned
getNumVertices
(void) const¶ Get the number of vertices currently in the graph.
- Return
The numbers of vertices currently in the graph.
-
ComputeSet
addComputeSet
(const DebugContext &debugContext = {})¶ Create a compute set within the graph.
- Return
The reference to the compute set.
- Parameters
name
: An optional identifier for the compute set that may be used during profiling/debugging.
-
void
setFieldSize
(FieldRef field, std::size_t size)¶ Set the size of a vector field.
- Parameters
field
: The reference to the field.size
: The size of the field.
-
std::size_t
getFieldSize
(FieldRef field) const¶ Get the size of a vector field.
- Return
The size of the field.
- Parameters
field
: The reference to the field.
-
std::size_t
getMaxFieldDim
(StringRef vertexName, StringRef fieldName, unsigned dimIndex) const¶ Find the maximum size for a dimension of a field.
- Parameters
vertexType
: The type of vertexfield
: The fielddimIndex
: The index of the dimension
- Exceptions
index_error
: If there is no such dimensionpoplar_error
: If the field is not indexable
-
double
getMaxVertexFieldValue
(StringRef vertexName, StringRef fieldName) const¶ Find the maximum value that can be represented by an element of a field.
- Parameters
vertexType
: The type of vertexfield
: The field
-
template<typename
T
>
voidsetInitialValue
(FieldRef field, T val, typename std::enable_if<TypeTraits::isSimpleType<T>()>::type* = nullptr)¶ Set the initial value of a field.
- Parameters
field
: The reference to the field.val
: The value to set the field to when the graph engine is created.
-
template<typename
T
>
voidsetInitCallback
(FieldRef field, LateInitCallback<T> callback, typename std::enable_if<std::is_arithmetic<T>::value>::type* = nullptr)¶ Set the init callback for a field; the callback function will be called after graph construction and must return the init value of the field.
This can be called instead of calling setInitialValue(), or both can be called for the field, to ensure that the field has a (at least partially) valid starting value, for instance it if needs to be retrieved in an early stage of graph compilation, before storage allocation (for instance during cycle estimation)
Note that you must explicitly provide the template parameter T in the specialisation, when using this function, e.g.: setInitCallback<uint16_t>(vertex[“size”], sizeCallback) because the compiler will not be able to detect the correct type from the callback parameter.
- Parameters
field
: The reference to the field.callback
: The callback that will return the value for the field.<unnamed>
: This exists only to allow to insert the ‘is_arithmetic<T>’ check for the type T.
-
void
setInitialValueHalf
(FieldRef field, uint16_t val)¶ Set the initial value of a field of type IEEE half.
- Parameters
field
: The reference to the field.val
: The value to set the field to when the graph engine is created.
-
template<typename
T
>
voidsetInitialValue
(FieldRef field, ArrayRef<T> val)¶ Set initial values of a vector field.
- Parameters
field
: The reference to the vector field.val
: A vector value to set the field to when the graph engine is created.
-
void
setInitialValueHalf
(FieldRef field, ArrayRef<uint16_t> val)¶ Set initial values of a vector field of type IEEE half.
- Parameters
field
: The reference to the vector field.val
: A vector value to set the field to when the graph engine is created.
-
template<typename
T
>
voidsetInitialValue
(const Tensor &t, T val, typename std::enable_if<TypeTraits::isSimpleType<T>()>::type* = nullptr)¶ Set the initial value of a tensor element.
- Parameters
t
: The tensor representing the value to set.val
: The value to set the field to when the graph engine is created. A buffer of values can be provided to set the elements of a non-scalar tensor.
-
void
setInitialValueHalf
(const Tensor &t, uint16_t val)¶ Set the initial value of a tensor element of type IEEE half.
- Parameters
t
: The tensor representing the value to set.val
: The value to set the field to when the graph engine is created. A buffer of values can be provided to set the elements of a non-scalar tensor.
-
void
createHostWrite
(StringRef handle, const Tensor &t, bool rearrangeOnHost = false)¶ Mark a Tensor as being available as the destination of host to device copies.
This is a convenience function that creates a host-to-device FIFO, and a Copy program that copies data from the FIFO to the tensor. When you call Engine::writeTensor() it copies the input data to the FIFO and then executes the Copy program on the device.
- See
- Parameters
handle
: A name to be associated with this host copy.t
: The tensor to be marked as an input.rearrangeOnHost
: Save IPU memory at the cost of exchange speed by rearranging the data on the host before sending it to the IPU, rather than doing an internal exchange. Note that due to alignment and size requirements of host exchange packets this may still require part of the transfer to be received to a temporary variable and copied to its destination.
-
void
createHostRead
(StringRef handle, const Tensor &t, bool rearrangeOnHost = false)¶ Mark a Tensor as being available as the source of device to host copies.
This is a convenience function that creates a device-to-host FIFO, and a Copy program that copies data to the FIFO from the tensor. When you call Engine::writeTensor() it executes the Copy program on the device and then outputs the data from the FIFO.
- See
- Parameters
handle
: A name to be associated with this host copy.t
: The tensor to be marked as an output.rearrangeOnHost
: Save IPU memory at the cost of exchange speed by sending data in any order and rearranging it on the host, rather than doing an internal exchange before sending it.
-
DataStream
addHostToDeviceFIFO
(StringRef handle, const Type &elementType, std::size_t numElements, ReplicatedStreamMode replicatedMode = ReplicatedStreamMode::REPLICATE, const OptionFlags &options = {})¶ Add a data stream to the graph for copying data from the host to the device.
The maximum size of the FIFO before being split into multiple FIFOs. This is a useful option to avoid exceeding the stream buffer size limit. If the original FIFO is larger than the specified split limit, then it is replaced by a number of FIFOs which represent chunks of the original FIFO, and are read from sequentially. Setting
splitLimit
to 0 or UINT_MAX disables this option.- Parameters
handle
: A name to be associated with this streamelementType
: The type of data in the streamnumElements
: The number of elements to be transferred from the stream by a Copy program.replicatedMode
: How the stream is replicated if this is a replicated graph.options
: List of options Supported options:splitLimit
Integer [=50 * 1024 * 1024]
bufferingDepth
Integer [=1]
The depth of the FIFO which may be prefetched before being read by the device. By default the FIFO size is 1, so prefetches a single entry after it has been read to refill the FIFO. Increasing the size of the FIFO allows for prefetching of multiple entries, increasing the probability there will be a valid entry in the FIFO for the device to read before falling back to synchronously fetching the next entry.
addressSpace
Enum [=pageTable]
The type of address mapping used by the hardware to translate an exchange address to a host physical address. Possible values:
pageTable
(default): uses a lookup table which maps one memory page per entry.addressTranslationTable
: uses a translation table. This table contains very few entries but each of them can map large regions. This type of address mapping is only supported for replicated streams.
-
DataStream
addDeviceToHostFIFO
(StringRef handle, const Type &elementType, std::size_t numElements, const OptionFlags &options = {})¶ Add a data stream to the graph for copying data from the device to the host.
The maximum size of the FIFO before being split into multiple FIFOs. This is a useful option to avoid exceeding the stream buffer size limit. If the original FIFO is larger than the specified split limit, then it is replaced by a number of FIFOs which represent chunks of the original FIFO, and are read from sequentially. Setting
splitLimit
to 0 or UINT_MAX disables this option.- Parameters
handle
: A name to be associated with this streamelementType
: The type of data in the streamnumElements
: The number of elements to be transferred to the stream by a Copy program.options
: List of options Supported options:splitLimit
Integer [=50 * 1024 * 1024]
-
RemoteBuffer
addRemoteBuffer
(StringRef handle, const Type &elementType, std::size_t numElements, std::size_t repeats = 1, bool rearrangeOnHost = false, bool optimiseMemory = false)¶ Add a remote buffer to the graph.
A remote buffer is memory outside the IPU which can be read and written by the IPU. A read returns the last written value. The remote buffer is (
repeats
*numElements
* sizeof(elementType
) + padding) bytes in size. Padding is added to meet any alignment constraints of the hardware.- Parameters
handle
: A name to be associated with this remote buffer.elementType
: The type of data in the remote buffer.numElements
: The number of elements to be transferred to the remote buffer by a Copy program.repeats
: The buffer can store multiple blocks of data to be transferred. The total number of data elements in the buffer isnumElements
*repeats
.rearrangeOnHost
: Perform any necessary data rearrangement on the on the host instead of on the IPU.optimiseMemory
: Optimise for memory use rather than speed.
-
void
outputVertexGraph
(std::ostream &outputStream, ArrayRef<program::Program> progs = {}) const¶ Output to a stream the vertex graph in dot file format.
- Parameters
outputStream
: The C++ stream to output the dot file onto.
-
void
outputComputeGraph
(std::ostream &outputStream, ArrayRef<program::Program> progs = {}) const¶ Output to a stream the compute graph in dot file format.
- Parameters
outputStream
: The C++ stream to output the dot file onto.
-
void
setTileMapping
(VertexRef v, unsigned tileNum)¶ Map a vertex to a specific tile on the device.
- Parameters
v
: Reference to the vertex to maptileNum
: The tile number to map the vertex to.
-
void
setTileMapping
(const Tensor &t, unsigned tileNum)¶ Map a tensor slice to a specific tile on the device.
- Parameters
t
: The tensor or tensor slice to map.tileNum
: The tile number to map to.
-
TileToTensorMapping
getTileMapping
(const Tensor &t, bool requireComplete = true) const¶ Inspect the tile mapping of a tensor.
- Return
The mapping from tiles to a vector of intervals mapped to the tile (implemented as vector indexed by the tile number). The lower and upper bound of each interval are elements number in the flattened tensor.
- Parameters
t
: The tensor to inspectrequireComplete
: Ift
is not fully mapped andrequireComplete
is true then an invalid_tile_mapping exception will be thrown.
-
TileToTensorMapping
getTileMapping
(const Tensor &t, bool *isComplete) const¶ Inspect the tile mapping of a tensor.
- Return
The mapping from tiles to a vector of intervals mapped to the tile (implemented as vector indexed by the tile number). The lower and upper bound of each interval are elements number in the flattened tensor.
- Parameters
t
: The tensor to inspectisComplete
: If non-null, updated to indicate whether the mapping is complete.
-
TileToTensorMapping
getVariableTileMapping
(const Tensor &t) const¶ Inspect the tile mapping of a tensor.
This excludes any constant regions.
- Return
The mapping from tiles to a vector of intervals mapped to the tile (implemented as vector indexed by the tile number). The lower and upper bound of each interval are elements number in the flattened tensor.
- Parameters
t
: The tensor to inspect
-
void
setTileMapping
(const Tensor &t, const TileToTensorMapping &mapping)¶ Set the tile mapping of a tensor based on an explicit map from tiles to tensor intervals.
- Parameters
t
: The tensor to mapmapping
: The mapping from tiles to a vector of intervals to be placed on that tile (implemented as vector indexed by the tile number). The lower and upper bound of each interval are elements number in the flattened tensor.
-
Tensor
getVariable
(VariableRef v) const¶ Get a tensor representing an entire variable.
- Return
A Tensor object representing that variable.
- Parameters
v
: The variable to retrieve.
-
bool
isConstant
(VariableRef v) const¶ Check whether a variable reference refers represents a constant.
When Graph::addConstant() is called a variable is created to represent that constant. This call checks whether a variable was created by that method or by Graph::addVariable().
- Return
True if and only if the variable refers to a constant.
- Parameters
v
: The variable to examine.
-
std::vector<std::vector<Interval>>
getSortedContiguousRegions
(const Tensor &t, ArrayRef<Interval> regions, bool removeAliasedIntervals = false, std::vector<std::size_t> *aliases = nullptr) const¶ Get a list of sequences of intervals over a tensor such that each sequence represents a contiguous region of memory.
- Return
A list of sequences of intervals. The intervals will cover the same elements of the tensor as provided as input.
- Parameters
t
: The tensor to get intervals over.regions
: A list of intervals representing the elements to sort into memory contiguous sequences.removeAliasedIntervals
: If true, remove intervals which alias others in the given regions from the result.aliases
: Optional list of indices for each region in the returned intervals where an index is always the same for a region representing the same underlying elements in memory. If this is nullptr, then no aliases will be returned.
-
void
reorderToSimplify
(Tensor *t, ArrayRef<Tensor*> ts, bool requireSimplestOrder = true) const¶ Reorder a set of tensors in order to simplify the view on data.
This function will update ‘t’ to be a (simpler) reordered view on the same data. The same reordering will be applied to all elements of ‘ts’. The reordering will be the same for all tensors so order-invariant or element-wise operations on ‘t’ and ‘ts’ can still be performed.
The main purpose of this function is to provide a way to implement more efficient graph construction of element-wise or order-invariant operations.
If ‘requireSimplestOrder’ is set to true then after execution t will consist of the minimum number of possible contiguous regions. If not, then no guarantee is give on the order of t.
All the tensors provided to this function must be of rank 1 (i.e flattened tensors) and have the same number of elements.
-
TensorRearranger
getSimplifyingRearranger
(const Tensor &t) const¶
-
Tensor
findUnbroadcastTensor
(const Tensor &t) const¶ Attempt to determine the shape of a Tensor prior to it having been broadcast.
Under some circumstances this may not be possible, failure is indicated by the returned tensor having the same shape as the input tensor
- Return
A tensor which will be set to the unbroadcast (sliced from ‘t’) tensor if it is possible to do so. Each dimension of the returned tensor will be a factor of the same dimension of the input tensor. The returned tensor will have the same rank as the input tensor. If it is not possible to determine the shape of the unbroadcast tensor the input tensor will be returned.
- Parameters
t
: The input tensor
-
void
serializeTensors
(std::ostream &out, ArrayRef<Tensor> tensors, SerializationFormat format) const¶ Serialize a set of tensors to JSON or CapnProto.
The tensors must all be from this graph or an exception is thrown. The information saved is:
The type, shape and expression of the tensors.
The type and number of elements of any variables used.
This is intended to be used for debugging, testing and visualisation.
- Parameters
out
: Stream to write to.tensors
: A set of tensors to serialize.format
: Serialize in JSON or CapnProto format. JSON is pretty printed.
- Exceptions
poplar_error
: if any tensor is not from this graph. CapnProto may also throw an exception if serialization fails.
-
std::vector<Tensor>
deserializeTensors
(std::istream &in, SerializationFormat format)¶ Deserialize a set of tensors from a CapnProto message.
JSON deserialization is not currently supported and an exception will be thrown if format is SerializationFormat::JSON.
This will recreate the tensors in this graph. It throws an exception on failure (for example, if the tensor type does not match the variable types). Whenever a variable is used by a tensor a new variable is added to the graph.
The layout of the tensors and variables should be the same as when they were serialized.
This function is primarily intended for testing and benchmarks. You should not use it as a general method of creating tensors.
- Return
The deserialized set of tensors.
- Parameters
in
: A stream from which serialised tensor data can be read.format
: Must be SerializationFormat::Binary
-
Graph
createVirtualGraph
(unsigned numTilesPerIPU)¶ Create a “virtual” graph working over a subset of the target’s tile.
This method returns a graph object that references the same state as this graph but has a virtual target than only uses a subset of the target’s tiles.
If the getTarget() method is called on the new graph it will return a target with the new number of tiles.
- Return
The virtual graph object
- Parameters
numTilesPerIPU
: The number of tiles per IPU for the new graph to work over.
-
Graph
createVirtualGraph
(unsigned lowerTile, unsigned upperTile)¶ Create a “virtual” graph working over a subset of the target’s tiles.
This method returns a graph object that references the same state as this graph but has a virtual target than only uses a subset of the target’s tiles.
This variant of the method takes a tile range for the new virtual graph to work over. This is the range [lowerTile:upperTile). This tile range must be contained within a single IPU.
If the getTarget() method is called on the new graph it will return a target with the new number of tiles.
- Return
The virtual graph object
- Parameters
lowerTile
: The starting tile of the tile range for the virtual graph to work over.upperTile
: The upper bound of the tile range for the virtual graph to work over. This is a non-inclusive upper bound.
-
Graph
createVirtualGraph
(const std::vector<unsigned> &perIpuTiles)¶ Create a “virtual” graph working over a subset of the target’s tiles.
This method returns a graph object that references the same state as this graph but has a virtual target than only uses a subset of the target’s tiles.
This variant of the method takes the set of tiles in each IPU that should be included in the new graph.
If the getTarget() method is called on the new graph it will return a target with the new number of tiles.
- Return
The virtual graph object
- Parameters
perIpuTiles
: The tiles to include in the graph. Tiles are specified by their index in the IPU. Each tile index must be unique and less than the number of tiles per IPU.
-
Graph
createReplicatedGraph
(unsigned replicationFactor)¶ Create a replicated graph.
The replicated graph is a view on
replicationFactor
virtual subgraphs. Operations on the replicated graph are implicitly applied to each virtual subgraph, for example adding a variable to the replicated graph implicitly creates a variable in all of the underlying subgraphs.The replication factor must divide the number of tiles in the graph. If n is the number of tiles in this graph the first subgraph contains tiles [0, n / replicationFactor), the second subgraph contains tiles [n / replicationFactor, 2n / replicationFactor) and so on.
-
Graph
getTopLevelGraph
()¶ Return the top level graph.
The createVirtualGraph() and createReplicatedGraph() methods can be used to create graph objects that are views on an underlying graph. If this is a virtual or replicated graph then this function returns the top level underlying graph, otherwise it returns the current graph.
-
unsigned
getReplicationFactor
() const¶ Return the replication factor of the graph.
-
Tensor
addReplicationIndexConstant
(const DebugContext &debugContext = {})¶ Add a constant that is initialized with the replication index.
-
Tensor
getNonReplicatedTensor
(const Tensor &t) const¶ Given a replicated tensor return the underlying tensors in this graph that the replicated tensor is a placeholder for.
The tensor returned by this function has an extra outer dimension equal to the replication factor of the tensor in this graph and it is formed by concatenating the underlying tensors for each replicated subgraph in this dimension.
This function can only be used with replicated graphs created by the createReplicatedGraph function, not when the Graph is constructed.
-
void
serialize
(std::ostream &out, SerializationFormat format) const¶ Serialize a graph to JSON or binary (CapnProto) format.
This is equivalent to serialize(out, {}, format).
Note that this does not currently serialize every bit of graph data, so it cannot be used to save and reload a graph.
- Parameters
out
: Stream to write to.format
: Serialize in JSON or CapnProto format. JSON is pretty printed.
-
void
serialize
(std::ostream &out, ArrayRef<program::Program> progs, SerializationFormat format) const¶ Serialize a graph to JSON or binary (CapnProto) format.
Progs can be passed so that information about Copy programs can be serialized (the Graph class itself does not know about them).
Note that this does not currently serialize every bit of graph data, so it cannot be used to save and reload a graph.
- Parameters
out
: Stream to write to.progs
: A set of programs that are searched for Copy programs. Information about the variables copied is serialised.format
: Serialize in JSON or CapnProto format. JSON is pretty printed.
-
Function
addFunction
(const program::Program &program)¶ Add a function to the graph.
A function is a partial control program that can be reused. By registering a repeated program as a function and calling it, less control code is generated than repeating the sequence.
- Return
The Function object that can be used by a Call program.
- Parameters
program
: The control program to register as a callable function
-
unsigned
convertVirtualTileToPhysicalTile
(unsigned virtualTileId) const¶ Convert Virtual Tile ID into Physical Tile ID.
A function provides conversion interface required by the Graphcore communication library to know what exchange block context a tile is associated with.
- Return
Physical Tile ID
- Parameters
Virtual
: Tile ID
-
unsigned
convertPhysicalTileToVirtualTile
(unsigned physicalTileId) const¶ Convert Physical Tile ID to Virtual Tile ID.
This function provides a conversion interface required by the Graphcore communication library to know what exchange block context a tile is associated with.
- Return
Virtual Tile ID
- Parameters
Physical
: Tile ID
-
unsigned
convertPhysicalTileToVirtualTile
(unsigned ipuId, unsigned physicalTileId) const¶ Convert Physical Tile ID to Virtual Tile ID.
A function returns Virtual Tile ID based on a parameters pair of IPU and and Physical Tile ID. This conversion interface is required by the Graphcore communication library to know what exchange block context a tile is associated with.
- Return
Virtual Tile ID
- Parameters
IPU
: IDPhysical
: Tile ID
Private Functions
-
void
setInitialValue
(FieldRef field, const void *val, const TypeTraits&)¶
-
template<typename
T
>
voidsetInitCallback
(FieldRef field, LateInitCallback<T> callback, const TypeTraits&)¶
-
void
setInitialValue
(const Tensor &t, const void *val, const TypeTraits&)¶
-
void
connect
(FieldRef field, void *val, const TypeTraits&)¶
-
class
ConnectionDesc
¶ Public Functions
-
template<typename
T
>ConnectionDesc
(StringRef field, T v, typename std::enable_if<TypeTraits::isSimpleType<T>()>::type* = nullptr)¶
Private Types
Private Members
-
TypeTraits
traits
¶
Friends
- friend class Graph
-
template<typename
-
-
namespace
core
-
namespace
program
¶ Namespace for program classes.
-
class
3.3.5. poplar/GraphElements.hpp¶
-
namespace
poplar
Poplar classes and functions.
Typedefs
-
class
ComputeSet
¶ - #include <GraphElements.hpp>
A reference to a compute set within a graph.
This type provides a way to address compute sets within a graph.
Private Members
-
unsigned
computeset_id
¶
-
unsigned
-
class
FieldRef
¶ - #include <GraphElements.hpp>
A reference to a field within a vertex instance.
This type provides a way to address fields (inputs or internal state) within a vertex. FieldRef’s are normally obtained using
VertexRef::operator[](StringRef fieldName)
, for example:VertexRef vertex = graph.addVertex(...); FieldRef input = vertex["input"]; graph.connect(input, ...);
A FieldRef can also be indexed, for example:
FieldRef input_5 = vertex["input"][5];
This is used when a field is a list of regions, for example a
Vector<Input<Vector<...>>> or an Input<VectorList<...>>
.Public Functions
-
FieldRef
()¶
-
FieldRef
operator[]
(std::size_t index) const¶ Access an element of a vector field.
Subscript a vector field to access the element at position
index
.- Return
A reference to the field.
- Parameters
index
: The subscript of the field
-
bool
isIndexed
() const¶
Private Functions
-
FieldRef
(VertexRef vertex, StringRef fieldName)¶ FieldRef constructor from vertex id and field name.
Construct a FieldRef out of a vertex id and the name of the field.
Friends
- friend class VertexRef
-
-
class
Function
¶ - #include <GraphElements.hpp>
A reference to a function stored within a graph.
Private Members
-
unsigned
function_id
¶
-
unsigned
-
class
VertexRef
¶ - #include <GraphElements.hpp>
A reference to a vertex within a graph.
This type provides a way to address vertices within a graph.
Public Functions
-
VertexRef
()¶
Private Functions
Friends
- friend class core::GraphBuilder
- friend class Graph
- friend class FieldRef
-
-
namespace
core
-
class
3.3.6. poplar/LateInitCallback.hpp¶
-
namespace
poplar
Poplar classes and functions.
Typedefs
-
using
LateInitCallback
= std::function<T(const VertexEdgeInfo&)>¶ A callback function of this type can be specified for a field of a vertex, instead of specifying an initialisation value with setInitialValue.
Will be called after the graph has been built. Will be passed information about the vertex fields. Needs to return the value for the field.
-
struct
VertexEdgeInfo
¶ - #include <LateInitCallback.hpp>
Data structure that will be passed to the callback used for ‘late initialisation’ for vertex fields.
Contains address information for the other (edge) vertex fields to allow the callback to appropriately initialise the ‘late init’ field itself.
Public Members
-
std::map<std::string, std::vector<StorageInfo>>
storage
¶
-
struct
StorageInfo
¶
-
std::map<std::string, std::vector<StorageInfo>>
-
using
3.3.7. poplar/PerfEstimateFunc.hpp¶
-
namespace
poplar
Poplar classes and functions.
Typedefs
-
using
PerfEstimateFunc
= std::function<VertexPerfEstimate(const VertexIntrospector &v, const Target &target)>¶ Functions of this type can be used as performance estimator callbacks for new vertex types.
-
using
3.3.8. poplar/Tensor.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
UpsampleMethod
¶ Enum passed to Tensor::upsample(unsigned scale, unsigned dimension) specifying the upsampling method.
Values:
-
enumerator
REPEAT
¶ If dimension is of size s, for every i in [0, s), repeats the subtensor at index i scale times.
For example, with scale = 2 and dimension = 1: Shape(2,3) Shape(2x6) [[1, 2, 3], becomes [[1, 1, 2, 2, 3, 3], [4, 5, 6]] [4, 4, 5, 5, 6, 6]]
Note that a scale of 0 means repeat each tensor 0 times. So a (i, j, k, l) tensor upsampled with scale = 0 and dimension = 3 would become an (i, j, k, 0) tensor containing 0 elements.
scale = 1 is the identity operation.
-
enumerator
Functions
-
Tensor
concat
(ArrayRef<Tensor> ts, unsigned dimension = 0)¶ Concatenate several tensors.
The tensors are concatenated along the specified dimension.
- Return
The result of the concatenation
- Parameters
ts
: The tensors to concatenatedimension
: The number of the dimension to concatenate across
-
Tensor
concat
(const Tensor &first, const Tensor &second, unsigned dimension = 0)¶ Concatenate two tensors.
The tensors are concatenated along the specified dimension.
- Return
The result of the concatenation
- Parameters
first
: The first tensor to concatenatesecond
: The second tensor to concatenatedimension
: The number of the dimension to concatenate across
-
Tensor
append
(const Tensor &first, const Tensor &second, unsigned dimension)¶ Append a tensor as an element to another tensor.
- Return
The extended tensor
- Parameters
first
: The tensor to append tosecond
: The tensor to add as an element in the specified dimensiondimension
: The number of the dimension to append to
-
class
Tensor
¶ - #include <Tensor.hpp>
A reference to a subset of tensor elements.
Public Functions
-
Tensor
()¶
-
~Tensor
()¶
-
Tensor
operator[]
(std::size_t i) const &¶ Get the sub-tensor indexed by i in the first dimension of the tensor.
- Parameters
i
: The index into the first dimension of the tensor.
-
Tensor
slice
(std::size_t begin, std::size_t end, unsigned dimension) const &¶ Get the sub-tensor given by a specific range [begin, end) in one dimension of the tensor.
- Parameters
begin
: The first element of the rangeend
: The upper bound to the range (the last element + 1)dimension
: The dimension to slice in
-
Tensor
slice
(std::size_t begin, std::size_t end) const¶ Get the sub-tensor given by a specific range [begin, end) in the first dimension of the tensor.
- Parameters
begin
: The first element of the rangeend
: The upper bound to the range (the last element + 1)
-
Tensor
slice
(const Interval ®ion, unsigned dimension = 0) const¶ Get the sub-tensor given by a specific range [begin, end) in one dimension of the tensor.
- Parameters
region
: The region to slicedimension
: The dimension to slice in
-
Tensor
slice
(ArrayRef<std::size_t> begin, ArrayRef<std::size_t> end) const¶ Get the sub-tensor given by slicing the tensor in multiple dimensions, starting at dimension 0.
Each pair begin[i], end[i] specifies that the tensor is sliced in dimension i by the range [begin[i], end[i]). The rank of the returned tensor is the same as the input tensor.
- Parameters
begin
: The lower bounds of the ranges used to slice the tensorend
: The upper bounds of the ranges used to slice the tensor
-
std::vector<Tensor>
slices
(ArrayRef<Interval> intervals, unsigned dimension = 0) const¶ Get a vector of slices.
- Return
A vector of slices where each slice is obtained by slicing this tensor between the two points in the given interval list.
- Parameters
intervals
: A list of intervals.dimension
: The dimension to slice in
-
std::vector<Tensor>
slices
(const std::vector<std::vector<Interval>> &intervals, unsigned dimension = 0) const¶ Get a vector of slices.
- Return
A vector of tensors where each tensor is the concatenation of the sequence of several slices, each slice being this tensor between the two point in the corresponding interval in the sequences given as input.
- Parameters
intervals
: A list of sequences of intervals.dimension
: The dimension to slice in
-
Tensor
index
(ArrayRef<std::size_t> indices) const¶ Get the sub-tensor indexed by the specified indices.
This is equivalent to repeatedly applying operator[] for each index in the vector of indices.
- Return
The sub-tensor indexed by the indices.
- Parameters
indices
: The indices used to index into the tensor.
-
Tensor
flatten
() const¶ Flatten the tensor.
- Return
A tensor consisting of all elements of the original tensor but with a single dimension.
-
Tensor
flatten
(unsigned dimBegin, unsigned dimEnd) const¶ Flatten the a subset of the dimensions of a tensor.
- Return
A tensor consisting of all elements of the original tensor with the specified dimension range flattened into one dimension.
- Parameters
dimBegin
: The first dimension to flattendimEnd
: One past the last dimension to flatten.
-
Tensor
reshape
(ArrayRef<std::size_t> shape) const¶ Reshape the tensor.
The reshaping operation changes the shape of the tensor but cannot change the total number of elements.
- Return
A tensor consisting of all elements of the original but with new dimensions.
- Parameters
shape
: The new shape of the tensor.
-
Tensor
dimShuffle
(ArrayRef<unsigned> permutation) const¶ Permute the dimensions of a tensor.
The dimShuffle operation reorders the tensor to a permutation of its dimensions. It can be seen as the generalized form of a matrix transpose.
Note that this operation does not create a copy of the tensor but returns a reordered view on this tensor’s data.
- Return
The shuffled tensor
- Parameters
permutation
: The permutation vector specifies a mapping from the output dimension to the input dimension. For example the permutation of {2, 0, 1} specifies that element element [a][b][c] in the original tensor is remapped to element [c][a][b] in the new tensor.
-
Tensor
dimShufflePartial
(ArrayRef<unsigned> source, ArrayRef<unsigned> destination) const¶ Permute some of a tensor’s dimensions.
dimShufflePartial reorders the tensors dimensions. The unspecified dimensions stay in the same relative order.
Note that this operation does not create a copy of the tensor but returns a reordered view on this tensor’s data.
- Return
The shuffled tensor.
- Parameters
source
: The dimensions to move.destination
: The index at which to move each source dimension.
-
Tensor
dimRoll
(unsigned dimIdx, unsigned newIdx = 0) const¶ Roll a specified dimension to the specified dimension.
The other dimensions remain in the same relative order
Note that this operation does not create a copy of the tensor but returns a reordered view on this tensor’s data.
- Return
The shuffled .
- Parameters
dimIdx
: The dimension to move.newIdx
: Its new location, default 0.
-
Tensor
reshapePartial
(unsigned beginIndex, unsigned endIndex, ArrayRef<std::size_t> newDims) const¶ Reshape a range of dimensions of a tensor.
reshapePartial reshapes the input tensor such that the total number of elements of the resultant tensor is the same as the input tensor.
Note that this operation does not create a copy of the tensor but returns a reshaped view on the input tensor’s data.
The following conditions define the valid use of this function:
1) beginIndex == endIndex
beginIndex and endIndex must each lie in the closed interval [0, rank()]. Singleton dimensions are added before beginIndex. The number of dimensions added is equal to the length of the newDims vector. For example:
Adds two singleton dimensions at indicies 0 and 1reshapePartial(0, {1, 1})
2) size(newDims) == 0 and beginIndex != endIndex
beginIndex must lie in the half closed interval [0, rank()) endIndex must lie in the half closed interval (0, rank()] The product of vector newDims must be 1. For example:
Removes singleton dimensions 1 and 2 from the tensorreshapePartial(1, 3, {})
3) size(newDims) != 0 and beginIndex != endIndex
beginIndex must lie in the half closed interval [0, rank()) endIndex must lie in the half close interval (0, rank()] The product of vector newDims must be equal to the product of the number of elements in the interval [beginIndex, endIndex)
The input dimensions [0, beginIndex) and [endIndex, rank()) are prepended and appended at the end of the tensor respectively. For example:
reshapePartial(1, 3, {10, 20, 30}) reshapePartial(1, 3, {10})
- Return
Reshaped view of tensor
- Parameters
beginIndex
: Index of the dimension from which reshape startsendIndex
: Index of the first dimension after reshape endsnewDims
: The new dimensions of the partial tensor
-
Tensor
expand
(ArrayRef<std::size_t> indices) const¶ Expand tensor by adding singleton dimensions at specified indices of tensor.
The rank is expanded by the size of dimensions to be added. To add more than one dimension at a given position, the same index shall be repeated.
- Return
A view of expanded tensor
- Parameters
indices
: Dimension indices before which the singleton dimensions are added
-
Tensor
squeeze
(ArrayRef<std::size_t> indices) const¶ Reduce dimension of tensor by removing singleton dimensions at specified indices of tensor.
- Return
A view of squeezed tensor
- Parameters
indices
: Indices of singleton dimensions which are removed
-
Tensor
subSample
(unsigned stride, unsigned dimension) const¶ Sub-sample the tensor.
Sub-sample this tensor by selecting every stride-th element of the tensor in a specified dimension
- Return
The sub-sampled tensor
- Parameters
stride
: The size of the stridedimension
: The dimension to sub-sample in
-
Tensor
upsample
(unsigned scale, unsigned dimension, UpsampleMethod method) const¶ Upsample the tensor.
Note that this operation does not create a copy of the tensor but creates a view of the tensor’s data. The repeated data is represented by repeated views into the tensor.
- See
UpsampleMethod for descriptions of how the tensor can be upsampled.
- Return
The upsampled tensor.
- Parameters
scale
: The scaling factor, >= 0.dimension
: The dimension to upsample in.method
: The method by which to upsample the tensor.
-
Tensor
broadcast
(unsigned N, unsigned dimension) const¶ Broadcast/repeat the tensor along a specified dimension.
Create a view with this tensor repeated N times along a specified dimension.
- Return
The broadcast tensor.
- Parameters
N
: The number of times to repeat.dimension
: The dimension to broadcast in.
-
Tensor
reinterpret
(const Type &type) const¶ Reinterpret the tensor as a new type.
The new type must be the same size as the old type. See elementType() for a list of valid types and their sizes.
- Return
A tensor with the same shape and referencing the same data but of the new type.
- Parameters
type
: The type to reinterpret to
-
Tensor
reverse
(unsigned dimensions) const¶ reverse this tensor along a specified dimension.
- Return
The reversed tensor.
- Parameters
dimension
: The dimension to reverse.
-
std::size_t
dim
(unsigned i) const¶ Get a dimension of the tensor.
- Parameters
i
: The index of the dimension to get.
-
std::vector<std::size_t>
shape
() const¶ Get the shape of the tensor.
- Return
A vector of all the dimensions of the tensor.
-
unsigned
rank
() const¶ Get the rank of the tensor.
- Return
The number of dimensions a tensor has.
-
bool
isContiguous
() const¶ Get whether the tensor is contiguous.
-
bool
containsAliases
() const¶ Get whether the tensor contains an alias to the same storage location.
- Return
True if the tensor contains an alias to the same storage location.
-
bool
containsConstant
() const¶ Get whether the tensor contains any constant tensors.
- Return
True if the tensor contains any constant tensors.
-
bool
isParallelWriteable
() const¶ Get whether the elements of this tensor can be written in parallel.
This is equivalent to !(containsAliases() || containsConstant()).
- Return
True if the tensor can be written in parallel.
-
const std::vector<Interval>
getContiguousRegions
() const¶ Get the contiguous regions of a tensor.
- Return
A vector of intervals in order representing regions of the tensor that are contiguous in the tensors storage ordering.
-
const std::vector<VariableInterval>
getVarRegions
() const¶ Get the contiguous regions of a tensor with reference to the variables allocated in the graph.
- Return
A vector of variable intervals (variable id, interval pairs) representing the regions of the tensor.
-
template<typename
T
>
boolgetConstantValue
(T *val) const¶ Read a single element of data from a tensor if it is a constant.
- Return
True if tensor is constant and data is read
- Parameters
val
: Buffer to which tensor data is copied to
-
bool
intersectsWith
(const Tensor &other) const¶ Return whether this tensor intersects with another tensor.
- Return
True if this tensor intersects with the other tensor.
- Parameters
other
: The tensor to compare with.
-
std::ostream &
output
(std::ostream &os) const¶ Display the expression representing the tensor on a stream.
- Return
The ostream written to
- Parameters
os
: The ostream to output to
-
std::ostream &
outputRegions
(std::ostream &os) const¶ Display the regions of the tensor on a stream.
- Return
The ostream written to
- Parameters
os
: The ostream to output to
-
void
dump
() const¶ Display the expression representing the tensor.
-
void
dumpRegions
() const¶ Display the regions of the tensor.
-
bool
valid
() const¶
Private Functions
-
bool
getConstantData
(void *dst, const TypeTraits &traits) const¶
-
-
namespace
core
-
enum
3.3.9. poplar/TensorCloneMethod.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
TensorCloneMethod
¶ Define behaviour when a Tensor is cloned.
- See
Values:
-
enumerator
PRESERVE_ORDER_AND_ALIASES
¶ Preserve the ordering and aliasing within the original tensor reference.
-
enumerator
CREATE_NEW_ORDER
¶ Create a new tensor with natural ordering based on the dimensions of the cloned tensor (in the same way as addTensor).
-
enumerator
PRESERVE_ORDER_UNLESS_ALIASES
¶ Preserve the ordering of the original tensor unless it contains aliases.
In the case of aliases, create a new tensor ordering and duplicate the aliased elements.
-
enumerator
GATHER_AND_PRESERVE_TILE_ORDER_AND_ALIASES
¶ Gather elements of the underlying variables that are mapped to the same tile so they form one contiguous region on the tile in the cloned tensor.
Contiguous regions on the tile and the aliasing of elements are preserved.
-
enum
TensorCloneDuplicationMethod
¶ Define behaviour when a Tensor is cloned and duplicated using Graph::cloneN.
If DUPLICATE_BY_TILE_CONTIGUOUS_REGION and a new order needs to be created (either via TensorCloneMethod::CREATE_NEW_ORDER or TensorCloneMethod::PRESERVE_ORDER_UNLESS_ALIASES) then Poplar will error.
Values:
-
enumerator
DUPLICATE_BY_OUTER_DIMENSION
¶ The multiple clones are concatenated in their outermost dimension.
i.e. the result is the same as concat(clone1, clone2, …, cloneN); There is no guarantee of any ordering constraints in memory between the clones.
-
enumerator
DUPLICATE_BY_TILE_CONTIGUOUS_REGION
¶ The underlying variables of the clones are contenated for each contiguous region on each tile.
Each clone will have the same contiguous regions on each tile but each of those regions will also form bigger contiguous regions across the N duplicates. This option is particular useful for efficient slicing/copying between the duplicates being cloned.
-
enumerator
Functions
-
std::string
toString
(const TensorCloneMethod &method)¶
-
std::string
toString
(const TensorCloneDuplicationMethod &method)¶
-
enum
3.3.10. poplar/TensorRearranger.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
TensorRearranger
¶ - #include <TensorRearranger.hpp>
A TensorRearranger is an object that can re-order the view on a tensor and undo that re-ordering.
- See
Graph::getSimplifyingRearranger
Public Functions
-
TensorRearranger
()¶
-
TensorRearranger
(const TensorRearranger &other)¶
-
TensorRearranger
(TensorRearranger &&other)¶
-
const TensorRearranger &
operator=
(const TensorRearranger &other) &¶
-
TensorRearranger &
operator=
(TensorRearranger &&other) &¶
-
~TensorRearranger
()¶
-
Tensor
undoRearrangement
(const Tensor &t) const¶ Undo the rearrangement done via the rearrange method.
-
std::vector<Interval>
rearrange
(ArrayRef<Interval> is) const¶ Apply the rearrangement to intervals.
is A list of intervals w.r.t the original tensor.
- Return
A list of equivalent intervals w.r.t the rearranged tensor.
-
std::vector<Interval>
undoRearrangement
(ArrayRef<Interval> is) const¶ Apply the undoing of the rearrangement to intervals.
is A list of intervals w.r.t the rearranged tensor.
- Return
A list of equivalent intervals w.r.t the original tensor.
-
bool
valid
() const¶
-
namespace
core
-
class
3.3.11. poplar/Type.hpp¶
Defines
-
POPLAR_DECLARE_EQUIV_TYPE
(T1, T2)¶
-
namespace
poplar
Poplar classes and functions.
Variables
-
template<typename
T
>
structequivalent_device_type
¶ - #include <Type.hpp>
Template structure to relate a host type to a device type.
This structure is specialized to allow a program to relate a host type to a corresponding device type. For example::
poplar::Type t = equivalent_device_type<int>().value;
-
class
Type
¶ - #include <Type.hpp>
Class representing device data types.
The following types are not supported on the IPU:
LONG
UNSIGNED_LONG
LONGLONG
UNSIGNED_LONGLONG
DOUBLE
For other types, the sizes on the IPU are:
BOOL: 1 byte
CHAR: 1 byte (signed)
SIGNED_CHAR: 1 byte
UNSIGNED_CHAR: 1 byte
SHORT: 2 bytes
SIGNED_SHORT: 2 bytes
UNSIGNED_SHORT: 2 bytes
INT: 4 bytes
SIGNED_INT: 4 bytes
SIGNED: 4 bytes
UNSIGNED_INT: 4 bytes
UNSIGNED: 4 bytes
HALF: 2 bytes
FLOAT: 4 bytes
-
namespace
core
-
template<typename
3.3.12. poplar/VariableMappingMethod.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
VariableMappingMethod
¶ When variables are added to the graph, a tile mapping can be created.
This class enumerates the method for creating that mapping.
Values:
-
enumerator
NONE
¶ No mapping is created.
The tile mapping will be set later via Graph::setTileMapping.
-
enumerator
LINEAR
¶ The variable will be spread evenly across the tiles with the element ordering matching the tile number ordering.
The tile mapping can also be overridden later via Graph::setTileMapping.
-
enumerator
Functions
-
std::string
toString
(const VariableMappingMethod &method)¶
-
enum
3.3.13. poplar/VariableRef.hpp¶
-
template<>
structstd
::
hash
<poplar::VariableRef>¶ Public Functions
-
size_t
operator()
(const poplar::VariableRef &v) const¶
-
size_t
-
namespace
poplar
Poplar classes and functions.
Functions
-
bool
operator==
(const VariableInterval &a, const VariableInterval &b)¶
-
bool
operator<
(const VariableInterval &a, const VariableInterval &b)¶
-
struct
VariableInterval
¶ - #include <VariableRef.hpp>
Type representing a segment of a particular variable.
Public Functions
-
VariableInterval
(VariableRef var, Interval interval)¶
-
VariableInterval
() = default¶
-
VariableInterval
(const VariableInterval &other) = default¶
-
VariableInterval
(VariableInterval &&other) = default¶
-
VariableInterval &
operator=
(const VariableInterval &other) = default¶
-
VariableInterval &
operator=
(VariableInterval &&other) = default¶
-
-
class
VariableRef
¶ - #include <VariableRef.hpp>
Type representing a reference to a variable in a graph.
Public Functions
-
VariableRef
(unsigned id, unsigned replicationFactor)¶
-
VariableRef
() = default¶
-
VariableRef
(const VariableRef &other) = default¶
-
VariableRef
(VariableRef &&other) = default¶
-
VariableRef &
operator=
(const VariableRef &other) = default¶
-
VariableRef &
operator=
(VariableRef &&other) = default¶
Friends
- friend class Graph
-
friend friend bool operator== (const VariableRef &a, const VariableRef &b)
-
friend friend bool operator< (const VariableRef &a, const VariableRef &b)
-
-
bool
-
namespace
std
¶ -
template<> VariableRef >
Public Functions
-
size_t
operator()
(const poplar::VariableRef &v) const¶
-
size_t
-
3.3.14. poplar/VectorLayout.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
namespace
layout
¶ Namespace for layout classes.
-
namespace
3.3.15. poplar/VertexIntrospector.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
FieldData
¶ - #include <VertexIntrospector.hpp>
Information about a vertex field, including its size and its initial value if set.
This is used when calculating cycle estimates.
Vertex fields can be scalar, 1D or 2D. For example:
Their sizes can always be returned, and the initial values can be returned for non-edge fields (
float
,Vector<float>
) and edge fields (Input
etc.) that are connected to constants.Note that 2D fields are vectors of vectors, in other words they are jagged 2D arrays.
Public Functions
-
~FieldData
()¶
-
unsigned
rank
() const¶ Return the rank of the field: 0 for scalar fields, 1 for 1D and 2 for 2D.
-
std::size_t
size
() const¶ Return the size of the field.
For scalar fields it returns 1, for 1D fields it returns the size of the vector, and for 2D fields it returns the number of sub-vectors.
-
std::size_t
getSizeAtIndex
(std::size_t i) const¶ For 2D fields, return the size of the sub-vector.
Throws an error if called on non-2D fields.
- Parameters
i
: Index of sub-vector to return size of
-
layout::Vector
getProfilerVectorLayout
(std::size_t nestingLevel) const¶ For Vector fields return the layout.
- Parameters
i
: The dimension to query, 0 for the outer vector, 1 for the inner.
-
layout::VectorList
getProfilerVectorListLayout
() const¶ For VectorList fields return the layout.
We only support introspecting a VectorList that is the outermost vector.
-
SizeT
operator[]
(std::size_t i) const¶ Instead of field.getSizeAtIndex(i) you can alternatively use field[i].size().
-
template<typename
T
>
TgetInitialValue
(const Target &target) const¶ Get the inital value for a scalar field.
T should be a scalar type. Throws an error if this is not a scalar field.
Private Functions
-
template<typename
T
>
voidgetInitialValuesOverload
(const Target &target, std::vector<T> &result) const¶
-
struct
SizeT
¶
-
-
class
VertexIntrospector
¶ - #include <VertexIntrospector.hpp>
Available to cycle estimators to inspect the shape and initial values of a vertex’s fields.
Public Functions
-
ComputeSet
getComputeSet
() const¶ Return the compute set that this vertex is in.
-
VertexIntrospector
(VertexIntrospector&&)¶
-
ComputeSet
-
namespace
core
-
class
3.4. Control program classes¶
3.4.1. poplar/Program.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
namespace
core
-
namespace
program
Namespace for program classes.
Functions
-
class
Abort
: public poplar::program::Program¶ Public Functions
-
Abort
(const DebugContext &debugContext = {})¶ Throws an exception.
- Parameters
debugContext
: Optional DebugId and program name.
-
-
class
AbortOnCondition
: public poplar::program::Program¶ Public Functions
-
AbortOnCondition
(Tensor predicate, const DebugContext &debugContext = {})¶ Throws an exception if the test tensor tests to true.
- Parameters
predicate
: Scalar tensor to test.debugContext
: Optional DebugId and program name.
-
-
class
AssumeEqualAcrossReplicas
: public poplar::program::Program¶ - #include <Program.hpp>
A program to mark a tensor as equal across replicas.
This can be used to tell Poplar that the value of a tensor is the same in all replicas (e.g. the result of a cross-replica all-gather operation). Poplar will assume this property while checking divergency in the control flow and accept programs that otherwise would have to reject due to the lack of knowledge of tensor values.
Public Functions
-
AssumeEqualAcrossReplicas
(Tensor t, const DebugContext &debugContext = {})¶
-
-
class
Call
: public poplar::program::Program¶ - #include <Program.hpp>
A program to perform a function call to a previously stored program.
Public Functions
-
Call
(Function f, const DebugContext &debugContext = {})¶ Call the function.
- Parameters
f
: A program that has been added to the graph using Graph::addFunction.debugContext
: Optional DebugId and program name.
-
-
class
Copy
: public poplar::program::Program¶ - #include <Program.hpp>
A program that copies data.
Public Functions
-
Copy
(Tensor src, Tensor dst, bool dontOutline = false, const DebugContext &debugContext = {})¶ Construct a program to copy data from one tensor to another.
This constructor creates a program that will copy data from the
src
tensor to thedst
tensor.- Parameters
src
: The tensor to copy from.dst
: The tensor to copy to.dontOutline
: Do not outline this copy as a function call. Default is false (the copy will be outlined).debugContext
: Optional DebugId and program name.
-
Copy
(const DataStream &stream, Tensor dst, bool optimiseMemory = false, const DebugContext &debugContext = {})¶ Construct a program to copy from a data stream to a tensor.
- Parameters
stream
: The stream to copy from.dst
: The tensor to copy to.optimiseMemory
: if set to true will sacrifice speed in order to reduce memory use. For example, rearranging data on host and outlining writes.debugContext
: Optional DebugId and program name.
-
Copy
(Tensor src, const DataStream &stream, bool optimiseMemory = false, const DebugContext &debugContext = {})¶ Construct a program to copy a Tensor to a data stream.
- Parameters
src
: The tensor to copy from.stream
: The stream to copy to.optimiseMemory
: Set to true to sacrifice speed in order to reduce memory usage.debugContext
: Optional DebugId and program name.
-
Copy
(const RemoteBuffer &buffer, Tensor dst, const DebugContext &debugContext = {})¶ Construct a program to copy a remote buffer to a tensor.
- Parameters
buffer
: The remote buffer to copy from.dst
: The tensor to copy to.debugContext
: Optional DebugId and program name.
-
Copy
(const RemoteBuffer &buffer, Tensor dst, Tensor offset, const DebugContext &debugContext = {})¶ Construct a program to copy a remote buffer to a tensor.
The data to be transferred is controlled by the definition of the buffer and the
offset
parameter.The buffer has
repeat
data-transfer “rows” each containingnumElements
data items (these are not necessarily the same as rows in the destination tensor.) The size ofoffset
defines the number of rows to copy. The rows to be copied are defined byoffset:
each element ofoffset
is the index of a row to be copied.The size of
dst
must be equal to the data transfer size:sizeof(offset)
*numElements
.If the
offset
tensor has more than one element then thedst
must be a rank 2 tensor with dimensions [offset.numElements(), remoteBuffer.numElements()].Multiple values in the
offset
tensor with the same value will result in undefined behaviour because the order of writes to the buffer is not guarenteed.- See
- Parameters
buffer
: The remote buffer to copy from.dst
: The tensor to copy to.offset
: The “rows”” in the remote buffer to copy from.debugContext
: Optional DebugId and program name.
-
Copy
(Tensor src, const RemoteBuffer &buffer, const DebugContext &debugContext = {})¶ Construct a program to copy a tensor to a remote buffer.
- Parameters
src
: The tensor to copy from.buffer
: The remote buffer buffer to copy to.debugContext
: Optional DebugId and program name.
-
Copy
(Tensor src, const RemoteBuffer &buffer, Tensor offset, const DebugContext &debugContext = {})¶ Construct a program to copy a tensor to a remote buffer.
The data that is transferred is controlled by the definition of the buffer and the
offset
parameter.The buffer has
repeat
data transfer “rows” each containingnumElements
data items. (These are not necessarily the same as rows in the source tensor) The rows to be copied are defined byoffset
. The size ofoffset
defines the number of rows to copy. Each element ofoffset
is the index of a row to be copied.The size of
src
must be equal to the data transfer size:sizeof(offset)
*numElements
.If the
offset
tensor has more than one element then thesrc
must be a rank 2 tensor with dimensions [offset.numElements(), remoteBuffer.numElements()].Multiple values in the
offset
tensor with the same value will result in undefined behaviour.- See
- Parameters
src
: The tensor to copy from.buffer
: The remote buffer buffer to copy to.offset
: The “rows” in the remote buffer to copy to.debugContext
: Optional DebugId and program name.
-
Copy
(const DataStream &stream, Tensor dst, Tensor expectedIndex, bool rearrangeOnHost = false, const OptionFlags &options = {}, const DebugContext &debugContext = {})¶ Construct a program to copy from a data stream to a tensor.
- Parameters
stream
: The data stream to copy from.dst
: The tensor to copy to.expectedIndex
:rearrangeOnHost
:options
:debugContext
: Optional DebugId and program name.
-
Copy
(Tensor src, const DataStream &stream, Tensor index, bool rearrangeOnHost = false, const OptionFlags &options = {}, const DebugContext &debugContext = {})¶ Construct a program to copy a tensor to a data stream.
- Parameters
src
: The tensor to copy from.stream
: The data stream to copy to.index
:rearrangeOnHost
:options
:debugContext
: Optional DebugId and program name.
Private Functions
-
Copy
(const DataStream &stream, Tensor dst, bool rearrangeOnHost, Tensor offset, size_t repeats, bool optimiseMemory, const OptionFlags &options = {}, const DebugContext &debugContext = {})¶
-
Copy
(Tensor src, const DataStream &stream, bool rearrangeOnHost, Tensor offset, size_t repeats, bool optimiseMemory, const OptionFlags &options = {}, const DebugContext &debugContext = {})¶
-
-
class
CrossReplicaCopy
: public poplar::program::Program¶ - #include <Program.hpp>
A program that copies tensors between replicated sub-graphs.
Public Functions
-
CrossReplicaCopy
(Tensor src, Tensor dst, std::map<unsigned, unsigned> replicaMap, const DebugContext &debugContext = {})¶ Constructor to create a program to copy a tensor to the equivalent tensor in a different replica sub-graph.
When the replicated graphs are created, this will create a Copy program in each replica. Each replica sends to exactly one other replica and receives from exactly one other replica. A replica may not copy to itself.
- Parameters
src
: Replicated tensor to copy from.dst
: Replicated tensor to copy to.replicaMap
: Each key in this map specifies the sub-graph or replica that contains the source tensor. The corresponding value is the replica that contains the destination tensor.The size of the replica map is equal to the graph replication factor.
Each replica must be represented once as a key (source) and once as a value (destination).
debugContext
: Optional DebugId and program name.
-
-
class
ErrorProgram
: public poplar::program::Program¶ Public Functions
-
ErrorProgram
(StringRef message, Tensor debugTensor, const DebugContext &debugContext = {})¶ Throw an error.
Prints out a message and then throws an error.
- Parameters
message
: String to print.debugTensor
: Tensor that will be printed after the message to aid debugging. \param debugContext Optional DebugId and program name.
-
-
class
Execute
: public poplar::program::Program¶ - #include <Program.hpp>
Program that executes a compute set in the graph.
Public Functions
-
Execute
(ComputeSet cs, const DebugContext &debugContext = {})¶ Construct a graph execution program.
- Parameters
cs
: The compute set to execute.debugContext
: Optional DebugId and program name.
-
Execute
(ComputeSet cs, Tensor t, const DebugContext &debugContext = {})¶ Construct a graph execution program and write the exit status to a scalar tensor.
The exit status is the logical and of the return values of the vertices in the compute set.
- Parameters
cs
: The compute set to execute.t
: The tensor to write the exit status to.debugContext
: Optional DebugId and program name.
-
-
class
If
: public poplar::program::Program¶ - #include <Program.hpp>
A program that runs one of two programs depending on the value of a scalar tensor.
Public Functions
-
If
(Tensor predicate, const Program &trueBody, const Program &falseBody, const DebugContext &debugContext = {})¶ A program that executes the trueBody or falseBody depending on the value of the predicate.
You can pass an empty Sequence to either trueBody or falseBody if you don’t want either branch to do anything.
- Parameters
predicate
: The scalar tensor that determines which branch to execute.trueBody
: This program is run if the predicate is true.falseBody
: This program is run if the predicate is false.debugContext
: Optional DebugId and program name.
-
-
class
PrintTensor
: public poplar::program::Program¶ Public Functions
-
PrintTensor
(Tensor t, const DebugContext &debugContext = {})¶ Print the contents of a tensor.
You can send the output to a different stream by using the Engine::setPrintTensorStream function.
- Parameters
t
: The Tensor to print.debugContext
: Optional DebugId and program name.
-
-
class
Program
¶ - #include <Program.hpp>
This class represents a control program that executes operations on the graph.
The class should not be explicitly constructed but one of its sub-classes should be constructed instead.
Subclassed by poplar::program::Abort, poplar::program::AbortOnCondition, poplar::program::AssumeEqualAcrossReplicas, poplar::program::Call, poplar::program::Copy, poplar::program::CrossReplicaCopy, poplar::program::ErrorProgram, poplar::program::Execute, poplar::program::If, poplar::program::PrintTensor, poplar::program::Repeat, poplar::program::RepeatWhileFalse, poplar::program::RepeatWhileTrue, poplar::program::Sequence, poplar::program::Switch, poplar::program::Sync, poplar::program::WriteUndef
-
class
Repeat
: public poplar::program::Program¶ - #include <Program.hpp>
A program that repeatedly executes for a fixed number of iterations.
Public Functions
-
Repeat
(unsigned count, const Program &prog, const DebugContext &debugContext = {})¶ Construct a repeat program.
- Parameters
count
: The number of iterations to repeat for.prog
: The program to repeatedly execute.debugContext
: Optional DebugId and program name.
-
-
class
RepeatWhileFalse
: public poplar::program::Program¶ - #include <Program.hpp>
A program that evaluates the condition program, and if the predicate tensor is true it exits the loop.
If predicate tensor is false it evaluates the body program, and then loops to re-evaluate the condition program. This is like a C while statement with an inverted condition.
Public Functions
-
RepeatWhileFalse
(const Program &cond, Tensor predicate, const Program &body, const DebugContext &debugContext = {})¶ Construct a repeat while false program.
- Parameters
cond
: The program evaluated before the body is evaluated.predicate
: The scalar tensor that determines whether to execute the body.body
: The body to execute when the predicate is false.debugContext
: Optional DebugId and program name.
-
-
class
RepeatWhileTrue
: public poplar::program::Program¶ - #include <Program.hpp>
A program that evaluates the condition program, and if the predicate tensor is false it exits the loop.
If predicate tensor is true it evaluates the body program, and then loops to re-evaluate the condition program. This is like a C while statement.
Public Functions
-
RepeatWhileTrue
(const Program &cond, Tensor predicate, const Program &body, const DebugContext &debugContext = {})¶ Construct a repeat while true program.
- Parameters
cond
: The program evaluated before the body is evaluated.predicate
: The scalar tensor that determines whether to execute the body.body
: The body to execute when the predicate is true.debugContext
: Optional DebugId and program name.
-
-
class
Sequence
: public poplar::program::Program¶ - #include <Program.hpp>
Program that executes a sequence of programs.
Public Functions
-
template<class ...
T
>Sequence
(T&&... args)¶ Construct an execution sequence from a list of programs.
This variadic constructor is used to create a sequence of programs where the programs are provided as arguments to the constructor. For example:
Sequence(prog1, prog2, prog3)
- Parameters
args
: Parameter pack of all programs in the sequence.
-
Sequence
(const DebugContext &debugContext = {})¶ Construct an empty execution sequence (with optional debug context).
-
Sequence
(std::initializer_list<Program> programs, const DebugContext &debugContext = {})¶ Construct an execution sequence from a list of programs.
This constructor is used to create a sequence of programs where the programs are provided as arguments to the constructor.
Sequence{prog1, prog2, prog3} Sequence({prog1, prog2, prog3}, {debugId}) Sequence({prog1, prog2, prog3}, {debugId, "debugName"})
- Parameters
programs
: List of programs in the sequence.debugContext
: Optional DebugId and program name.
-
template<class ...
-
class
Switch
: public poplar::program::Program¶ - #include <Program.hpp>
A program that runs one of many programs depending on the value of a tensor.
The controlling tensor must be a scalar of type INT or UNSIGNED_INT. A switch contains of a number of switch cases, each with a case value and a case body and a default case. The case values must be unique. If the value of the controlling tensor matches the case value of a case the corresponding case body is run, otherwise the default case is run.
Public Functions
-
Switch
(Tensor control, const std::vector<std::pair<std::int32_t, Program>> &cases, const DebugContext &debugContext = {})¶ Construct a switch with the specified set of cases and an empty default case.
- Parameters
control
: The controlling tensor.cases
: The cases of the switch.debugContext
: Optional DebugId and program name.
-
Switch
(Tensor control, const std::vector<std::pair<std::int32_t, Program>> &cases, const Program &defaultCaseBody, const DebugContext &debugContext = {})¶ Construct a switch with the specified set of cases and default case.
- Parameters
control
: The controlling tensor.cases
: The cases of the switch.defaultCaseBody
: The body of the default case.debugContext
: Optional DebugId and program name.
-
Switch
(Tensor control, const DebugContext &debugContext = {})¶ Construct a switch with no cases and an empty default case.
The add() method can be used to add cases after the switch is constructed.
- Parameters
control
: The controlling tensor.debugContext
: Optional DebugId and program name.
-
Switch
(Tensor control, const Program &defaultCaseBody, const DebugContext &debugContext = {})¶ Construct a switch with no cases and the specified default case.
The add() method can be used to add cases after the switch is constructed.
- Parameters
control
: The controlling tensor.defaultCaseBody
: The body of the default case.debugContext
: Optional DebugId and program name.
Public Static Functions
-
Switch
switchWithBoundsChecking
(Tensor control, const std::vector<std::pair<std::int32_t, Program>> &cases, const DebugContext &debugContext = {})¶ A helper function that causes the default case to throw an error.
-
Switch
switchWithUnreachableDefault
(Tensor control, const DebugContext &debugContext = {})¶ This function lets the compiler assume the default case is unreachable.
If the control value is something other than one of the cases, it results in undefined behaviour (although there is some very minimal error checking at runtime).
Private Functions
-
Switch
(Tensor control, const Program &defaultCaseBody, const bool unreachableDefault, const DebugContext &debugContext = {})¶
-
-
class
Sync
: public poplar::program::Program¶ - #include <Program.hpp>
A program to synchronise at a certain granularity dictated by the
SyncType
.Public Functions
-
Sync
(SyncType type, const DebugContext &debugContext = {})¶ - Parameters
type
: The type of sync to perform.debugContext
: Optional DebugId and program name.
-
-
class
WriteUndef
: public poplar::program::Program¶ - #include <Program.hpp>
A program to mark a tensor as containing an undefined value.
This can be used to improve the liveness analysis of tensors and save memory in some situations.
Poplar does liveness analysis using the standard algorithm except that Poplar’s variables are not scalar values; they are arrays. In the standard analysis a variable is “killed” when it is written to with a new value. This means that it is dead immediately before that point because its value there can never be read.
int a = 1; // a is dead here because its current value (1) can never be read. a = 2; // a is killed here, which makes it dead on the line above.
In Poplar a variable is killed when all of its elements are written in the same compute set. Consider the pseudo-code:
var = graph.addVariable(FLOAT, {2}, ...); seq.add(Execute( var[0] = 1, var[1] = 2 )); // var is dead here (it is killed on the line below) because none of its // element values (1, 2) can ever be read. seq.add(Execute( var[0] = 3, var[1] = 4 ));
If only some of the elements are written then the entire variable is still live before the write because we may still need the value of the elements that were not written to.
seq.add(Execute( var[0] = 1, var[1] = 2 )); // var is alive here because the value 2 might be read later. seq.add(Execute( var[0] = 3 ));
var is still alive because no compute set writes to every element. If the entire variable is overwritten but in separate compute sets, then it will still be considered to be live because Poplar does not track the liveness of each variable element - only the entire variable.
seq.add(Execute( var[0] = 1, var[1] = 2 )); // var is alive here even though 1 and 2 can never be read. seq.add(Execute( var[0] = 3 )); seq.add(Execute( var[1] = 4 ));
This means var is alive more than necessary which may lead to increased memory use. One solution is for Poplar to track the liveness of every variable element separately, but that would be prohibitively expensive.
Instead, this program provides a way to manually mark a tensor as being dead by writing an undefined value to it. Changing the above code to the following results in the correct liveness.
seq.add(Execute( var[0] = 1, var[1] = 2 )); // Manually kill var because we know - even if Poplar does not - that // it is about to be completely overwritten. seq.add(WriteUndef(var)); seq.add(Execute( var[0] = 3 )); seq.add(Execute( var[1] = 4 ));
For more information about liveness analysis see https://en.wikipedia.org/wiki/Live_variable_analysis and https://www.cl.cam.ac.uk/teaching/2006/OptComp/slides/lecture03.pdf
- Parameters
t
: The tensor to mark as undefined.debugContext
: Optional DebugId and program name.
Public Functions
-
WriteUndef
(Tensor t, const DebugContext &debugContext = {})¶
-
class
-
namespace
3.5. Device management¶
3.5.1. poplar/TargetType.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
-
enum
TargetType
¶ Enum to represent the type of a device capable of running a graph.
Values:
-
enumerator
IPU
¶ Run on real IPU hardware.
-
enumerator
IPU_MODEL
¶ Model of the IPU which actually runs on the CPU but behaves like an IPU.
-
enumerator
CPU
¶ Run code on the CPU.
This does not accurately replicate all the functionality of an IPU and should only be used for running simple tests.
-
enumerator
Functions
-
std::string
toString
(TargetType t)¶ Convert the target type to a string.
Throws an exception if an undefined type is passed, e.g. static_cast<TargetType>(100).
-
enum
3.5.2. poplar/Target.hpp¶
-
namespace
poplar
Poplar classes and functions.
Functions
-
void
copyDeviceHalfToFloat
(const Target &target, const void *src, float *dst, std::size_t numElements)¶ Convert device half-precision values to floats.
- Parameters
target
: Target that the half-precision data is to be copied from.src
: Pointer to the start of the half-precision data.dst
: Pointer to the float data to write.numElements
: Number of items to convert.
-
void
copyFloatToDeviceHalf
(const Target &target, const float *src, void *dst, std::size_t numElements)¶ Convert float values to device half-precision values.
- Parameters
target
: Target that the half-precision data is to be copied to.src
: Pointer to the float data to read.dst
: Pointer to the half-precision data to write.numElements
: Number of items to convert.
-
void
copyDeviceHalfToDouble
(const Target &target, const void *src, double *dst, std::size_t numElements)¶ Convert device half-precision values to doubles.
- Parameters
target
: Target that the half-precision data is to be copied from.src
: Pointer to the start of the half-precision data.dst
: Pointer to the double precision data to write.numElements
: Number of items to convert.
-
void
copyDoubleToDeviceHalf
(const Target &target, const double *src, void *dst, std::size_t numElements)¶ Convert double precision values to device half-precision values.
- Parameters
target
: Target that the half-precision data is to be copied to.src
: Pointer to the double precision data to read.dst
: Pointer to the half-precision data to write.numElements
: Number of items to convert.
-
class
Target
¶ - #include <Target.hpp>
A target representation.
The Target class holds characteristics of a compilation target and enables interaction with it.
Target creation options
ipuLinkConfiguration
(Default, BarleyTwist, SlidingWindow, None) [=None]The configuration used for the IPU to IPU connections (known as the Newmanry network). ‘None’ means that Poplar decides, based on the number of IPUs.
Note that ‘Default’ is not the default!
syncConfiguration
(intraReplicaAndAll, ipuAndAll) [=intraReplicaAndAll]The configuration of the hardware synchronisation groups. Note the ‘target.syncReplicasIndependently’ engine option determines which of the synchronisation groups is used for host synchronisation.
intraReplicaAndAll: The first sync group is used to sync IPUs within a replica and the second sync group is used to sync all IPUs.
ipuAndAll: The first sync group is used to sync each IPU independently with the host (if the target.syncReplicasIndependently option is set) and the second sync group is used to sync all IPUs.
ipuLinkTopology
(mesh, torus) [=mesh]The topology of the IPU links. It describes how the IPUs in the system are connected.
mesh: The IPUs are connected as a ladder.
torus: The IPUs are connected as a ladder, with the top and bottom of the ladder linked together.
IpuLinkDomainSize
Integer [=NIPUS]The number of IPUs connected via IPU links. Two IPU link domains can be connected together via gateway links.
Public Functions
-
Target
()¶
-
~Target
()¶
-
TargetType
getTargetType
() const¶ The target type.
-
unsigned
getNumIPUs
() const¶ The number of IPUs.
-
unsigned
getTilesPerIPU
() const¶ The number of tiles per IPU.
-
unsigned
getNumWorkerContexts
() const¶ The number of worker contexts per tile.
-
unsigned
getBytesPerTile
() const¶ Bytes of memory per tile.
-
unsigned
getExchangeBytesPerCycle
() const¶ The bandwidth of internal IPU exchange in bytes per cycle.
-
unsigned
getMemcpyBytesPerCycle
() const¶ The maximum bandwidth for internal data copies on a tile.
-
unsigned
getMinIPUSyncDelay
() const¶ The IPU sync delay for the tile that is closest to the sync controller.
-
unsigned
getGlobalSyncCycles
() const¶ The number of clock cycles required to synchronize all IPUs.
-
unsigned
getInterleavedMemoryElementIndex
() const¶ Memory element offset index for interleaved memory.
-
const std::vector<GlobalExchangeConstraint> &
getGlobalExchangeConstraints
() const¶ Set of constraints that provide a lower bound on the time it takes to send data between IPUs.
-
unsigned
getNumStrideBits
() const¶
-
unsigned
getDataPathWidth
() const¶ The width of the load/store data path within the tile.
-
unsigned
getFp16ConvUnitMaxPipelineDepth
() const¶ The maximum pipeline depth of the convolution units within the tile for fp16.
-
unsigned
getFp32ConvUnitMaxPipelineDepth
() const¶ The maximum pipeline depth of the convolution units within the tile for fp32.
-
unsigned
getFp16ConvUnitInputLoadElemsPerCycle
() const¶ The number of input elements loaded per cycle in f16 convolution unit.
-
unsigned
getFp32ConvUnitInputLoadElemsPerCycle
() const¶ The number of input elements loaded per cycle in f32 convolution unit.
-
unsigned
getFp16InFp16OutConvUnitsPerTile
() const¶ The number of convolution units in the tile that can be used when partial results are outputs as 16-bits and inputs are 16 bits.
-
unsigned
getFp16InFp32OutConvUnitsPerTile
() const¶ The number of convolution units in the tile that can be used when partial results are outputs as 32-bits and inputs are 16 bits.
-
unsigned
getFp32InFp32OutConvUnitsPerTile
() const¶ The number of convolution units in the tile that can be used when accumulating to 32 bit values.
-
unsigned
getConvUnitCoeffLoadBytesPerCycle
() const¶ The number of convolutional weights that can be loaded in a cycle.
-
unsigned
getRptCountMax
() const¶
-
bool
supportsExchangeBusSharing
() const¶ Whether tiles can share the local exchange bus during exchange.
The number of consecutive tiles that can share the exchange bus.
-
unsigned
getNumTiles
() const¶ Get the total number of tiles for this target (tiles per IPU * number of IPUs).
-
std::uint64_t
getMemoryBytes
() const¶ Get the total amount of memory on this target, across all IPUs.
-
unsigned
getFloatVectorWidth
() const¶ How many floats can be processed in one vector operation.
Equivalent to getDataPathWidth() / 32.
-
unsigned
getHalfVectorWidth
() const¶ How many halves can be processed in one vector operation.
Equivalent to getDataPathWidth() / 16.
-
unsigned
getVectorWidth
(const poplar::Type &type) const¶ How many of the given type can be processed in one vector operation.
-
unsigned
getWeightsPerConvUnit
(bool floatActivations) const¶
-
unsigned
getConvUnitInputLoadElemsPerCycle
(bool floatActivations) const¶
-
unsigned
getMaxIPUSyncDelay
() const¶ Get the maximum number of cycles required for an IPU sync in the best case scenario (all tiles are immediately ready).
-
double
getTileClockFrequency
() const¶ Get the tile clock frequency in Hertz.
-
unsigned
getNumTilesPerXBContext
() const¶ Get the number of tiles per exchange-block context (with repair).
-
unsigned
getNumContextsPerXB
() const¶ Get the number of contexts per exchange-block.
-
std::size_t
getAtomicStoreGranularity
() const¶ Get the granularity of atomic stores that can be made by independent parallel worker threads.
- Return
The granularity in bytes.
-
uint32_t
makeFpIctlValue
(bool inv, bool div0, bool oflo, bool esr, bool nanoo) const¶ Generate a value that could be written to Floating Point Initial Control Value register CSR_S.FP_ICTL in order to configure it with the specified options.
- Parameters
inv
: If true, a floating-point invalid operation (defined by IEEE 754) will cause an exception.The invalid operations are:
Addition or subtraction where the operands are + or - infinity (inf) and the operation results in the subtraction of two infs; for example: (-inf)+(+inf) or (+inf)-(+inf).
Divisions: (+/-0)/(+/-0) and (+/-inf)/(+/-inf).
Multiplications: (+/-0)*(+/-inf) and (+/-inf)*(+/-0).
Remainder: x REM y where y=0 or x=(+/-inf)
Real operations with complex results such as the square root or logarithm of a negative number.
Operations with Not-a-Number as at least one operand.
Comparisons where one of the operands is Not-a-Number.
See also nanoo below.
div
: If true a floating point divide by zero operation will cause an exceptionoflo
: If true a floating point overflow will cause an exceptionesr
: Enable stochastic roundingnanoo
: Enable Not-a-Number on overflow mode. When enabled half precision calculations that have overflowed will produce a Not-a-Number result, rather than saturating to the half precision max/min value, and the invalid operation (inv
) flag will be set
-
unsigned
getFpIctlRegIndex
() const¶ Return the register index of the Floating Point Initial Control Value register CSR_S.FP_ICTL.
-
unsigned
getDbgDataRegIndex
() const¶ Return the register index of CSR_C.DBG_DATA.
-
IpuLinkConfiguration
getIpuLinkConfiguration
() const¶ Return the ipu link configuration of this target.
-
IpuLinkTopology
getIpuLinkTopology
() const¶ Return the IPU link topology.
-
unsigned
getIpuLinkDomainSize
() const¶ Return the size of the IPU link domain.
That is the number of IPUs that are connected via IPU links.
-
Target
createVirtualTarget
(unsigned numIPUs, unsigned tilesPerIPU) const¶ Create a “virtual” target consisting of a subset of the target’s tiles.
This method returns a target object that references the same state as this target but only uses a subset of the target’s tiles.
- Return
The virtual target object.
- Parameters
numIPUs
: The number of IPUs the target should be for.tilesPerIPU
: The number of tiles per IPU.
Public Static Functions
-
Target
createCPUTarget
(bool accurateHalf = false)¶ Create a CPU target.
Create a target for executing a simple graph on the CPU. This target will have 1 IPU with 1 tile on 1 worker thread.
This should only be used for simple functional testing.
- Return
A Target object that can be used to create a graph.
-
Target
createIPUTarget
(unsigned numIPUs, StringRef systemType, const OptionFlags &opts = {})¶ Create an IPU target.
Create an IPU target with a specified number of IPUs based on the given system type.
- Return
A Target object that can be used to create a graph.
- Parameters
numIPUs
: The number of IPUs the target should be for.systemType
: The ID of the system. Possible options:"ipu1"
opts
: The option passed to the target.
-
Target
createIPUTarget
(unsigned numIPUs, unsigned tilesPerIPU, StringRef systemType, const OptionFlags &opts = {})¶ Create an IPU target with a virtual number of tiles.
Create an IPU target with a specified number of IPUs based on the given system type. In addition, the number of tiles can be restricted to a smaller virtual number of observable tiles.
- Return
A Target object that can be used to create a graph.
- Parameters
numIPUs
: The number of IPUs the target should be for.tilesPerIPU
: The number of tiles per IPU.systemType
: The ID of the system. Possible options:"ipu1"
opts
: The option passed to the target.
-
Target
createIPUTarget
(unsigned numIPUs, StringRef systemType, const core::TargetOptions &opts)¶ Create an IPU target.
Create an IPU target with a specified number of IPUs based on the given system type.
- Return
A Target object that can be used to create a graph.
- Parameters
numIPUs
: The number of IPUs the target should be for.systemType
: The ID of the system. Possible options:"ipu1"
opts
: The option passed to the target.
-
Target
createIPUTarget
(unsigned numIPUs, unsigned tilesPerIPU, StringRef systemType, const core::TargetOptions &opts)¶ Create an IPU target with a virtual number of tiles, and target options.
Create an IPU target with a specified number of IPUs based on the given system type. In addition, the number of tiles can be restricted to a smaller virtual number of observable tiles. This overload also accepts target options that can be obtained from another target.
- Return
A Target object that can be used to create a graph.
- Parameters
numIPUs
: The number of IPUs the target should be for.tilesPerIPU
: The number of tiles per IPU.systemType
: The ID of the system. Possible options:"ipu1"
opts
: The option passed to the target.
-
namespace
core
-
void
3.5.3. poplar/Device.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
Device
¶ - #include <Device.hpp>
A device refers to a physical entity that can execute code.
Devices should be obtained from a poplar::DeviceManager object or from appropriate factory poplar::Device::createXXXDevice(). Devices can not be copied but can be moved.
Public Functions
-
Device
()¶
-
~Device
()¶
-
unsigned
getId
() const¶ Get the numerical ID of this device as known by the DeviceManager.
-
bool
attach
() const¶ Try and acquire this device and lock it to the current process.
-
void
detach
() const¶ Release this device to other processes.
-
void
temporarilyDetach
() const¶ Temporarily detach from this device so it can be reattached to without reloading the executable.
The behaviour is undefined if another process acquires and uses the device inbetween. Use of this method is strongly discouraged and it will be removed in future.
-
void
getDriverVersion
(unsigned &major, unsigned &minor, unsigned &point) const¶ Retrieve driver version of the attached device.
Throws if the device is not attached or is not an IPU device.
-
bool
supportsRemoteBuffers
() const¶ Retrieve Remote Buffers availability from attached device.
Throws if the device is not attached or is not an IPU device.
-
bool
supportsGraphStreaming
() const¶ Retrieve Remote Buffers availability from attached device.
Throws if the device is not attached or is not an IPU device. Deprecated, please use supportsRemoteBuffers()
-
std::vector<int>
getNumaNodesUsedForIPUs
() const¶ Get the NUMA nodes that Poplar will use to execute code that communicates with each IPU that makes up this device.
If Poplar can’t execute code on the NUMA node for an IPU then this function returns -1 for that IPU. Poplar will interpret the -1 as disabling NUMA node pinning for that IPU.
Note that this function is not necessarily the same as getNumaTopology(), as it also handles NUMA node restrictions imposed by the Poplar process’ CPU affinity. For example on a machine with two NUMA nodes, with ids of 0 and 1, each connected to one CPU and one IPU then a Poplar process that is bound to CPU 1 will use CPU 1 to execute stream callbacks for IPUs on both NUMA node 0 and 1, so this function would return [-1, 1] whereas the getNumaTopology() would return [0, 1].
Note that if the look-up of available host NUMA nodes fails then this function will return a vector of
-1
s, with one element for each IPU.
-
std::vector<unsigned>
getDriverIDs
() const¶ Get the list of driver device IDs that make up this device.
-
void
reset
() const¶ Reset the device’s state.
-
Device
createVirtualDevice
(unsigned tilesPerIPU)¶ Create a virtual device with a restricted number of tiles per IPU.
This method provides a smaller “virtual” device whose target only shows a subset of the tiles on the underlying device.
The calling object becomes a null device (the underlying device is moved into the returned Device object).
Public Static Functions
-
Device
createCPUDevice
()¶ Create a device that executes vertex code on the host CPU.
This is only suitable for running small amounts of code; for example, for functional testing. It may not reproduce exactly the same functionality as running on an IPU. Also, functions such as Engine::getTileClockFrequency() may not return meaningful results.
-
Device
createSimulatorDevice
(const Target &target, const OptionFlags &options = {})¶
-
-
namespace
core
-
class
3.5.4. poplar/DeviceManager.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
DeviceManager
¶ - #include <DeviceManager.hpp>
A DeviceManager is able to enumerate and return groups of physical IPUs connected to an entity/host.
It returns such a group of IPUs as a single poplar::Device with a unique device manager id.
The physical devices within any returned Device may overlap with other Devices returned.
Any poplar::Device(s) returned can not be copied but can be moved for further use.
It is thread safe to both construct multiple DeviceManager’s in different threads and use them at the same time (although both threads might return the same device and therefore only one will succeed in attaching to it). It is also thread safe to use the same DeviceManager in different threads.
Public Functions
-
DeviceManager
()¶
-
DeviceManager
(const DeviceManager&)¶
-
DeviceManager
(DeviceManager&&)¶
-
~DeviceManager
()¶
-
std::vector<Device>
getDevices
(const OptionFlags &opts = {}) const¶ Get the list of all devices.
-
std::vector<Device>
getDevices
(TargetType type, unsigned requiredNumIPUs, const OptionFlags &opts = {}) const¶ Get the list of all devices fulfilling the specified criteria.
Depending on the criteria, the list may be empty - for example, if the
requiredNumIPUs
cannot be satisfied by any available device configurations. To view available device configurations, see the gc-info command line tool.- Return
A potentially empty list of matching devices
- Parameters
type
: The desired target type (IPU, IPU_Model, CPU)requiredNumIPUs
: Number of IPUs requiredopts
: The arguments passed to the target (optional)
-
Device
getDevice
(unsigned deviceManagerId, const OptionFlags &opts = {}) const¶ Get a specific device by its device manager id.
- Return
A matching device
- Parameters
deviceManagerId
: The ID of the requested device. The ID is that returned by thegc-info
command. This can specify a single device or a group of devices.opts
: The arguments passed to the target (optional)
-
std::vector<unsigned>
getChildDeviceIds
(unsigned parentId, unsigned numChildDeviceIpus = 1) const¶ Get the deviceIds of the child devices of a multi-IPU device.
A multi-IPU device will fully overlap “child” devices that are made out of the same IPUs. This method returns the set of child devices.
- Parameters
parentId
: The device ID of the parent devicenumChildDeviceIpus
: The number of IPUs the child devices must contain to be considered a child.
Public Static Functions
-
DeviceManager
createDeviceManager
()¶ Create a device manager for the current host.
-
-
namespace
core
-
class
3.5.5. poplar/IpuLinkConfiguration.hpp¶
-
namespace
poplar
Poplar classes and functions.
Enums
Functions
-
std::ostream &
operator<<
(std::ostream &os, IpuLinkConfiguration ic)¶
-
std::ostream &
3.6. Graph execution¶
3.6.1. poplar/Engine.hpp¶
-
namespace
poplar
Poplar classes and functions.
Functions
-
Executable
compileGraph
(const Graph &graph, ArrayRef<program::Program> progs, const OptionFlags &opt = {}, ProgressFunc progressCallBack = ProgressFunc(), const DebugContext &debugContext = {})¶ Compile the given graph and programs to make an executable that can be executed using a poplar::Engine.
- Parameters
graph
: The graph to compile.progs
: The list of programs to run over the graph. Each program can be run separately by calling the run() method of the Engine with the argument being the index of the program to run in this list.opt
: Options that can be used to control compilation and execution. The available options are listed under Engine.progressCallBack
: A function that will be called to indicate engine compilation progress. See Engine::ProgressFunc for more information.debugContext
: Optional DebugId and debug name.
- Exceptions
invalid_option
: If any of the options passed inopt
were not recognised or improperly formatted.link_error
: If program linking fails; for example, due to undefined symbols or lack of memory on a tile.
-
Executable
compileGraph
(Graph &&graph, ArrayRef<program::Program> progs, const OptionFlags &opt = {}, ProgressFunc progressCallBack = ProgressFunc(), const DebugContext &debugContext = {})¶ - Deprecated:
This moving compileGraph interface is deprecated.
-
class
Engine
¶ - #include <Engine.hpp>
A graph compute engine.
The Engine class provides the ability to execute a graph program.
Engine creation options
Options can be overridden with the environment variable
POPLAR_ENGINE_OPTIONS
. For example:POPLAR_ENGINE_OPTIONS='{"target.deterministicWorkers":"true"}'
Engine creation options: Debug
debug.allowOutOfMemory
(true, false) [=false]If true, allow out-of-memory while compiling and linking.
debug.computeInstrumentationLevel
(vertex, tile, device, ipu) [=tile]The granularity of compute instrumentation. This option has no effect unless debug.instrumentCompute is true.
vertex: Store the last cycle count of each vertex on every tile
tile: Store the last cycle count of each compute set on every tile
device: Store the last cycle count of each compute set on one tile. This saves memory compared to
tile
(since the cycle counts are always live and this needs to store them on only one tile), but it loses all per-tile cycle information. It works by adding a sync after each compute set and timing how long it takes to get to that sync, so effectively it measures the cycle time of the longest-running tile in the compute set.ipu: Similar to “device”, but instead of storing the cycle counts on a single tile across all IPUs, it stores them on one tile per IPU which avoids the need for global syncs.
debug.retainDebugInformation
(true, false) [=true] Retain compilation information to help with debugging. Must be true if profiling is enabled. Must be true if deprecated Engine connectStream / connectStreamToCallback / copy{To,From}RemoteBuffer methods are used.debug.cpuMultiThreadExecution
(true, false) [=true] If true, operations are executed using multiple host threads for a CPU or IPU model target. Setting to false may simplify debugging at the cost of reduced performance.debug.instrument
(true, false) [=false]If true, enable all instrument options (below). This will instruct the engine to add cycle counters to the compiled program to enable the execution profile to be retrieved after the program is run. This is only available for an IPU target (not an IPU Model target). Note that the more specific instrumentation options may override the default. For example,
{"debug.instrument":"true", "debug.instrumentExternalExchange":"false"}
will instrument everything apart from external exchange.
debug.instrumentCompute
(true, false) [=false]If true, enable instrumentation of compute sets. See
debug.instrument
.debug.instrumentExternalExchange
(true, false) [=false]If true, enable instrumentation of external exchanges. See
debug.instrument
.debug.instrumentControlFlow
(true, false) [=false]If true, enable instrumentation of loops and conditionals. See
debug.instrument
.debug.outputAllSymbols
(true, false) [=false]If true, output additional symbols to the ELF files that are not required but aid debugging.
debug.exceptOnSOCError
(true, false) [=false]If true, throw an exception on a SoC error. If false the error will be reported in the log instead.
debug.checkForSOCErrorAtRun
(true, false) [=false]If true, check for SoC errors before and after program execution.
debug.profilingTile
Integer [=Tiles per IPU - 1]The tile on which to store the cycle counter for every comput set. This has no effect unless
debug.computeInstrumentationLevel
is set todevice
.debug.branchRecordTile
Integer [=NTILES-1]The tile on which to store the branch record. This has no effect unless
debug.instrumentControlFlow
flag is set. In CPU target, this option has no effect. In IPU model, it only affects the memory profile.debug.runtimeVerify
(true, false) [=false]If true, expensive verification steps are enabled at runtime.
debug.trace
(true, false) [=false]If true, a trace is printed to the error stream with the state of every edge before and after the execution of a compute set or exchange.
debug.traceFile
StringOnly used if
debug.trace
is true. If set, the debug trace is output to the specified file instead of the error stream.debug.verify
(true, false) [=false]If true, expensive verification steps are enabled at compile time. The checks mostly focus on exchange code, including the following:
ensuring variables have been set,
ensuring section/instruction alignment is correct,
and ensuring the total number of bytes received is as expected.
In addition after laying out memory we verify the memory constraints on variables are satisfied.
debug.supervisorStackSizeInBytes
IntegerIf set, the automatically computed stack size for supervisor threads will be overridden with the specified value (in bytes) for all tiles.
debug.workerStackSizeInBytes
IntegerIf set, the automatically computed stack size for worker threads will be overridden with the specified value (in bytes) for all tiles.
Engine creation options: Optimisations
opt.maxCompilationThreads
Integer [=0]The maximum number of threads to use during compilation. A value of 0 means the hardware will be fully utilised.
opt.maxLinkerThreads
Integer [=0]The maximum number of threads to use during compilation. A value of 0 means the same number will be used as were used for compilation.
opt.enableSwSyncs
(true, false) [=false]If true, use a software synchronisation scheme to synchronise with the host following a stream copy. The software based synchronisation scheme lets IPUs start executing the next step as soon as they have finished sending and receiving all their data, without having to wait for every IPU to reach the end of the stream copy.
opt.internalExchangeOptimisationTarget
(balanced, cycles) [=cycles]What balance of heuristics to use when generating exchange code.
cycles
will focus completely on speed whereasbalanced
will sacrifice some speed to attempt to reduce the amount of always live memory produced.opt.limitVertexStateToLower256K
(true, false) [=false]Enable this option to optimise the control code by allocating all of the vertex state in the first 256KB of memory. This has a disadvantage that this is the same range of memory that the code must live in so if the sum of the two is larger than that then the model will fail to compile.
Engine creation options: Profiler
The Profiler options control how Poplar generates the reports that can be viewed in the PopVision Graph Analyser (e.g. graph and execution profiles)
profiler.format
(“v1”, “experimental”, “v3”) [=”v1”]This option sets the version of the profiler format. Note the “experimental” version may break tools that expect the “v1” format. Also note the “experimental” version is not backward compatible and subject to change. V3 format reduces the memory footprint of the profiler.
profiler.replicaToProfile
Integer [=All replicas]Specifies which replica (0-based index) will be profiled. Note that a high-level summary of several metrics and timings will still be provided for the whole execution.
Engine creation options: Target
target.deterministicWorkers
(true, false, portable) [=true]Ensure that the mapping of vertices to worker threads is the same for repeated execution either on the same IPU (true), or on every IPU (portable). This guarantee does not hold following breakpoints or exceptions.
target.saveArchive
StringIf set, the binary archive will be saved to the specified filename during graph compilation. This archive contains the Elf files for each tile. No archive will be saved unless this option is set.
target.syncMethod
(polling, hybrid, default) [=default]Controls how the host determines when an IPU wants to sync
polling: Using polling to determine when an IPU wants to sync.
hybrid: Use a mixture of interrupts and polling to determine an IPU wants to sync.
default: Choose a sensible default method based on the device type. Currently we default to polling for all device types but this may change in future.
target.syncPollPeriodUs
Integer [=0]The period to use when polling for a host sync, in microseconds.
target.hostSyncTimeout
Integer [=300]The amount of time to wait for a response from the IPU after running a program, in seconds. “0” means no timeout.
target.gatewayMode
(true, false) [=false]Enable GWMODE (Gateway Mode) in the PCI Complex
target.gatewayWriteCombining
(true, false) [=false]Optimise write to host code to use IPU machine Gateway write combining.
target.maxStreamCallbackThreadsPerNumaNode
Integer [=0]The maximum number of threads per NUMA node to use to execute stream callbacks. A value of 0 means the main thread will execute all of the callbacks, which is the default because a non-zero number of threads requires thread-safe callbacks.
A value of “auto” means the hardware will be fully utilised, this typically means up to one thread per CPU core is used.
Note that this is the maximum number of threads in addition to the main thread, for example on a system with two NUMA nodes setting this option to 1 would mean that a total of three threads could execute callbacks with one thread pinned to each NUMA node and the main thread operating on one of the two nodes as well (assuming the main thread is free to execute callbacks).
Engine creation options: Report generation
The report generation options will automatically output the Poplar reports that can be viewed in the PopVision Graph Analyser.
These options provide a basic ability to capture the reports. For more complex use cases the reports should be generated programmatically via functions in the framework (TensorFlow, PopART or Poplar) in which the application is written.
autoReport.all
(true, false) [=false]Output all the available reports described below.
You can exclude individual reports by combining options. For example, this will generate all reports apart from the serialized graph:
{"autoReport.all":"true", "autoReport.outputSerializedGraph":"false"}
autoReport.outputGraphProfile
(true, false) [=false]Output the graph profile report:
graph.cbor
(V1) orprofile.pop
(V3). This is the same as the output ofEngine::getGraphProfile
.autoReport.outputLoweredVars
(true, false) [=false]Output the lowered variables file report:
vars.capnp
. This is equivalent to using thedebug.loweredVarDumpFile
option with the filename set tovars.capnp
.autoReport.outputArchive
(true, false) [=false]Output the archive report:
archive.a
. This is equivalent to using thetarget.saveArchive
option with the filename set toarchive.a
.autoReport.outputSerializedGraph
(true, false) [=false]Output the serialized graph: serialized_graph.capnp.
autoReport.outputExecutionProfile
(true, false) [=false]Output the execution profile report:
execution.cbor
(V1) orprofile.pop
(V3). This is the same as the output ofEngine::getExecutionProfile
.By default this setting will also set
debug.instrument
to true. If you do not want instrumentation enabled you can setautoReport.outputExecutionProfile
ordebug.instrument
to false.autoReport.streamAtEachRun
(true, false) [=true]% Applies to profiler format V3 or higher: Enable/disable the streaming of the execution profile to disk at each run. If false, the whole execution will be written to disk on Engine destruction (note some frameworks like Tensorflow may not properly destroy the Engine).
autoReport.outputDebugInfo
(true, false) [=false]Output debug info:
debug.json
. This file gathers the data in every DebugInfo object created. Elements in the graph report with debugIds can be related to these DebugInfo objects.autoReport.executionProfileProgramRunCount
Integer [=2]Specify how many runs of each program to capture in the execution profile.
autoReport.directory
String [=./]Specify which directory you want the reports to be written to. By default they will be written to the current working directory.
Engine creation options: Other
prng.enableStochasticRounding
(true, false) [=false]If true, stochastic rounding is enabled.
You can also enable or disable stochastic rounding using the functions setFloatingPointBehaviour() and setStochasticRounding(). For setFloatingPointBehaviour() the default behaviour is to enable stochastic rounding.
prng.seed
Integer [=0]Base seed for PRNG initialisation.
Public Types
-
using
ProgressFunc
= std::function<void(int, int)>¶ Callback function used to to indicate engine compilation progress.
The function is passed two integers. The first is the progress value and the second is the maximum value for the progress.
If a progress callback is used, the function should not block. All calls to the callback function will be made in a single dedicated thread so blocking in the callback will block the receipt of further notifications (but will not block compilation from progressing). The callback should not use Poplar objects or functions relating to the Graph, Engine or Device that are being compiled.
Public Functions
-
Engine
(const Graph &graph, ArrayRef<program::Program> progs, const OptionFlags &opt = {}, ProgressFunc progressCallBack = ProgressFunc(), const DebugContext &debugContext = {})¶ Construct the engine from a graph and a list of programs.
- Parameters
graph
: The graph to compile into the engine.progs
: The list of programs to run over the graph. Each program can be run separately by calling the run() method of the Engine with the argument being the index of the program to run in this list.opt
: Options that can be used to control compilation and execution. The available options are listed under Engine.progressCallBack
: A function that will be called to indicate engine compilation progress. See Engine::ProgressFunc for more information.debugContext
: Optional DebugId and debug name.
- Exceptions
invalid_option
: If any of the options passed inopt
were not recognised or improperly formatted.link_error
: If program linking fails; for example, due to undefined symbols or lack of memory on a tile.
-
Engine
(Graph &&graph, ArrayRef<program::Program> progs, const OptionFlags &opt = {}, ProgressFunc progressCallBack = ProgressFunc(), const DebugContext &debugContext = {})¶ - Deprecated:
This moving Engine constructor is deprecated.
-
Engine
(const Graph &graph, program::Program prog, const OptionFlags &opt = {}, ProgressFunc progressCallBack = ProgressFunc(), const DebugContext &debugContext = {})¶ Construct the engine from a graph and a program.
- Parameters
graph
: The graph to compile into the engine.prog
: The program to run over the graph. This program is run when the run() method is called on the Engine.opt
: Options that can be used to control compilation and execution. The available options are listed under Engine.progressCallBack
: A function that will be called to indicate engine compilation progress. See Engine::ProgressFunc for more information.debugContext
: Optional DebugId and debug name.
- Exceptions
invalid_option
: If any of the options passed inopt
were not recognised or improperly formatted.link_error
: If the program linking fails; for example, due to undefined symbols or lack of memory on a tile.
-
Engine
(Graph &&graph, program::Program prog, const OptionFlags &opt = {}, ProgressFunc progressCallBack = ProgressFunc(), const DebugContext &debugContext = {})¶ - Deprecated:
This moving Engine constructor is deprecated.
-
Engine
(Executable &&exe, const OptionFlags &opt = {}, const DebugContext &debugContext = {})¶ Construct the engine from a precompiled executable.
- Parameters
exe
: The precompiled executable. This can be created using poplar::compileGraph().opt
: Options that can be used to control execution. These must be the same as the flags passed to compileGraph(). The available options are listed under Engine.debugContext
: Optional DebugId and debug name.
- Exceptions
invalid_option
: If any of the options passed inopt
were not recognised or improperly formatted.
-
~Engine
()¶
-
void
prepare
(const Device &device)¶ Prepare the device for loading.
This configures the device ready for loading binary code.
- Parameters
device
: The device to load onto.
-
void
deploy
()¶ Load the engine.
This loads binary code. The device must have been prepare()ed previously.
-
void
load
(const Device &device)¶ Load the compiled program/graph onto a device.
This function will load all binary code and data onto the device ready for execution. This is a shortcut to separate prepare() and deploy() calls.
- Parameters
device
: The device to load onto.
-
void
run
(unsigned prog = 0, const std::string &debugName = "")¶ Run the graph program.
This function will execute the graph program. Note that the program needs to have already been loaded onto a device otherwise an exception will occur.
- Parameters
prog
: The index of the program to run. If this is greater than or equal to the number of programs given in the constructor then an exception is thrown.debugName
: Run name (for debugging/analysis).
-
void
loadAndRun
(const Device &device, unsigned prog = 0)¶ Run the graph program.
This function will load the program/graph onto the device and then execute the graph program.
- Parameters
prog
: The index of the program to run. If this is greater than or equal to the number of programs given in the constructor then an exception is thrown.
-
TimerTimePoint
getTimeStamp
()¶ Get a record of the current host and device time.
Details depend on the underlying device used.
-
const ProfileValue &
getGraphProfile
() const¶ Get a report containing profiling data for the graph on the underlying device.
This is only valid to call if the underlying device of the graph is an IPU model device.
- Return
A reference to an internal profile.
- Exceptions
profiling_disabled
: If the device is not an IPU or IPU model.
-
const ProfileValue &
getExecutionProfile
()¶ Get a report containing profiling data for programs executed with this engine since this engine was constructed/the execution report was last reset.
See the Poplar and PopLibs User Guide for details of the data in the report.
- Return
A reference to an internal profile. Be aware that if you store a reference to this, rather than copying it, then it may change when you run further programs.
- Exceptions
profiling_disabled
: If the device is not an IPU or IPU model.
-
ProfileValue
getProfile
()¶ Get a report containing profiling data for both the graph and the programs executed with this engine.
This is equivalent to getting both the graph profile and execution profiles in a single ProfileValue.
See the Poplar and PopLibs User Guide for details of the data in the report.
- Return
A copy of the internal profile.
- Exceptions
profiling_disabled
: If the device is not an IPU or IPU model.poplar_error
: If profiler format is not “v1” or “experimental” (v2)
-
void
resetExecutionProfile
()¶ Reset execution profile.
When programs are run their profiles are appended to the execution profile. This discards profiling information for previously executed programs.
-
void
disableExecutionProfiling
()¶ Pause execution profiling.
Subsequent engine.run() calls are executed without being profiled until a subsequent call to
enableExecutionProfiling
.For example, you can exclude individual programs from a profile like this:
engine.disableExecutionProfiling(); engine.run(...); engine.enableExecutionProfiling();
-
void
enableExecutionProfiling
()¶ Enable execution profiling.
Subsequent engine.run() calls are profiled when executed.
-
void
printProfileSummary
(std::ostream &outputStream, const OptionFlags &opt = {})¶ Get and print the summary of a report with the given options.
This is equivalent to getting and printing the summary of both the graph and execution reports using poplar::printProfileSummary().
- Parameters
outputStream
: A stream to write the summary to.opt
: A set of option flags configuring the contents of the report. All can be “true” or “false”. The default is “false”.The available options are:
showVarStorage
(true, false)showOptimizations
(true, false)showExecutionSteps
(true, false)
- Exceptions
profiling_disabled
: If the device is not an IPU model device.invalid_option
: If any of the options passed inopt
were not recognised or improperly formatted.
-
void
reportIntervals
(std::ostream &outputStream)¶ Write a CSV data file to a specified output stream containing the number of tiles active over time in cycles for compute, synchronisation and exchange phases.
Each row contains the following entries:
begin time in cycles
end time in cycles
number of tiles participating in compute
number of tiles participating in exchange
number of tiles participating in synchronisation
Because tiles execute a number of threads (up to 6) in parallel a single “thread cycle” may only be executed every 6 tile clock cycles. The cycles reported by this function are tile clock cycles rather than thread cycles.
- Parameters
outputStream
: An output stream for the CSV data to be written to.
- Exceptions
profiling_disabled
: If the device has no profiling enabled.
-
void
readTensor
(StringRef handle, void *buf)¶ Synchronous copy of a buffer of data from a specific tensor in the device into a host size buffer.
The tensor must have been marked as an output tensor. The buffer must have room for all of the tensor data. The handle should match the one passed to Graph::createHostRead()
- Deprecated:
Use readTensor(StringRef, void*, void*) instead.
- See
- Parameters
handle
: The source host copy handle.buf
: The destination of the read.
-
void
readTensor
(StringRef handle, void *buf, void *bufEnd)¶ Synchronous copy of a buffer of data from a specific tensor in the device into a host size buffer.
The tensor must have been marked as an output tensor. The buffer must have room for all of the tensor data. Buffer end address required for sizes verification. The handle should match the one passed to Graph::createHostRead()
- See
- Parameters
handle
: The source host copy handle.buf
: The destination of the read.bufEnd
: The end address of destination space
-
void
writeTensor
(StringRef handle, const void *buf)¶ Synchronous copy of a buffer of data from the host to a specific tensor in the device.
The tensor must have been marked as an input tensor. The buffer must have enough data for the whole tensor. The handle should match the one passed to Graph::createHostWrite()
- See
- Parameters
handle
: The destination host copy handle.buf
: The source of the write.
-
void
writeTensor
(StringRef handle, const void *buf, const void *bufEnd)¶ Synchronous copy of a buffer of data from the host to a specific tensor in the device.
The tensor must have been marked as an input tensor. Buffer end address required for sizes verification. The handle should match the one passed to Graph::createHostWrite()
- See
- Parameters
handle
: The destination host copy handle.buf
: The source of the write.bufEnd
: The end address of source space.
-
void
connectStream
(StringRef handle, void *begin, void *end)¶ Connect a stream to a circular buffer in memory.
Each time data is copied to/from the stream the pointer for the next transfer is incremented within the bounds given.
- Parameters
handle
: The name of the stream to connect tobegin
: Pointer to the start of the circular bufferend
: Pointer to the end of the circular buffer.
-
void
connectStream
(const DataStream &stream, void *begin, void *end)¶ Connect a stream to a circular buffer in memory.
Each time data is copied to/from the stream the pointer for the next transfer is incremented within the bounds given.
- Deprecated:
Use connectStream(StringRef, void*, void*) instead.
- Parameters
stream
: The stream to connect tobegin
: Pointer to the start of the circular bufferend
: Pointer to the end of the circular buffer.
-
void
connectStream
(StringRef handle, void *p)¶ Connect a stream to a fixed location in memory.
Each time data is copied to/from the stream this location will be read/written.
- Parameters
handle
: The name of the stream to connect top
: The pointer to the memory buffer
-
void
connectStream
(const DataStream &stream, void *p)¶ Connect a stream to a fixed location in memory.
Each time data is copied to/from the stream this location will be read/written.
- Deprecated:
Use connectStream(StringRef, void) instead.
- Parameters
stream
: The stream to connect top
: The pointer to the memory buffer
-
void
connectStreamToCallback
(StringRef handle, StreamCallbackHandle f)¶ Connect a stream to a callback taking a pointer to the location in memory to copy into/from.
This will be called whenever the stream will be read/was written by the device. The given memory location will only be valid to read from/write to for the duration of the callback.
- Parameters
handle
: The name of the stream to connect to.f
: Callback to be called whenever the stream is to be read/was written by the device.
-
void
connectStreamToCallback
(const DataStream &stream, StreamCallbackHandle f)¶ Connect a stream to a callback taking a pointer to the location in memory to copy into/from.
This will be called whenever the stream will be read/was written by the device. The given memory location will only be valid to read from/write to for the duration of the callback.
- Parameters
stream
: The stream to connect to.f
: Callback to be called whenever the stream is to be read/was written by the device.
-
void
connectStreamToCallback
(StringRef handle, unsigned index, StreamCallbackHandle f)¶ Connect a replicated stream to a callback taking a pointer to the location in memory to copy into/from.
This will be called whenever the stream will be read/was written by the device. The given memory location will only be valid to read from/write to for the duration of the callback.
- Parameters
handle
: The name of the stream to connect to.index
: The replicated index to connect to.f
: Callback to be called whenever the stream is to be read/was written by the device.
-
void
connectStreamToCallback
(const DataStream &stream, unsigned index, StreamCallbackHandle f)¶ Connect a replicated stream to a callback taking a pointer to the location in memory to copy into/from.
This will be called whenever the stream will be read/was written by the device. The given memory location will only be valid to read from/write to for the duration of the callback.
- Deprecated:
Use connectStreamToCallback(StringRef, unsigned, StreamCallbackHanle) instead.
- Parameters
stream
: The stream to connect to.index
: The replicated index to connect to.f
: Callback to be called whenever the stream is to be read/was written by the device.
-
void
copyFromRemoteBuffer
(StringRef handle, void *w, int repeatIndex, unsigned replicationIndex = 0)¶ Copy from a remote buffer to a user buffer w.
- Parameters
handle
: The name of the remote buffer to copy from.w
: The user buffer to copy to.repeatIndex
: The index in the remote buffer to copy from.replicationIndex
: The replicated graph index.
-
void
copyFromRemoteBuffer
(const RemoteBuffer &buffer, void *w, int repeatIndex, unsigned replicationIndex = 0)¶ Copy from a remote buffer to a user buffer w.
- Parameters
buffer
: The remote buffer to copy from.w
: The user buffer to copy to.repeatIndex
: The index in the remote buffer to copy from.replicationIndex
: The replicated graph index.
-
void
copyToRemoteBuffer
(void *w, StringRef handle, int repeatIndex, unsigned replicationIndex = 0)¶ Copy to a remote buffer from a user buffer w.
- Parameters
w
: The user buffer to copy from.handle
: The remote buffer to copy to.repeatIndex
: The index in the remote buffer to copy to.replicationIndex
: The replicated graph index.
-
void
copyToRemoteBuffer
(void *w, const RemoteBuffer &buffer, int repeatIndex, unsigned replicationIndex = 0)¶ Copy to a remote buffer from a user buffer w.
- Parameters
w
: The user buffer to copy from.buffer
: The remote buffer to copy to.repeatIndex
: The index in the remote buffer to copy to.replicationIndex
: The replicated graph index.
-
std::vector<std::string>
listStreams
() const¶ Return a list of all streams in the engine.
- Return
Vector of strings each of which is a stream’s handle postfixed with ‘+’ or ‘-‘ indicating whether the stream is a host-write or a host-read respectively.
-
void
setPrintStream
(std::ostream &stream)¶ Set output stream for printf commands.
- Parameters
stream
: The output stream to use.
-
void
setPrintTensorStream
(std::ostream &stream)¶ Set the output stream for PrintTensor programs.
By default tensors are printed to stderr.
- Parameters
stream
: The output stream to use.
-
OptionFlags
getEngineOptions
() const¶ Returns options the engine was created with.
Public Static Functions
-
std::string
reportTiming
(const TimerTimePoint &start, const TimerTimePoint &end)¶ Get a timing report for the measured interval.
Details depend on the underlying device used.
- Parameters
start
: Start time of reportend
: End time of report
-
namespace
core
-
Executable
3.6.2. poplar/StreamCallback.hpp¶
-
template<typename
Result
, typenameRet
>
structis_invocable_impl
<Result, Ret, void_type<typename Result::type>> : public std::is_void<Ret>¶
-
namespace
poplar
Poplar classes and functions.
-
class
LegacyStreamCallback
: public poplar::StreamCallback¶ - #include <StreamCallback.hpp>
Convenience StreamCallback specialization for implementations that do not support prefetch/complete operations.
-
class
StreamCallback
¶ - #include <StreamCallback.hpp>
Interface used during stream copies to produce/consume the data being exchanged between the host and the device.
In regular stream copies,
fetch
andcomplete
functions are called as a result of the device requesting the data transfer.If the following engine options are set,
prefetch
function will be called after an ongoing host-to-device transfer of the same stream completes:exchange.streamBufferOverlap=none
exchange.enablePrefetch=true
Subclassed by poplar::LegacyStreamCallback
Public Functions
-
~StreamCallback
() = default¶
-
Result
prefetch
(void *p) = 0¶ Callback function to fill the host buffer (host-to-device streams only).
This function is called speculatively, this means it might still be called even if no additional copies for this stream exist for the remaining execution of the program.
The following situations are possible during the invocation:
There is more data available for consumption (A)
Data is temporarily not available during the time this function is called (B)
The stream reached the end and so no more data is available (C)
The return value indicates if the invocation resulted in the buffer being successfully filled. In the first case (A), the function shall return
Result::Success
. A call to complete() will follow if the program ends up transferring the data. Otherwise (scenarios B and C), it must returnResult::NotAvailable
. Calls to fetch() and then complete() will follow if the transfer takes place.Note that when using a buffered data stream (see Graph::addHostToDeviceFIFO(),
bufferingDepth
option) there can be multiple calls to prefetch() before a corresponding complete() is called. In some circumstances prefetched data is invalidated and not read, and therefore will have no corresponding complete(), this is notified with invalidatePrefetched().- Return
Result::Success
if the function was able to fill the buffer with data, orResult::NotAvailable
otherwise.- Parameters
p
: Location of the buffer. It will only be valid for the duration of the function.
-
void
complete
() = 0¶ Notifies that the data involved in the last prefetch/fetch invocation is used by the device.
It usually means that a speculative read was a hit, and the callback can move on to the next piece of input.
-
void
invalidatePrefetched
()¶ Notifies when the engine will reset this stream (invalidating any prefetched data which has not been read).
-
void
fetch
(void*) = 0¶ Callback function to fill the host buffer.
This function is called as a result of a stream copy, unless the last
prefetch
invocation was successful.It must always fill the buffer with more data and it is followed by a call to
complete
.
-
class
StreamCallbackHandle
¶ - #include <StreamCallback.hpp>
Wrapper for StreamCallback instances.
Provides backwards compatibility with C++ lambda expressions and
std::function
instances.Public Functions
-
template<class
CallbackImpl
, typename = typename std::enable_if<std::is_base_of<StreamCallback, CallbackImpl>::value>::type>StreamCallbackHandle
(std::unique_ptr<CallbackImpl> f)¶ Constructs a handle from an instance of a stream callback implementation.
This constructor only participates in overload resolution if CallbackImpl is derived from poplar::StreamCallback (i.e. it is an implementation of the callback interface).
-
template<class
F
, typename = typename std::enable_if<traits::is_callback<F>::value>::type>StreamCallbackHandle
(F &&f)¶ Constructs a handle from a callable instance.
This constructor only participates in overload resolution if F satisfies the requirements of a Function Object. It transforms
f
into a LegacyStreamCallback implementation.
-
StreamCallbackHandle
(const StreamCallbackHandle&) = delete¶
-
StreamCallbackHandle
(StreamCallbackHandle&&) = default¶
-
operator std::unique_ptr<StreamCallback>
() &&¶ Extracts the callback implementation from the handle.
Private Members
-
std::unique_ptr<StreamCallback>
callback
¶
Private Static Functions
-
template<class
F
>
std::unique_ptr<StreamCallback>makeCallback
(F &&f)¶
-
template<class
-
namespace
traits
¶ Typedefs
-
using
void_type
= void¶
-
template<typename
F
>
structis_callback
: public poplar::traits::is_invocable_impl<std::result_of<F&(void*)>, void>¶
-
template<typename
Result
, typenameRet
, typename = void>
structis_invocable_impl
: public false_type¶ Subclassed by poplar::traits::is_callback< F >
-
template<typename Result, typename Ret> type > > : public std::is_void< Ret >
-
using
-
class
3.7. Serializing executable state¶
3.7.1. poplar/Executable.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
class
Executable
¶ - #include <Executable.hpp>
An instance of poplar::Executable contains all of the information needed to run a program on an IPU device.
It can be saved to or loaded from disk.
Public Functions
-
~Executable
()¶
-
Executable
(Executable &&other)¶
-
Executable &
operator=
(Executable &&other)¶
-
void
serialize
(std::ostream &out) const¶ Serialize an executable to a stream.
All of the binary files and metadata needed to run a Poplar executable will be written to the stream. Currently the format is opaque, and compatibility between different versions of Poplar is not guaranteed.
- Parameters
out
: The stream to write to. It must be seekable.
- Exceptions
poplar_error
: if the target is not an IPU - this cannot be used to serialise CPU or IPU_MODEL executables.
Public Static Functions
-
Executable
deserialize
(std::istream &in)¶ Load an executable from a stream.
- Parameters
in
: The stream to read from. It must be seekable.
Friends
- friend class Engine
-
-
namespace
core
-
class
3.8. Profiling & debugging¶
3.8.1. poplar/DebugContext.hpp¶
Defines
-
SUPPORTS_LOCATION_BUILTINS
¶
-
namespace
poplar
Poplar classes and functions.
Enums
Functions
-
std::ostream &
operator<<
(std::ostream &os, const DebugNameAndId &dnai)¶ Display the path name of the DebugNameAndId.
- Return
The ostream written to
- Parameters
os
: The ostream to output todnai
: The DebugNameAndId to display
-
std::ostream &
operator<<
(std::ostream &os, const DebugContext &dc)¶ Display the path name of the DebugContext.
- Return
The ostream written to
- Parameters
os
: The ostream to output todc
: The DebugContext to display
-
class
DebugContext
¶ - #include <DebugContext.hpp>
DebugContext gathers the common external parameters of the context of an operation.
As an extension to DebugNameAndId, DebugContext bundles a name and a DebugId as well as the file and line in the source code where it is invoked.
Note that to reflect the specific line where an invocation took place, the DebugContext object must be constructed in the same line of the invocation. For instance, if a function
foo
wants to capture the DebugContext of its invocation, it should be called like this: foo(DebugContext{}); rather than: DebugContext debugContext; foo(debugContext); Although typicallyfoo
would accept a default argument: void foo(const DebugContext &debugContext = {}); so that the DebugContext can be automatically captured: foo();A DebugContext ultimate goal is to be passed to the constructor of a DebugInfo. The DebugContext carries the DebugId of the parent DebugInfo to keep a hierarchical relationship. A typical flow would be: Initial DebugContext is (implicitly) created in
foo
default argument and used to create the initial DebugInfo. Thenfoo2
is called. void foo(const DebugContext &debugContext = {}) { DebugInfo debugInfo{debugContext}; foo2(debugInfo); }foo2
captures the DebugContext that contains the parent DebugId: void foo2(const DebugContext &debugContext) { DebugInfo debugInfo{debugContext}; } In this way, low-level operations and resources can be related to the high-level operation that triggered them.Public Functions
-
DebugContext
(SourceLocation loc = SourceLocation::Current())¶
-
DebugContext
(const char *name, SourceLocation loc = SourceLocation::Current())¶
-
DebugContext
(StringRef name, SourceLocation loc = SourceLocation::Current())¶
-
DebugContext
(std::string name, SourceLocation loc = SourceLocation::Current())¶
-
DebugContext
(const DebugInfo &debugInfo, std::string name = "", SourceLocation loc = SourceLocation::Current())¶
-
DebugContext
(const DebugNameAndId &debugNameAndId, std::string name = "", SourceLocation loc = SourceLocation::Current())¶
-
DebugContext
(const DebugContext &debugContext, std::string name = "")¶
-
DebugContext
(const DebugContext &debugContext, SourceLocation loc)¶
-
DebugContext
(DebugContext&&)¶
-
~DebugContext
()¶
-
std::string
getPathName
() const¶ Gets the pathname of this object as the concatenation of the parent name received in the constructor via DebugInfo or DebugNameAndId and the name explicitly set for this object.
-
-
class
DebugInfo
¶ - #include <DebugContext.hpp>
DebugInfo stores and persists a set of data that describes the context of an operation.
Some of that data is structured, such as the framework layer name (Poplar, PopLibs, PopART, and so on) or the file and line of the source code. But it can also be custom data set by the user through
setValue
method.In turn, the DebugInfo is passed to sub-operations of that operation so that resources (Programs, Variables, etc.) created in lower levels can be hierarchically related to the initial DebugInfo.
After execution, the created DebugInfo has been written to a file. At the same time, the operation resources have been persisted in the graph and execution profile, together with their DebugInfo Id. In this way, tools like PopVision can conveniently present to the user the operation, its resources, and its DebugInfo.
This class is expected to be derived to adapt to particular use cases (typically, by adding extra mandatory arguments to the constructor). Internally, derived classes can use setValue() to store the extra data to be persisted.
At object destruction, the DebugInfo data is passed to the Streamer to be written to a file. Thus, the Streamer should be initialized before any DebugInfo object gets destroyed, or it will not be persisted.
Subclassed by poputil::OpDebugInfo
Public Functions
-
DebugInfo
(const DebugContext &debugContext, std::string layer)¶ Constructor.
- Parameters
debugContext
: Captures the external context of the operation (for example, file and line of invocation).layer
: Name of the framework level (for example Poplar, PopLibs or PopART).
-
~DebugInfo
()¶
-
std::string
getPathName
() const¶ Gets the pathname of this object (as received from DebugContext).
-
bool
setValue
(std::string name, ProfileValue value)¶ Adds custom data to this object if “name” is not already set.
- Return
true if “name” was not already set, false otherwise.
- Parameters
name
: The key name of the data.value
: A ProfileValue object containing the custom data.
Public Static Functions
-
void
initializeStreamer
(const std::string &fileName, const DebugSerializationFormat &format = DebugSerializationFormat::CBOR)¶ Initializes the Streamer, unless it is already initialized (for example through env variables).
- Parameters
fileName
: The name of the file where all DebugInfos will be persisted.format
: The format of the file (JSON or CBOR).
-
-
class
DebugNameAndId
¶ - #include <DebugContext.hpp>
DebugNameAndId bundles a name and a DebugId to facilitate their propagation through function calls.
Public Functions
-
DebugNameAndId
(const char *name)¶
-
DebugNameAndId
(const DebugNameAndId &DebugNameAndId, std::string name = "")¶
-
DebugNameAndId &
operator=
(const DebugNameAndId &other)¶
-
~DebugNameAndId
()¶
-
std::string
getPathName
() const¶ Gets the pathname of this object as the concatenation of the parent name received in the constructor via DebugInfo or DebugNameAndId and the name explicitly set for this object.
-
-
class
SourceLocation
¶ - #include <DebugContext.hpp>
This class mimics
std::source_location
that is unavailable as we don’t yet support C++20.Public Functions
-
SourceLocation
() = default¶
-
constexpr
SourceLocation
(const char *functionName, const char *fileName, unsigned lineNumber)¶
-
constexpr const char *
getFunctionName
() const¶
-
constexpr const char *
getFileName
() const¶
-
constexpr unsigned
getLineNumber
() const¶
-
constexpr bool
isValid
() const¶
Public Static Functions
-
SourceLocation
Current
()¶
-
-
namespace
core
-
std::ostream &
3.8.2. poplar/ProfileValue.hpp¶
-
namespace
poplar
Poplar classes and functions.
Functions
-
void
serializeToJSON
(std::ostream &out, const ProfileValue &val, bool prettyPrint = false)¶
-
void
serializeToCBOR
(std::ostream &out, const ProfileValue &val, bool withTag = true)¶
-
std::ostream &
operator<<
(std::ostream &os, const ProfileValue &v)¶ Dumps the JSON representation to an output stream.
-
void
printGraphSummary
(std::ostream &out, const ProfileValue &graphProfile, const OptionFlags &opts)¶ Print a summary of the static graph profiling information - primarily memory use.
The available options are:
showOptimizations
(true, false) [=false]If true, information about the optimisations performed are included in the summary output.
showPerIpuMemoryUsage
(true, false) [=false]If true, total memory usage per-IPU is included in the summary output in addition to memory usage for the whole device.
showVarStorage
(true, false) [=false]If true, information about variable storage liveness is included in the summary output. This is provided for some tiles with the highest maximum live bytes as well as a total for all tiles. The maximum live bytes is output along with information about always-live variables.
colours
(true, false)Specify whether colours should be displayed in the profile report. If not set, colours will be displayed only if outputting to a supported terminal. If not set, using environment variable
CLICOLOR_FORCE=1
forces colours to be displayed, whileCLICOLOR=0
disables colours.
-
void
printExecutionSummary
(std::ostream &out, const ProfileValue &graphProfile, const ProfileValue &executionProfile, const OptionFlags &opts)¶ Print a summary of the execution profiling information - primarily cycle counts.
The information printed depends on the target and the execution profiling mode. IPUModel always prints a simulation of execution.
The available options are:
showExecutionSteps
(true, false) [=false]If true, the program execution sequence with cycle estimates is included in the summary output.
colours
(true, false)See printGraphSummary().
-
void
printProfileSummary
(std::ostream &out, const ProfileValue &graphProfile, const ProfileValue &executionProfile, const OptionFlags &opts = {})¶
-
class
ProfileValue
¶ - #include <ProfileValue.hpp>
ProfileValue represents a read-only JSON-like tree of values that are used to store the output of the profiler.
Each value can be one of:
A boolean
A string
A double-precision number
A vector<> of child values
A map<string, …> of child values. Only string keys are supported.
If an invalid access is made, for example an out-of-range access or accessing the wrong type, then an exception is thrown. It is possible to write code that should never throw an exception by using type().
See the Poplar and PopLibs User Guide for details of the data in the report.
Public Types
-
enum
Type
¶ Values:
-
enumerator
BOOL_
¶
-
enumerator
STRING
¶
-
enumerator
NUMBER
¶
-
enumerator
VECTOR
¶
-
enumerator
MAP
¶
-
enumerator
-
using
Boolean
= bool¶
-
using
Number
= double¶
-
using
Vector
= std::vector<ProfileValue>¶
-
using
Map
= std::map<std::string, ProfileValue>¶
Public Functions
-
double
asDouble
() const¶
-
const ProfileValue &
operator[]
(StringRef s) const¶
-
const ProfileValue *
getOrNull
(StringRef s) const¶
-
const ProfileValue &
operator[]
(std::size_t i) const¶
-
double
sumDouble
() const¶
-
bool
operator==
(const ProfileValue &other) const¶
-
bool
operator!=
(const ProfileValue &other) const¶
-
ProfileValue
()¶
-
template<class
T
, typename = typename std::enable_if<std::is_integral<T>::value>::type>ProfileValue
(T init)¶
-
ProfileValue
(const char *init)¶
-
~ProfileValue
()¶
-
ProfileValue
(const ProfileValue &other)¶
-
ProfileValue
(ProfileValue &&other) noexcept¶
-
ProfileValue &
operator=
(const ProfileValue &other)¶
-
ProfileValue &
operator=
(ProfileValue &&other) noexcept¶
-
ProfileValue &
operator=
(Boolean init)¶
-
ProfileValue &
operator=
(Number init)¶
-
ProfileValue &
operator=
(String init)¶
-
ProfileValue &
operator=
(Vector init)¶
-
ProfileValue &
operator=
(Map init)¶
Friends
- friend class core::MutableProfileValue
-
struct
Storage
¶
-
namespace
core
-
void
3.8.3. poplar/IPUModel.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
struct
IPUModel
¶ - #include <IPUModel.hpp>
A model of an IPU to create an IPUModel Device The IPU Model will simulate the behaviour of the IPU hardware.
It will not completely implement every aspect of a real IPU.
Public Types
Public Functions
-
IPUModel
(char const *IPUVersion = "ipu2")¶
-
Device
createDevice
(OptionFlags opts = {}, bool accurateHalf = false, unsigned deviceManagerId = std::numeric_limits<unsigned>::max())¶ Create a device that runs code on the CPU and models the performance that would be achieved on an IPU.
Public Members
-
unsigned
numIPUs
¶ The number of IPUs.
-
unsigned
tilesPerSuperTile
¶ The number of tiles per supertile.
-
unsigned
tilesPerIPU
¶ The number of tiles per IPU.
-
unsigned
numWorkerContexts
¶ The number of worker contexts per tile.
-
unsigned
memoryBytesPerTile
¶ Memory bytes per tile.
-
double
tileClockFrequency
¶ Clock frequency in Hz.
-
unsigned
exchangeBytesPerCycle
¶ The bandwidth of internal IPU exchange in bytes per cycle.
-
unsigned
memcpyBytesPerCycle
¶ The number of bytes per cycle that can be copied from one location to another using a memcpy.
-
unsigned
instructionBytes
¶ The size of an instruction in bytes.
-
bool
supportsSuperTileSendReceive
¶ Whether a tile in a supertile can use all the exchange bandwidth of the supertile to send or receive, when the other tile is idle or receiving the same data.
-
unsigned
interleavedMemoryElementIndex
¶ Index in the memoryElementOffsets table (returned by Target::getMemoryElementOffsets) which gives the start of the interleaved memory region.
Any value greater than or equal to size of the offsets table is interpreted as machine not having interleaved memory elements. Note that by definition, interleaved memory is always in the upper part of memory
-
enum poplar::IPUModel::RelativeSyncDelayType
relativeSyncDelay
¶
-
unsigned
minIPUSyncDelay
¶ The IPU sync delay for the tile that is closest to the sync controller.
-
unsigned
globalSyncCycles
¶ The number of clock cycles required to synchronize all IPUs.
-
std::vector<GlobalExchangeConstraint>
globalExchangeConstraints
¶ Set of constraints that provide a lower bound on the time it takes to send data between IPUs.
-
unsigned
globalExchangePacketBytes
¶ Size of the packet used to transfer data between tiles in bytes.
-
unsigned
tileLocalSyncSyncDelay
¶ Number of cycles from issuing a sync instruction to the earliest time that instructions can resume.
-
unsigned
tileLocalSyncExitDelay
¶ Number of cycles after a worker has issued its exit instruction that the supervisor can resume.
-
unsigned
numStrideBits
¶ Number of stride bits.
-
unsigned
dataPathWidth
¶ The width of the load/store data path within the tile.
-
unsigned
fp16ConvUnitMaxPipelineDepth
¶ The maximum pipeline depth of the convolution units within the tile for fp16.
-
unsigned
fp32ConvUnitMaxPipelineDepth
¶ The maximum pipeline depth of the convolution units within the tile for fp32.
Only allow a maximum of 4 cycle AMP loop.
-
unsigned
fp16ConvUnitInputLoadElemsPerCycle
¶ The input elements loaded per cycle for f16 conv.
-
unsigned
fp32ConvUnitInputLoadElemsPerCycle
¶ The input elements loaded per cycle for f32 conv.
-
unsigned
fp16InFp16OutConvUnitsPerTile
¶ The number of convolution units in the tile that can be used when partial results are outputs as 16-bits and inputs are 16 bits.
-
unsigned
fp16InFp32OutConvUnitsPerTile
¶ The number of convolution units in the tile that can be used when partial results are outputs as 32-bits and inputs are 16 bits.
-
unsigned
fp32InFp32OutConvUnitsPerTile
¶ The number of convolution units in the tile that can be used when accumulating to 32 bit values.
-
unsigned
convUnitCoeffLoadBytesPerCycle
¶ The number of convolutional weights that can be loaded in a cycle.
-
unsigned
supervisorInstrFetchDelay
¶ Number of bytes supervisor contexts may be loading instructions from memory ahead of current PC.
-
unsigned
workerInstrFetchDelay
¶ Number of bytes worker context may be loading instructions from memory ahead of current PC.
-
unsigned
maxImmediateOffsetInRunInstr
¶ max range of immediate operand in run instruction zimm16 operand multiplied implicitly by 4 when added to register operand
-
unsigned
rptCountMax
¶
-
unsigned
atomicStoreGranularity
¶ The atomic store granularity.
-
bool
compileIPUCode
¶ Whether or not to actually compile real IPU code for modelling.
-
-
struct
3.8.4. poplar/GlobalExchangeConstraints.hpp¶
-
namespace
poplar
Poplar classes and functions.
-
struct
GlobalExchangeConstraint
¶ Public Functions
-
GlobalExchangeConstraint
(double bandwidth, ArrayRef<GlobalExchangeFlow> flows)¶
-
bool
operator==
(const GlobalExchangeConstraint &other) const¶
-
bool
operator<
(const GlobalExchangeConstraint &other) const¶
Public Members
-
double
bandwidth
¶ Bandwidth in bits per second.
-
std::vector<GlobalExchangeFlow>
flows
¶ The flows that the constraint applies to.
-
-
struct
GlobalExchangeFlow
¶ Public Functions
-
GlobalExchangeFlow
(unsigned src, unsigned dst)¶
-
bool
operator==
(const GlobalExchangeFlow &other) const¶
-
bool
operator<
(const GlobalExchangeFlow &other) const¶
-
-
struct
3.8.5. poplar/CycleCount.hpp¶
-
namespace
poplar
Poplar classes and functions.
Functions
-
poplar::Tensor
cycleCount
(poplar::Graph &graph, poplar::program::Sequence &prog, unsigned tile, const DebugContext &debugContext = {})¶ Given a sequence program type, times the program and returns the 64 bit value in a tensor of two unsigned integers.
The first element of the tensor is the lower 32-bits and the second the upper 32-bits. Sequence is timed by adding sync and timing programs around the original sequence. You must also specify the tile on which the program is timed.
- Deprecated:
Use cycleCount with the syncType arg instead
- Return
A unsigned integer tensor of length 2
- Parameters
graph
: The Poplar graphprog
: The program sequence to timetile
: The tile on which the program is timeddebugContext
: Optional debug context
-
poplar::Tensor
cycleCount
(poplar::Graph &graph, poplar::program::Sequence &prog, unsigned tile, SyncType syncType, const DebugContext &debugContext = {})¶ Given a sequence program type, times the program and returns the 64 bit value in a tensor of two unsigned integers.
The first element of the tensor is the lower 32-bits and the second the upper 32-bits. Sequence is timed by adding sync and timing programs around the original sequence. You must also specify the tile on which the program is timed.
- Return
A unsigned integer tensor of length 2
- Parameters
graph
: The Poplar graphprog
: The program sequence to timetile
: The tile on which the program is timedsyncType
: Type of sync to wrap the original sequence indebugContext
: Optional debug context
-
poplar::Tensor
cycleStamp
(poplar::Graph &graph, poplar::program::Sequence &prog, unsigned tile, const DebugContext &debugContext = {})¶ Add a sequence program to record an absolute hardware cycle stamp on a given tile.
The stamp is a snapshot of a continuously running hardware counter on a tile and to have consistent results, measurements must be done on the same tile.
The result is a tensor containing two 32-bit elements of a 64-bit snapshot of the hardware counter. The first element of the tensor is the lower 32-bits and the second the upper 32-bits.
The timestamp is added after an internal sync is executed.
- Deprecated:
Use cycleStamp with the syncType arg instead
- Return
An unsigned integer tensor of length 2
- Parameters
graph
: The Poplar graphprog
: The program sequence to which the time stamp is addedtile
: The tile on which the time stamp is addeddebugContext
: Optional debug context
-
poplar::Tensor
cycleStamp
(poplar::Graph &graph, poplar::program::Sequence &prog, unsigned tile, SyncType syncType, const DebugContext &debugContext = {})¶ Add a sequence program to record an absolute hardware cycle stamp on a given tile.
The stamp is a snapshot of a continuously running hardware counter on a tile and to have consistent results, measurements must be done on the same tile.
The result is a tensor containing two 32-bit elements of a 64-bit snapshot of the hardware counter. The first element of the tensor is the lower 32-bits and the second the upper 32-bits.
The timestamp is added after a sync is executed.
- Return
An unsigned integer tensor of length 2
- Parameters
graph
: The Poplar graphprog
: The program sequence to which the time stamp is addedtile
: The tile on which the time stamp is addedsyncType
: Type of sync to perform before stampingdebugContext
: Optional debug context
-
std::vector<poplar::Tensor>
cycleStamp
(poplar::Graph &graph, poplar::program::Sequence &prog, const std::vector<unsigned> &tiles, const DebugContext &debugContext = {})¶ Add a compute set to record an absolute hardware cycle stamp on the specified tiles.
- Deprecated:
Use cycleStamp with the syncType arg instead
- Return
A vector of tensors of 2 integers
- Parameters
graph
: The Poplar graphprog
: The program sequence to which the time stamp is addedtiles
: The tiles on which the time stamp is addeddebugContext
: Optional debug context
-
std::vector<poplar::Tensor>
cycleStamp
(poplar::Graph &graph, poplar::program::Sequence &prog, const std::vector<unsigned> &tiles, SyncType syncType, const DebugContext &debugContext = {})¶ Add a compute set to record an absolute hardware cycle stamp on the specified tiles.
- Return
A vector of tensors of 2 integers
- Parameters
graph
: The Poplar graphprog
: The program sequence to which the time stamp is addedtiles
: The tiles on which the time stamp is addedsyncType
: Type of sync to perform before stampingdebugContext
: Optional debug context
-
poplar::Tensor