package pblczero

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Used in: NodeProto

• optional string name = 1

• optional string doc_string = 13

• optional float f = 2

  Exactly ONE of the following fields must be present

  float

• optional int64 i = 3

  int

• optional bytes s = 4

  UTF-8 string

• optional TensorProto t = 5

  tensor value

• repeated float floats = 7

  list of floats

• repeated int64 ints = 8

  list of ints

• repeated bytes strings = 9

  list of UTF-8 strings

• repeated TensorProto tensors = 10

  list of tensors

• optional AttributeProto.AttributeType type = 20

Used in: AttributeProto

• UNDEFINED = 0

• FLOAT = 1

• INT = 2

• STRING = 3

• TENSOR = 4

  GRAPH = 5;

• FLOATS = 6

• INTS = 7

• STRINGS = 8

• TENSORS = 9

  GRAPHS = 10;

Used in: CompileOptionsProto

• required string key = 1

• required OptionOverrideProto value = 2

• repeated XlaShapeProto argument_layouts = 1

• optional bool parameter_is_tupled_arguments = 2

• optional ExecutableBuildOptionsProto executable_build_options = 3

• optional bool compile_portable_executable = 4

• optional int64 profile_version = 5

• optional bytes serialized_multi_slice_config = 6

• repeated CompileEnvOptionProto env_options = 7

Used in: CompileOptionsProto

• optional int64 device_ordinal = 1

  If set, this is the device to build the computation for. Valid device_ordinal values are: 0 to # of devices - 1. These values are identical to the device ordinal values used by StreamExecutor. The built executable will be executable on any device equivalent to the specified device as determined by Backend::devices_equivalent(). A value of -1 indicates this option has not been set.

• optional XlaShapeProto result_layout = 2

  If set, this specifies the layout of the result of the computation. If not set, the service will chose the layout of the result. A Shape is used to store the layout to accommodate tuple result shapes. A value of nullptr indicates the option has not been set.

• optional int64 num_replicas = 4

  The number of replicas of this computation that are to be executed. Defaults to 1.

• optional int64 num_partitions = 5

  The number of partitions in this computation. Defaults to 1.

• optional bool use_spmd_partitioning = 6

  Indicates whether to use SPMD (true) or MPMD (false) partitioning when num_partitions > 1 and XLA is requested to partition the input program.

• optional bool use_auto_spmd_partitioning = 7

  Whether to automatically generate XLA shardings for SPMD partitioner.

• optional bool deduplicate_hlo = 8

  Whether HLOs should be deduplicated.

• optional XlaDeviceAssignmentProto device_assignment = 9

  If set, this specifies a static device assignment for the computation. Otherwise, the computation will be compiled generically and can be run with any device assignment compatible with the computation's replica and partition counts.

• optional bool alias_passthrough_params = 10

  Whether input and output buffers are aliased if the associated parameter is passed-through XLA modules without being changed.

• optional bool run_backend_only = 11

  By default, XLA builds an executable by invoking standard compilation, i.e. running Compiler::Compile, or both Compiler::RunHloPasses and Compiler::RunBackend. When run_backend_only is set to true, XLA builds an executable by invoking only RunBackend and skip invoking RunHloPasses, which can be used to compile post-optimizations HLO modules.

• repeated bool allow_spmd_sharding_propagation_to_output = 12

  Allows sharding propagation to propagate to the outputs. This changes the output shape of the computation (which is undesirable), but it can be used to allow to run partial compilation to determine what would be the output sharding of a computation if XLA would be allowed to propagate the sharding which can be used by higher level framework as a way to query intermediate sharding of operations when multiple computation would be chained and merged together. This is a vector of bool, because the user can control (if the output of the computation is a tuple) which elements of the tuple can have the sharding substituted and which don't. If only one boolean value is passed in the vector that's interpreted as the value to be applied for every single element of the output tuple. One value per element of the tuple means that each value is attached to one of the output elements.

• optional bytes fdo_profile = 14

  Opaque profile data for any feedback directed optimizations.

• optional int64 device_memory_size = 15

• repeated int64 auto_spmd_partitioning_mesh_shape = 16

  Mesh shape in auto sharding options.

• repeated int64 auto_spmd_partitioning_mesh_ids = 17

  Mesh ids in auto sharding options.

Used in: ModelProto

• repeated NodeProto node = 1

• optional string name = 2

• repeated TensorProto initializer = 5

• optional string doc_string = 10

• repeated ValueInfoProto input = 11

• repeated ValueInfoProto output = 12

Used in: HloModuleProto

• required string name = 1

• repeated HloInstructionProto instructions = 2

  The array of instructions is always in a valid dependency order, where operands appear before their users.

• required XlaProgramShapeProto program_shape = 4

• required int64 id = 5

  The id of this computation.

• required int64 root_id = 6

  The id of the root of the computation.

Used in: HloComputationProto

• required string name = 1

• required string opcode = 2

• required XlaShapeProto shape = 3

• optional XlaOpMetadata metadata = 7

• optional XlaLiteralProto literal = 8

  Literal, only present for kConstant.

• optional int64 parameter_number = 9

  Parameter number is only present for kParameter.

• optional int64 tuple_index = 13

  Index for kGetTupleElement.

• optional XlaWindow window = 15

  Describes the window in a windowed operation such as convolution.

• optional XlaConvolutionDimensionNumbers convolution_dimension_numbers = 16

  Describes the dimension numbers used for a convolution.

• repeated HloInstructionProto.SliceDimensions slice_dimensions = 17

• optional XlaDotDimensionNumbers dot_dimension_numbers = 30

• repeated int64 dimensions = 14

  Dimensions present for some operations that require reshaping or broadcasting, including Reshape, Reduce, ReduceWindow, and Reverse.

• optional XlaGatherDimensionNumbers gather_dimension_numbers = 33

  Gather dimension numbers.

• repeated int64 gather_slice_sizes = 34

• optional bool indices_are_sorted = 67

• optional bool unique_indices = 69

• required int64 id = 35

  The id of this instruction.

• repeated int64 operand_ids = 36

• repeated int64 called_computation_ids = 38

• optional string comparison_direction = 63

Describes the [begin, end) index range and stride for slices.

Used in: HloInstructionProto

• optional int64 start = 1

• optional int64 limit = 2

• optional int64 stride = 3

• required string name = 1

• required string entry_computation_name = 2

• required int64 entry_computation_id = 6

• repeated HloComputationProto computations = 3

  The array of computations is always in a valid dependency order, where callees appear before their callers.

• required XlaProgramShapeProto host_program_shape = 4

  The host program shape (with layout) of the entry computation.

• required int64 id = 5

  The id of this module.

The subset of Onnx protos that are used in lczero.

• optional int64 ir_version = 1

• optional string producer_name = 2

• optional string producer_version = 3

• optional string domain = 4

  'org.lczero.models.*'

• optional int64 model_version = 5

• optional string doc_string = 6

• optional GraphProto graph = 7

• repeated OperatorSetIdProto opset_import = 8

Used in: GraphProto

• repeated string input = 1

• repeated string output = 2

• optional string name = 3

• optional string op_type = 4

• repeated AttributeProto attribute = 5

• optional string doc_string = 6

• optional string domain = 7

Used in: ModelProto

• optional string domain = 1

• optional int64 version = 2

Used in: CompileEnvOptionProto

• optional string string_field = 1

• optional bool bool_field = 2

• optional int64 int_field = 3

• optional double double_field = 4

Used in: TensorProto

• optional string key = 1

• optional string value = 2

Used in: AttributeProto, GraphProto

• repeated int64 dims = 1

• optional TensorProto.DataType data_type = 2

• optional string name = 8

• optional bytes raw_data = 9

• optional string doc_string = 12

• repeated StringStringEntryProto external_data = 13

• optional TensorProto.DataLocation data_location = 14

Used in: TensorProto

• DEFAULT = 0

• EXTERNAL = 1

Used in: TensorProto, TypeProto.Tensor

• UNDEFINED = 0

• FLOAT = 1

  Basic types.

  float

• UINT8 = 2

  uint8_t

• INT8 = 3

  int8_t

• UINT16 = 4

  uint16_t

• INT16 = 5

  int16_t

• INT32 = 6

  int32_t

• INT64 = 7

  int64_t

• STRING = 8

  string

• BOOL = 9

  bool

• FLOAT16 = 10

• DOUBLE = 11

• UINT32 = 12

• UINT64 = 13

• COMPLEX64 = 14

• COMPLEX128 = 15

• BFLOAT16 = 16

• FLOAT8E4M3FN = 17

• FLOAT8E4M3FNUZ = 18

• FLOAT8E5M2 = 19

• FLOAT8E5M2FNUZ = 20

Used in: TypeProto.Tensor

• repeated TensorShapeProto.Dimension dim = 1

Used in: TensorShapeProto

• optional int64 dim_value = 1

• optional string dim_param = 2

Used in: ValueInfoProto

• optional TypeProto.Tensor tensor_type = 1

Used in: TypeProto

• optional TensorProto.DataType elem_type = 1

• optional TensorShapeProto shape = 2

Used in: GraphProto

• optional string name = 1

• optional TypeProto type = 2

• optional string doc_string = 3

Used in: HloInstructionProto

• optional int64 input_batch_dimension = 7

• optional int64 input_feature_dimension = 8

• repeated int64 input_spatial_dimensions = 11

• optional int64 kernel_input_feature_dimension = 3

• optional int64 kernel_output_feature_dimension = 4

• repeated int64 kernel_spatial_dimensions = 6

• optional int64 output_batch_dimension = 9

• optional int64 output_feature_dimension = 10

• repeated int64 output_spatial_dimensions = 12

Used in: ExecutableBuildOptionsProto

• optional int32 replica_count = 1

• optional int32 computation_count = 2

• repeated XlaDeviceAssignmentProto.ComputationDevice computation_devices = 3

Used in: XlaDeviceAssignmentProto

• repeated int64 replica_device_ids = 1

Used in: HloInstructionProto

• repeated int64 lhs_contracting_dimensions = 1

• repeated int64 rhs_contracting_dimensions = 2

• repeated int64 lhs_batch_dimensions = 3

• repeated int64 rhs_batch_dimensions = 4

Used in: HloInstructionProto

• repeated int64 offset_dims = 1

• repeated int64 collapsed_slice_dims = 2

• repeated int64 start_index_map = 3

• optional int64 index_vector_dim = 4

Used in: XlaShapeProto

• repeated int64 minor_to_major = 1

  Sequence of dimension numbers, from minor (fastest varying index) to major (slowest varying index). This field is required.

Used in: HloInstructionProto

• required XlaShapeProto shape = 1

• repeated bool preds = 2

• optional bytes s4s = 21

• optional bytes u4s = 22

• optional bytes s8s = 15

• optional bytes u8s = 3

• repeated int32 s32s = 4

• repeated int64 s64s = 5

• repeated uint32 u32s = 6

• repeated uint64 u64s = 7

• repeated float f32s = 8

• repeated double f64s = 9

• repeated float c64s = 12

  Stored as interleaved real, imag floats.

• repeated double c128s = 18

  Stored as interleaved real, imag doubles.

• repeated XlaLiteralProto tuple_literals = 10

• optional bytes f16s = 11

  The F16s, BF16s, U16s and S16s are encoded in little endian byte order

• optional bytes bf16s = 13

• optional bytes u16s = 16

• optional bytes s16s = 17

• optional bytes f8e5m2s = 19

• optional bytes f8e4m3fns = 20

• optional bytes f8e4m3b11fnuzs = 23

• optional bytes f8e5m2fnuzs = 24

• optional bytes f8e4m3fnuzs = 25

• repeated int64 sparse_indices = 14

  Next = 26

Symbolization metadata for HLO Instructions. This metadata is used for debugging XLA code generation, as well as performance profiling of XLA-generated executables.

Used in: HloInstructionProto

• optional string op_type = 1

  The framework op name that generated this XLA op. Frameworks that build on top of XLA should mirror the names of their ops back to users by specifying the op_type. In this way, even if the framework's "ops" are implemented as multiple XLA HLO Ops, they can be grouped appropriately. (e.g. if a SoftMax layer is emitted into XLA as multiple ops, then each op should have the op_type be "SoftMax".)

• optional string op_name = 2

  The user-specified name of the op. This name is often unique within a computation. Note: some frameworks add auto-generated names if the user does not provide one.

• optional string source_file = 3

  Indicate a file and line that this op is associated to in a user's program. e.g. it could be the file and line of user code that generated the op.

• optional int32 source_line = 4

Shape of the parameters and output of a computation (like a traditional function signature).

Used in: HloComputationProto, HloModuleProto

• repeated XlaShapeProto parameters = 1

• required XlaShapeProto result = 2

• repeated string parameter_names = 3

Used in: CompileOptionsProto, ExecutableBuildOptionsProto, HloInstructionProto, XlaLiteralProto, XlaProgramShapeProto

• required XlaShapeProto.Type element_type = 2

  The element type for this shape.

• repeated int64 dimensions = 3

  The size (number of elements) for each dimension, or an upper bound on the size if the dimension is dynamic. In XLA, dimensions are numbered from 0 to N-1 for an N-dimensional array. The first element of 'dimensions' is the size of dimension 0, the second element is the size of dimension 1, and so forth. Empty list indicates a scalar. If the respective element in 'is_dimension_dynamic' is true then the value in this field represents an upper bound on the size of the dimension.

• repeated XlaShapeProto tuple_shapes = 4

  For tuples only, the shapes of constituent shapes in the tuple sequence.

• required XlaLayoutProto layout = 5

  The layout used to back this shape.

• repeated bool is_dynamic_dimension = 6

  For arrays, this indicates whether or not each dimension is dynamically-sized. The number of elements in this repeated field should be zero (indicating that no dimensions are dynamic) or equal to the number of elements in the 'dimensions' field.

Used in: XlaShapeProto

• PRIMITIVE_TYPE_INVALID = 0

• PRED = 1

  Predicates are two-state booleans.

• S4 = 21

  Signed integral values of fixed width.

• S8 = 2

• S16 = 3

• S32 = 4

• S64 = 5

• U4 = 22

  Unsigned integral values of fixed width.

• U8 = 6

• U16 = 7

• U32 = 8

• U64 = 9

• F16 = 10

  Floating-point values of fixed width. Note: if f16s are not natively supported on the device, they will be converted to f16 from f32 at arbirary points in the computation.

• F32 = 11

• BF16 = 16

  Truncated 16 bit floating-point format. This is similar to IEEE's 16 bit floating-point format, but uses 1 bit for the sign, 8 bits for the exponent and 7 bits for the mantissa.

• F64 = 12

• F8E5M2 = 19

• F8E4M3FN = 20

• F8E4M3B11FNUZ = 23

• F8E5M2FNUZ = 24

  FP8 dtypes, as described in this paper: https://arxiv.org/abs/2206.02915 F8E5M2FNUZ has 5 exponent bits and 2 mantissa bits. F8E4M3FNUZ has 4 exponent bits and 3 mantissa bits. The "FNUZ" means only Finite and NaN values are supported; zero is unsigned. Unlike IEEE types, infinities are not supported. NaN is represented when the exponent and mantissa bits are all 0s with a sign bit of 1. All other values are finite. These differences mean there's an additional exponent value available. To keep the same dynamic range as an IEEE-like FP8 type, the exponent is biased one more than would be expected given the number of exponent bits (8 for Float8E4M3FNUZ and 16 for Float8E5M2FNUZ).

• F8E4M3FNUZ = 25

• C64 = 15

  Complex values of fixed width.

  Paired F32 (real, imag), as in std::complex<float>.

• C128 = 18

  Paired F64 (real, imag), as in std::complex<double>.

• TUPLE = 13

  A tuple is a polymorphic sequence; e.g. a shape that holds different sub-shapes. They are used for things like returning multiple values from a computation; e.g. a computation that returns weights and biases may have a signature that results in a tuple like (f32[784x2000], f32[2000]) If a shape proto has the tuple element type, it may not have any entries in the dimensions field.

• OPAQUE_TYPE = 14

  An opaque type used for passing context-specific data to a custom operation. Shapes of this primitive type will have empty dimensions and tuple_shapes fields. (OPAQUE would be a better name for this identifier, but that conflicts with a macro defined in windows.h.)

• TOKEN = 17

  A token type threaded between side-effecting operations. Shapes of this primitive type will have empty dimensions and tuple_shapes fields.

Used in: HloInstructionProto

• repeated XlaWindowDimension dimensions = 1

Used in: XlaWindow

• optional int64 size = 1

• optional int64 stride = 2

• optional int64 padding_low = 3

• optional int64 padding_high = 4

• optional int64 window_dilation = 5

• optional int64 base_dilation = 6

• optional bool window_reversal = 7