package tezos-benchmark

You can search for identifiers within the package.

in-package search v0.2.0

tezos-benchmark
- Tezos_benchmark
  - Ast
    
    Ast
    
    At_least_10
    
    X
    
    Make
    
    Size
    
    Optimize
    
    X
    
    S
    
    To_ast
    
    Ast
    
    Transform
    
    F
    
    Ast
    
    X
  - Base_samplers
    
    Adversarial
  - Benchmark
    
    Benchmark_base
    
    S
    
    Simple
    
    Simple_with_num
  - Benchmark_helpers
  - Builtin_benchmarks
    
    Timer_latency_bench
  - Builtin_models
  - Codegen
    
    Parser
  - Config
  - Costlang
    
    Arg_names
    
    Beta_normalize
    
    X
    
    Eval
    
    Eval_linear_combination_impl
    
    Eval_to_vector
    
    Fold_constants
    
    X
    
    Free_variables
    
    Hash_cons
    
    X
    
    Hash_cons_vector
    
    Identity
    
    X
    
    Let_lift
    
    X
    
    Num
    
    Pp
    
    S
    
    Subst
    
    P
    
    X
    
    Transform
    
    X
    
    Ty
    
    Type
    
    Void
  - Crypto_samplers
    
    Finite_key_pool_S
    
    Make_finite_key_pool
    
    Arg
    
    P_Finite_key_pool_S
    
    Param_S
    
    V0
    
    Finite_key_pool_S
    
    Make_finite_key_pool
    
    Arg
    
    V1
    
    Finite_key_pool_S
    
    Make_finite_key_pool
    
    Arg
    
    V_latest
    
    Finite_key_pool_S
    
    Make_finite_key_pool
    
    Arg
  - Csv
  - Dep_graph
    
    Graph
    
    Graphviz
    
    Solver
    
    Solved
    
    Unsolved
  - Fixed_point_transform
    
    Apply
    
    P
    
    X
  - Free_variable
    
    Map
    
    Set
    
    Sparse_vec
    
    Op
    
    Table
  - Generator
    
    S
  - Inference
    
    NMap
  - Maths
  - Measure
    
    Time
  - Model
    
    Applied
    
    X
    
    Binary_operation
    
    Def
    
    X
    
    Instantiate
    
    M
    
    Def
    
    X
    
    X
    
    Instantiated
    
    Model_impl
    
    Def
    
    X
  - Namespace
    
    Hashtbl
    
    Map
    
    Set
  - Ocamlformat
  - Override
  - Plot
    
    Bar
    
    Color
    
    Data
    
    Fill
    
    Histogram
    
    Line
    
    Pointtype
    
    Scatter
    
    Style
    
    Tics
  - Pyinference
    
    LinearModel
  - Pyinit
  - Pytools
  - Registration
  - Scikit_matrix
  - Sparse_vec
    
    Make
    
    M
    
    Op
    
    S
    
    Op
    
    String
    
    Op
  - Structure_samplers

Legend:
Library
Module
Module type
Parameter
Class
Class type

val pyinit : unit -> unit

Initializes Python

val numpy : unit -> Pytypes.pyobject

Import numpy and returns its Python object. It also initialize Python runtime if not yet.

val linear_model : unit -> Pytypes.pyobject

Import sklearn.linear_model and returns its Python object. It also initialize Python runtime if not yet.

val scipy_optimize : unit -> Pytypes.pyobject

Import scipy.optimize and returns its Python object. It also initialize Python runtime if not yet.

val sklearn_metrics : unit -> Pytypes.pyobject

Import sklearn.metrics and returns its Python object. It also initialize Python runtime if not yet.

val statsmodels_api : unit -> Pytypes.pyobject

Import statsmodels.api and returns its Python object. It also initialize Python runtime if not yet.

val statsmodels_stats : unit -> Pytypes.pyobject

Import statsmodels.stats and returns its Python object. It also initialize Python runtime if not yet.