Skip to content

v0.15.2.0
Compare
Choose a tag to compare
@kmantel kmantel released this 10 Dec 05:38
· 45 commits to master since this release
v0.15.2.0
cc0a663
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Learn about vigilant mode.

[0.15.2.0] - 2024-11-11

Bug Fixes

  • Fix/ego_update_figs (#3108)

  • EGO CSW Model: update figures

CombineMeans

  • Avoid creating unecessary object dtype for means

Component

  • Only explicitly set new parameter defaults
  • Check for existing parameter by name before getattr
  • _initialize_parameters: allow creating Parameters dynamically
  • _get_current_parameter_value: pass modulated=True to _get
  • Always shallow copy owner
  • Handle hybrid copy in deepcopy
  • deepcopy remove no_shared in memo
  • deepcopy add copy to memo
  • Copy default variable if not passed to execute
  • _validate_variable: copy default variable if used
  • Copy matrix default value if used
  • Store set of containing Compositions
  • Rework size argument to accept and validate numpy shapes

Composition

  • Inherit Parameters from parent class
  • Fix bug storing results
  • Do not delete value Parameter
  • Remove compiled writeback of matrix during learning

CompositionInterfaceMechanism

  • Use standard default_variable assignment

DDM

  • Codestyle

DictionaryMemory

  • Consolidate default entry creation

Documentation

  • Fix table formatting
  • Extend short title underlines
  • Fix "strong" markup
  • Fix literal markup
  • Fix Inline emphasis markup
  • Fix external links
  • Fix inline interpreted markup
  • Fix table vs. substitution conflict
  • Fix basic rst formatting errors (#2958)
  • Rename figure to match docstring reference (#3009)
  • Add quotation to pip install (#3051)
  • Use pattern rule to execute generator scripts (#3087)

DriftDiffusionAnalytical

  • Specify dependence of bias on starting_value, threshold

DriftOnASphereIntegrator

  • Fix initializer assignment
  • Correct default initializer

EMComposition

  • Reduce calls to memory_getter in init

EMStorageMechanism

  • Add 'fields' as Parameter
  • Do not set value in _execute
  • Fix dot-notation access
  • Explicitly update field_projection matrices

EMstorageMechanism

  • Replace internal use of Parameter.get with _get

Function

  • Copy variable on external .function call
  • Do not process the value, or reset PRNG when syncing seed

Function_Base

  • Don't catch and re-raise ValueError

IntegratorMechanism

  • Correct broken size argument (#3046)

MDF

  • Condition: handle np.number and np.array types as arguments
  • Handle parameters/args in list and dict format

MaskedMappingProjection

  • Also set matrix parameter port value

Mechanism

  • Use np ones instead of list multiplication
  • Copy defaults before executing with them
  • Drop beartype decorator on internal function

OptimizationControlMechanism

  • Correct non-stateful use of num_estimates

OptimizationFunction

  • Make grid stateful

PECOptimizationFunction

  • Make initial_seed shared and use context

Parameter

  • Fix arg comment
  • _set_default_value: add 'directly' to bypass parse/validate
  • Bypass any setters when making uninherited
  • deepcopy: always deepcopy non-inherited default_value
  • Store source and final_source as self
  • Faster contains
  • getattr: call _parent fewer times
  • Replace equivalent code with copy_parameter_value
  • _set, _set_value: reformat arg list
  • _set: make skip_delivery kwarg explicit
  • On set, update compatible numpy arrays in place

ParameterEstimationComposition

  • Make seed parameters shared
  • Empty results on new run, not clear

ParameterPortList

  • Reduce excess slow str formats

Parameters

  • Clean up getter dev docs
  • Check for alias using name

ParametersBase

  • Cache names of attrs that do not exist
  • Break throw_attr into separate method
  • Do not getattr on parent for missing parameter attrs

ParametersTemplate

  • Replace _children with WeakSet
  • Add _params check in _is_parameter

Port

  • Refactor is_modulated -> has_modulation

Projection_Base

  • Copy sender default value if used as default

RecurrentTransferMechanism

  • Make recurrent_projection a Parameter (#2940)

Refactor

  • Refactor/emcomposition_softmax_after_dot (#3095)

    • emcomposition.py
    • move softmax operation to after combining weighted dot products
    • update use_gating_for_weighting and softmax CONTROL option to work with refactoring
    • validate that use_gating_for_weighting is False when learn_field_weights is True
    • docstring updates

  • Update Environment.py

  • test_emcomposition.py

    • update test_execution

  • Refactor/linearmatrix_matrixtransform (#3101)

  • combinationfunctions(.py) -> transformfunctions(.py)

  • transferfunctions.py:

    • rename LinearCombination as MatrixTransform and move to transformfunctions.py

  • transformfunctions:

    • MatrixTransform: add operation parameter

  • recurrenttransfermechanism.py

    • correct names for standard_outputports ENERGY and ENTROPY

  • lccontrolmechanism.py:

    • add keywords for modulable fitzhugh-nagumo params

  • emcomposition.py:

    • use MatrixTransform(operation=L0) w/o normalization for retrieval if len(key)==1

  • 'EGO Model - CSW with Simple Integrator.py':

    • Younes' script corrections, now functions propery!

Report

  • Store report parameters on the instance instead of the class

SampleIterator

  • Make generate_current_value instance-method-like

Scheduler

  • Fix false add_condition replace warning (#3107)

StatefulFunction

  • Correct previous_value shape with ragged variable

Testing

  • Replace some assert == with numpy.testing.assert_array_equal
  • Correct assert shape mismatch
  • TestControlTimeScales: correct silent shape mismatch in results
  • Check shape of results as well as the values
  • Check shape of results as well as the values
  • Use assert_array_equal to check array shape and values (#2922)
  • Fix AVX512 detection on Numpy>=1.26 (#2932)
  • Allow writeback on compiled tests.
  • Remove result shape workaround
  • Add test of dependency after DDM finished
  • Control: split result assertions
  • Auto test all numeric values wrapped in np array
  • Add missing 'composition' marks (#2967)
  • Narrow down the allowed exceptions in compilation fallback test
  • Codestyle
  • Use numpy prod instead of product
  • Use fixture to preserve environment (#2987)
  • Add leak check test (#2992)
  • Remove leftover debug code
  • Test show_graph in the leak test
  • Fix show_graph leak and extend the leak test (#2997)
  • Skip running ExecutionMode.LLVM instead of xfail
  • Clarify failure in xfail test
  • Cleanup some xfail tests (#2998)
  • Adjust expected result based on scipy version
  • Update OCM controller tests
  • Use numpy arrays for fixed size arguments
  • Use numpy arrays for fixed size arguments
  • Use numpy arrays for fixed size arguments
  • Use numpy arrays for fixed size arguments
  • Cleanup
  • Cleanup use of ExecutionMode.Python
  • Cleanup
  • Add llvm_not_implemented mark.
  • Add llvm_not_implemented mark (#3075)
  • Use issubclass to check Function class
  • Convert dict test arguments to an immutable MappingProxyType
  • Use MappingProxyType to pass dict test parameters (#3076)
  • Drop unused ctypes import
  • Use top level module import of ExecutionMode
  • Drop unused import of core.llvm
  • Comment out imports only used in commented out code
  • Drop unused imports
  • Drop unused imports (#3083)
  • Move condition construction args to test parametrization
  • Enable testing in per-node compiled mode

UserDefinedFunction

  • Do not modify cust_fct_params attr on function call
  • Rework creation of custom Parameters
  • Use external Parameter.set for custom parameters

Broken_trans_deps

  • Block beartype==0.17.1 (#2914)

Ci

  • Split windows x86 job (#2943)
  • Test-release: add --verbose to twine upload
  • Test-release: use github cli to create github release
  • Test-release: include python 3.10, 3.11, 3.12

Ci/ga

  • Use native python architecture for macos python 3.8 job
  • Use native python version on macos-arm64 runners (#2953)
  • Simplify documentaitons ci jobs (#2957)
  • Use single variable to check for self-hosted runners availability (#2965)
  • Drop python-3.7 macos documentation build
  • Require custom runners to have "enabled" flag (#2989)

Ci/ga/docs

  • Use default python-architecture for each platform to build docs
  • Represent correct os version in matrix.os
  • Generate version matrix dimension based on GA event

Ci/github-actions

  • Add python 3.12 docs building jobs
  • Add python 3.12 jobs

Composition

  • Create a copy of 'controller_condition'

Condition

  • Add python interface from graph_scheduler
  • Fix pnl-specific names in condition.py stub and all (#3089)

Conditions

  • Add When alias for Condition
  • Explicitly specify pnl Conditions in all

Conftest

  • Clear graph scheduler cache in test teardown
  • Inherit the original class of the benchmark fixture (#3093)

Dependabot

  • Allow up to 25 open pull requests (#2944)

Deps/fastkde

  • Bump minimum version to >=2.0.0

Fitfunctions

  • Try using underscore name to construct fastKDE object

Function

  • Replace FunctionOutputType.RAW_NUMBER with NP_0D_ARRAY

Functions

  • Return numpy array as output for multi-item functions

Ga

  • Move wheel/sdist creation to install-pnl action (#3085)

Llvm

  • Move matrices of learnable projections to compiled state
  • Move learnable matrices from RO params to RW params (#2933)
  • Enable state writeback on all compiled Functions and Mechanisms (#2938)
  • AutoassociativeProjection is a PNL param of the owning Mechanism (#2941)
  • Add cleanup destruction check
  • Consolidate construction and sync of compiled structures (#2973)
  • Rearrange members of the Mersenne-Twister state structure
  • Use int16 instead of int1 for flag in Philox state
  • Use known type instead of int32_ty if available
  • Codestyle
  • Tweaks to structure layout and codestyle (#2994)
  • Create numpy structures of all params/state before syncing to Parameters (#2995)
  • Fix processing of enum values after compilation sync (#2996)
  • Track and clear active CompExecution instances (#2999)
  • Rename node_wrapper -> node_assembly
  • Remove workaround, rename node assembly (#3016)
  • Store only pointee types in byref_arg_types for pointer arguments (#3017)
  • Construct numpy dtypes of compiled argument structures
  • Move numpy buffer allocation to LLVMBinaryFunction
  • Use numpy ndpointer for fixed size arguments of compiled functions (#3027)
  • Remove support for running multiple contexts
  • Remove 'wrap_call'
  • Rename np_params -> np_arg_dtypes
  • Use Numpy ndpointer by default
  • Use Numpy ndpointer as default for pointer/array arguments (#3028)
  • Use zero extend to promote integers
  • Improve test coverage of compilation helpers (#3029)
  • Use numpy array for dynamically sized output arguments (#3033)
  • Use per jit-engine printf pointer
  • Add env variable control over debugging output
  • Control debug output via PNL_LLVM_DEBUG env var (#3092)
  • Bring compiled scheduler implementation closer to the Python one (#3096)
  • Drop PTXExec execution mode
  • Use more aggressive optimizations for GPU target (#3109)

Llvm/Composition

  • Add debugging output to scheduled node executions

Llvm/ConditionGenerator

  • Use IntEnum to index the timestamp structure

Llvm/Functions/GridSearch

  • Remove duplicate/dead code
  • Use Numpy structures for fixed sizes arguments

Llvm/LLVMBinaryFunction

  • Allow setting argument types to numpy ndpointer
  • Enforce contiguous arrays as Numpy inputs
  • Add support for dynamically sized inputs

Llvm/OneHot

  • Codestyle cleanup
  • Use sharp inequalities and unordered comparison
  • Return absolute value in MIN_ABS_VAL mode
  • Return first extreme value rather than the last (#3066)

Llvm/Scheduler

  • Do not use precomputed locations of execution counts

Llvm/builder_context

  • Remove used parameters workaround
  • Merge conversion of lists and tuples

Llvm/cleanup

  • Run GC only if needed

Llvm/codegen

  • Factor out resetting of execution counts to a helper function

Llvm/compiler

  • Use node num_executions to implement AllHaveRun condition
  • Use TimeIndex enum to determine the size of the timestamp structure

Llvm/component

  • Explicitly check for numpy array functions (#2905)

Llvm/cuda

  • Always upload param structure to GPU mem
  • Always download "data" buffer after GPU execution
  • Download an free mutable GPU buffers after kernel execution
  • Synchronize CPU and GPU buffers (#2969)

Llvm/execute

  • Move cuda_execute for Function and Mechanism to FuncExecution

Llvm/execution

  • Restrict writeback API to state structures
  • Skip "ring_memory" parameter.
  • Skip writeback of special RTM params
  • Consolidate recursion points in writeback
  • Use ctypes type in sizeof call
  • Skip writeback of "optimizer" and "num_executions"
  • Remove writeback condition parameter
  • Make parameter and state writeback private
  • Retrieve PNL parameter value only once
  • Do stricter checks when reshaping synced parameters
  • Covert compiled structures to numpy before sync to PNL params
  • Cache both ctype and numpy compiled structures
  • Cache numpy struct of execution conditions
  • Remove byref calls
  • Don't use wrap_call to execute "run"
  • Use converted dtype to construct compiled numpy structures
  • Use numpy structures for param, state and data arguments
  • Use numpy structures for Function and Mechanism outputs
  • Use numpy structures for Function and Mechanism inputs
  • Use numpy structure for 'conditions' argument
  • Use numpy structures for frozen values
  • Use numpy structures to extract data
  • Use numpy structure to insert output data
  • Do not store ctype structure of frozen values
  • Drop 'context' argument
  • Use numpy structure for execution input
  • Simplify and remove dead code
  • Consolidate shared code between CPU and GPU 'run'
  • Consolidate shared code between CPU and GPU 'evaluate'
  • Use Context instance in the CompExecution constructor
  • Use numpy arrays to return results of LLVM/PTX Run
  • Use numpy arrays to return result of compiled evaluate
  • Drop unused import

Llvm/execution/cuda

  • Use numpy argument handlers to access compiled structures
  • Use numpy arrays and arg handlers to extract results
  • Create numpy stuructres for compiled input
  • Drop upload/download counter
  • Always use pycuda ArgumentHandler as cached buffer (#3010)

Llvm/execution/run

  • Use numpy structures for input and execution counts

Llvm/gpu

  • Use more aggressive optimizations for GPUs

Llvm/helpers

  • Assert on invalid floating point conversion
  • Always assume that the Treshold target is an array
  • Assert if printf is not found

Llvm/scheduler

  • Drop tracking of the number of node executions
  • Assert that enabled controller uses TRIAL time scale
  • Use position in consideration queue to honor data dependencies
  • Move compiled scheduler to its own file

Llvm/thread_evaluate

  • Reuse type-cast parameters (#2923)

Mdf

  • Encode numpy functions the same as Python functions (#2909)

Parameters

  • Sync numeric values with compiled structures
  • On incompatible value, only delete necessary compiled struct

Requirements

  • Bump pycuda to <2025 (#2902)
  • Update numpy requirement from <1.24.5,>=1.21.0 to >=1.21.0,<1.25.3 (#2906)
  • Update numpy requirement (#2904)
  • Update llvmlite requirement from <0.42 to <0.43 (#2910)
  • Update pytest requirement from <8.0.1 to <8.0.2 (#2917)
  • Update grpcio requirement from <1.61.0 to <1.63.0 (#2919)
  • Update pandas requirement from <2.2.1 to <2.2.2 (#2920)
  • Update pytest requirement from <8.0.2 to <8.0.3 (#2921)
  • Update matplotlib requirement from <3.7.3 to <3.7.6 (#2925)
  • Update packaging requirement from <24.0 to <25.0 (#2926)
  • Update pytest requirement from <8.0.3 to <8.1.2 (#2928)
  • Update pytest-cov requirement from <4.1.1 to <5.0.1 (#2934)
  • Update beartype requirement from <0.18.0 to <0.19.0 (#2949)
  • Update torch requirement from >=1.8.0,<2.2.0 to >=1.8.0,<2.3.0 (#2950)
  • Update torch requirement from >=1.8.0,<2.3.0 to >=1.8.0,<2.4.0 (#2951)
  • Update pandas requirement from <2.2.2 to <2.2.3 (#2952)
  • Update pillow requirement from <10.3.0 to <10.4.0 (#2954)
  • Update networkx requirement from <3.3 to <3.4 (#2955)
  • Update pytest requirement from <8.1.2 to <8.1.3 (#2956)
  • Update pytest requirement from <8.1.3 to <8.2.1 (#2960)
  • Update pytest-xdist requirement (#2959)
  • Update grpcio requirement from <1.63.0 to <1.64.0 (#2961)
  • Update grpcio requirement from <1.64.0 to <1.65.0 (#2970)
  • Update pytest requirement from <8.2.2 to <8.2.3 (#2974)
  • Update llvmlite requirement from <0.43 to <0.44 (#2978)
  • Update pillow requirement from <10.4.0 to <10.5.0 (#2990)
  • Update grpcio requirement from <1.65.0 to <1.66.0 (#3000)
  • Update pytest requirement from <8.2.3 to <8.3.2 (#3004)
  • Update pytest requirement from <8.3.2 to <8.3.3 (#3012)
  • Set minimum scipy version to 1.7.3
  • Update scipy requirement from <1.12 to <1.14
  • Update scipy requirement from <1.14 to <1.15
  • Update scipy requirements from <1.12 to >=1.7.3, < 1.14.0 (#3018)
  • Update grpcio requirement from <1.66.0 to <1.67.0 (#3034)
  • Update jupyter requirement from <1.0.1 to <1.1.1 (#3039)
  • Update torch requirement from >=1.8.0,<2.4.0 to >=1.8.0,<2.5.0 (#3040)
  • Update jupyter requirement from <1.1.1 to <1.1.2 (#3041)
  • Update pytest requirement from <8.3.3 to <8.3.4 (#3045)
  • Update pandas requirement from <2.2.3 to <2.2.4 (#3049)
  • Update beartype requirement from <0.19.0 to <0.20.0 (#3050)
  • Update dill requirement from <0.3.9 to <0.3.10 (#3054)
  • Update pytest-pycodestyle requirement (#3061)
  • Update pytest-pydocstyle requirement from <2.4.0 to <2.5.0 (#3064)
  • Update networkx requirement from <3.4 to <3.5 (#3067)
  • Update pillow requirement from <10.5.0 to <11.1.0 (#3070)
  • Update grpcio requirement from <1.67.0 to <1.68.0 (#3072)
  • Update pytest-profiling requirement from <1.7.1 to <1.8.1 (#3074)
  • Update torch requirement from >=1.10.0,<2.5.0 to >=1.10.0,<2.6.0 (#3077)
  • Update pytest-benchmark requirement from <4.0.1 to <5.1.1 (#3091)
  • Update optuna requirement from <3.4.0 to <4.1.0 (#3042)
  • Update pytest-cov requirement from <5.0.1 to <6.0.1 (#3097)
  • Update fastkde requirement to <2.0.2
  • Bump fastkde to 2.x (#3103)

Sampleiterator

  • Store numeric attrs as numpy arrays

Setup

  • Advertise support for python 3.12
  • Convert PEP3118 size mismatch warnings to errors

Showgraph

  • Make default subdirectory name consistent
  • Rename default subdirectory
  • Use pathlib to create output dirs instead of str append
  • Do not store output files in site-packages

Treewide

  • Use Python's all() instead of Numpy's alltrue
  • Avoid some deprecated numpy constructs (#2913)
  • Convert all external numeric parameter values into ndarray
  • Change all internal non-torch numeric values to numpy array
  • Remove numpy matrix references from docs
  • Remove numpy matrix in favor of numpy ndarray
  • Add space around operator in f-strings
  • Qualify calls to itertools.product/combinations
  • Qualify calls to product function (#2981)
  • Use ndarray.item() to convert single element numpy arrays to scalars (#3063)
  • Allow Mapping type for 'params' in Component construction
  • Rename Component arg size -> input_shapes

Utilities

  • Convert_all_elements_to_np_array: fix crash on arr containing 0 dim arr
  • Convert_all_elements_to_np_array: create fewer unnecessary internal arrays
  • Add helper functions using numpy
  • Add extended numpy array comparison function
  • Copy_iterable_with_shared: handle weakref types
  • Copy_iterable_with_shared: handle ContentAddressableList
  • Is_iterable: simplify and allow option to exclude str
  • Get_deepcopy_with_shared: handle object dict modification
  • Contains_type: handle infinite recursion for numpy matrix
  • Copy_iterable_with_shared: support numpy array
  • Add update_array_in_place function
  • Add array_from_matrix_string

Versioneer

  • Updated embedded versioneer to 0.29
Assets 4
Loading