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Merge pull request #918 from JuliaAI/dev
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For a 0.21.12 release
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ablaom authored Jul 25, 2023
2 parents 9089635 + fa009a1 commit a437f97
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17 changes: 16 additions & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "MLJBase"
uuid = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
authors = ["Anthony D. Blaom <anthony.blaom@gmail.com>"]
version = "0.21.11"
version = "0.21.12"

[deps]
CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
Expand Down Expand Up @@ -33,6 +33,7 @@ Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
CategoricalArrays = "0.9, 0.10"
CategoricalDistributions = "0.1"
ComputationalResources = "0.3"
DelimitedFiles = "1"
Distributions = "0.25.3"
InvertedIndices = "1"
LossFunctions = "0.10"
Expand All @@ -47,3 +48,17 @@ StatisticalTraits = "3.2"
StatsBase = "0.32, 0.33, 0.34"
Tables = "0.2, 1.0"
julia = "1.6"

[extras]
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
DecisionTree = "7806a523-6efd-50cb-b5f6-3fa6f1930dbb"
Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
MultivariateStats = "6f286f6a-111f-5878-ab1e-185364afe411"
NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
TypedTables = "9d95f2ec-7b3d-5a63-8d20-e2491e220bb9"

[targets]
test = ["DataFrames", "DecisionTree", "Distances", "Logging", "MultivariateStats", "NearestNeighbors", "StableRNGs", "Test", "TypedTables"]
4 changes: 1 addition & 3 deletions README.md
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Expand Up @@ -29,9 +29,7 @@ repository provides core functionality for MLJ, including:
[MLJModelInterface](https://github.com/JuliaAI/MLJModelInterface.jl) (/src/interface)

- definition of **machines** and their associated methods, such as
`fit!` and `predict`/`transform` (src/machines). Serialization of machines,
however, now lives in
[MLJSerialization](https://github.com/JuliaAI/MLJSerialization.jl).
`fit!` and `predict`/`transform` (src/machines).

- MLJ's **model composition** interface, including **learning
networks**, **pipelines**, **stacks**, **target transforms** (/src/composition)
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9 changes: 5 additions & 4 deletions src/MLJBase.jl
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Expand Up @@ -292,11 +292,15 @@ export coerce, coerce!, autotype, schema, info
export UnivariateFiniteArray, UnivariateFiniteVector

# -----------------------------------------------------------------------
# abstract model types defined in MLJModelInterface.jl and extended here:
# re-export from MLJModelInterface.jl

#abstract model types defined in MLJModelInterface.jl and extended here:
for T in EXTENDED_ABSTRACT_MODEL_TYPES
@eval(export $T)
end

export params

# -------------------------------------------------------------------
# exports from this module, MLJBase

Expand All @@ -306,9 +310,6 @@ export default_resource
# one_dimensional_ranges.jl:
export ParamRange, NumericRange, NominalRange, iterator, scale

# parameter_inspection.jl:
export params # note this is *not* an extension of StatsBase.params

# data.jl:
export partition, unpack, complement, restrict, corestrict

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8 changes: 4 additions & 4 deletions src/machines.jl
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Expand Up @@ -533,7 +533,7 @@ last_model(mach) = isdefined(mach, :old_model) ? mach.old_model : nothing
rows=nothing,
verbosity=1,
force=false,
composite=nothing
composite=nothing,
)
Without mutating any other machine on which it may depend, perform one of the following
Expand All @@ -553,7 +553,7 @@ data to `rows` if specified:
increment `mach.state`.
If the model, `model`, bound to `mach` is a symbol, then instead perform the action using
the true model `getproperty(composite, model)`.
the true model given by `getproperty(composite, model)`. See also [`machine`](@ref).
### Training action logic
Expand Down Expand Up @@ -762,13 +762,13 @@ end

"""
fit!(mach::Machine, rows=nothing, verbosity=1, force=false)
fit!(mach::Machine, rows=nothing, verbosity=1, force=false, composite=nothing)
Fit the machine `mach`. In the case that `mach` has `Node` arguments,
first train all other machines on which `mach` depends.
To attempt to fit a machine without touching any other machine, use
`fit_only!`. For more on the internal logic of fitting see
`fit_only!`. For more on options and the the internal logic of fitting see
[`fit_only!`](@ref)
"""
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11 changes: 6 additions & 5 deletions src/operations.jl
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Expand Up @@ -138,7 +138,7 @@ for operation in OPERATIONS
get!(ret, $quoted_operation, mach)
end

function $operation(mach::Machine{<:Static}, Xraw, Xraw_more...)
function $operation(mach::Machine, Xraw, Xraw_more...)
_check_and_fit_if_warranted!(mach)
ret = $(operation)(
last_model(mach),
Expand All @@ -153,10 +153,11 @@ for operation in OPERATIONS
$operation(mach::Machine, X::AbstractNode) =
node($(operation), mach, X)

$operation(mach::Machine{<:Static},
X::AbstractNode,
Xmore::AbstractNode...) =
node($(operation), mach, X, Xmore...)
$operation(
mach::Machine,
X::AbstractNode,
Xmore::AbstractNode...,
) = node($(operation), mach, X, Xmore...)
end
eval(ex)
end
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33 changes: 0 additions & 33 deletions src/parameter_inspection.jl

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26 changes: 0 additions & 26 deletions test/Project.toml

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