resolve comments

Author: codeboy5

FastTimeSeries/Project.toml

@@ -13,7 +13,6 @@ MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 UnicodePlots = "b8865327-cd53-5732-bb35-84acbb429228"
-Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 DataDeps = "0.7"
@@ -23,5 +22,4 @@ Flux = "0.12, 0.13"
 InlineTest = "0.2"
 MLUtils = "0.2"
 UnicodePlots = "2, 3"
-julia = "1.6"
-Zygote = "0.6"
+julia = "1.6"

FastTimeSeries/src/models.jl

@@ -9,7 +9,6 @@ function blockmodel(inblock::TimeSeriesRow,
                 backbone)
     #TODO: Use Flux.outputsize here.
     data   = rand(Float32, inblock.nfeatures, 32, inblock.obslength)
-    # data   = [rand(Float32, inblock.nfeatures, 32) for _ ∈ 1:inblock.obslength]
     output = backbone(data)
     return Models.RNNModel(backbone, outsize = length(outblock.classes), recout = size(output, 1))
 end
@@ -25,4 +24,6 @@ end
 
 # ## Tests
 
-@testset "blockbackbone" begin @test_nowarn FastAI.blockbackbone(TimeSeriesRow(1,140)) end
+@testset "blockbackbone" begin 
+    @test_nowarn FastAI.blockbackbone(TimeSeriesRow(1,140)) 
+end

FastTimeSeries/src/models/InceptionTime.jl

@@ -65,10 +65,7 @@ function InceptionBlock(ni::Int, nf::Int = 32, residual::Bool = true, depth::Int
 
 end
 
-function changedims(X)
-    X = permutedims(X, (2, 1, 3))
-    return X
-end
+changedims(X) = permutedims(X, (2, 1, 3))
 
 """
     InceptionTime(c_in::Int, c_out::Int, seq_len = nothing, nf::Int = 32)

FastTimeSeries/src/models/RNN.jl

@@ -1,7 +1,4 @@
-function tabular2rnn(X::AbstractArray{Float32, 3})
-    X = permutedims(X, (1, 3, 2))
-    return X
-end
+tabular2rnn(X::AbstractArray{<:AbstractFloat, 3}) = permutedims(X, (1, 3, 2))
 
 struct RNNModel{A, B}
     recbackbone::A
@@ -32,6 +29,9 @@ end
 function (m::RNNModel)(X)
     X = tabular2rnn(X)
     Flux.reset!(m.recbackbone)
+    # ChainRulesCore.ignore_derivatives() do
+    #     Flux.reset!(m.recbackbone)
+    # end
     X = m.recbackbone(X)[:, :, end]
     return m.finalclassifier(X)
 end

FastTimeSeries/src/models/layers.jl

@@ -21,18 +21,17 @@ of the layers.
 function StackedLSTM(in::Int, out::Integer, hiddensize::Integer, layers::Integer;
 			init=Flux.glorot_uniform)
 	if layers == 1
-		chain = Chain(LSTM(in, out; init=init))
+		return Chain(LSTM(in, out; init=init))
 	elseif layers == 2
-		chain = Chain(LSTM(in, hiddensize; init=init),
+		return Chain(LSTM(in, hiddensize; init=init),
 					  LSTM(hiddensize, out; init=init))
 	else
 		chain_vec = [LSTM(in, hiddensize; init=init)]
 		for i = 1:layers - 2
 			push!(chain_vec, LSTM(hiddensize, hiddensize; init=init))
 		end
-		chain = Chain(chain_vec..., LSTM(hiddensize, out; init=init))
+		return Chain(chain_vec..., LSTM(hiddensize, out; init=init))
 	end
-	return chain
 end
 
 function Conv1d(ni, nf, ks; stride = 1, padding = Flux.SamePad, dilation = 1, bias = true)