Re-add the tests

src/layers/recurrent.jl

@@ -702,6 +702,8 @@ function BidirectionalRNN(cell::AbstractRecurrentCell;
  backward_rnn_layer = backward_cell === nothing ? layer :
  Recurrence(backward_cell; return_sequence=true, ordering)
  fuse_op = merge_mode === nothing ? nothing : Broadcast.BroadcastFunction(merge_mode)
- return BidirectionalRNN(Parallel(
- fuse_op, layer, Chain(ReverseSequence(), backward_rnn_layer, ReverseSequence())))
+ return BidirectionalRNN(Parallel(fuse_op;
+ forward_rnn=layer,
+ backward_rnn=Chain(;
+ rev1=ReverseSequence(), rnn=backward_rnn_layer, rev2=ReverseSequence())))
 end

test/layers/recurrent_tests.jl

@@ -402,17 +402,14 @@ end
  @test size(y_[1]) == (4,)
  @test all(x -> size(x) == (5, 2), y_[1])
 
- if mode != "AMDGPU"
- # gradients test failed after vcat
- # __f = p -> sum(Base.Fix1(sum, abs2), first(bi_rnn(x, p, st)))
- # @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
+ __f = p -> sum(Base.Fix1(sum, abs2), first(bi_rnn(x, p, st)))
+ @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
 
- __f = p -> sum(
- Base.Fix1(sum, abs2), first(first(bi_rnn_no_merge(x, p, st))))
- @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
- else
- # This is just added as a stub to remember about this broken test
+ __f = p -> begin
+ (y1, y2), st_ = bi_rnn_no_merge(x, p, st)
+ return sum(Base.Fix1(sum, abs2), y1) + sum(Base.Fix1(sum, abs2), y2)
  end
+ @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
 
  @testset "backward_cell: $_backward_cell" for _backward_cell in (
  RNNCell, LSTMCell, GRUCell)
@@ -421,7 +418,6 @@ end
  bi_rnn = BidirectionalRNN(cell; backward_cell=backward_cell)
  bi_rnn_no_merge = BidirectionalRNN(
  cell; backward_cell=backward_cell, merge_mode=nothing)
- println("BidirectionalRNN:")
  display(bi_rnn)
 
  # Batched Time Series
@@ -441,18 +437,14 @@ end
  @test size(y_[1]) == (4,)
  @test all(x -> size(x) == (5, 2), y_[1])
 
- if mode != "AMDGPU"
- # gradients test failed after vcat
- # __f = p -> sum(Base.Fix1(sum, abs2), first(bi_rnn(x, p, st)))
- # @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
+ __f = p -> sum(Base.Fix1(sum, abs2), first(bi_rnn(x, p, st)))
+ @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
 
- __f = p -> sum(
- Base.Fix1(sum, abs2), first(first(bi_rnn_no_merge(x, p, st))))
- @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
- else
- # This is just added as a stub to remember about this broken test
- @test_broken 1 + 1 == 1
+ __f = p -> begin
+ (y1, y2), st_ = bi_rnn_no_merge(x, p, st)
+ return sum(Base.Fix1(sum, abs2), y1) + sum(Base.Fix1(sum, abs2), y2)
  end
+ @eval @test_gradients $__f $ps atol=1e-2 rtol=1e-2 gpu_testing=$ongpu
  end
  end
  end