From 8ef660663e14d06e9e33308fc864496b2f627ec8 Mon Sep 17 00:00:00 2001
From: Avik Pal <avikpal@iitk.ac.in>
Date: Sat, 21 Sep 2024 23:15:56 -0400
Subject: [PATCH] revert: "test: enable enzyme testing for recurrent models"

This reverts commit fe967bdac463e51c70ffb299c5d85d3899a73b6d.
---
 test/layers/recurrent_tests.jl | 32 ++++++++++++++++++++------------
 1 file changed, 20 insertions(+), 12 deletions(-)

diff --git a/test/layers/recurrent_tests.jl b/test/layers/recurrent_tests.jl
index c15e48b94..e249e200f 100644
--- a/test/layers/recurrent_tests.jl
+++ b/test/layers/recurrent_tests.jl
@@ -26,7 +26,7 @@
                 @test_throws ErrorException ps.train_state
 
                 @test_gradients(loss_loop_rnncell, ps; atol=1.0f-3, rtol=1.0f-3,
-                    soft_fail=[AutoFiniteDiff()])
+                    soft_fail=[AutoFiniteDiff()], broken_backends=[AutoEnzyme()])
             end
         end
 
@@ -84,7 +84,7 @@ end
                 end
 
                 @test_gradients(loss_loop_lstmcell, ps; atol=1.0f-3, rtol=1.0f-3,
-                    soft_fail=[AutoFiniteDiff()])
+                    soft_fail=[AutoFiniteDiff()], broken_backends=[AutoEnzyme()])
 
                 @test_throws ErrorException ps.train_state
                 @test_throws ErrorException ps.train_memory
@@ -195,7 +195,7 @@ end
                 end
 
                 @test_gradients(loss_loop_grucell, ps; atol=1e-3, rtol=1e-3,
-                    soft_fail=[AutoFiniteDiff()])
+                    soft_fail=[AutoFiniteDiff()], broken_backends=[AutoEnzyme()])
 
                 @test_throws ErrorException ps.train_state
             end
@@ -282,7 +282,7 @@ end
                 end
 
                 @test_gradients(loss_loop_rnn, ps; atol=1e-3, rtol=1e-3,
-                    soft_fail=[AutoFiniteDiff()])
+                    broken_backends=[AutoEnzyme()], soft_fail=[AutoFiniteDiff()])
             end
         end
     end
@@ -327,11 +327,11 @@ end
 
                         __f = p -> sum(first(rnn(x, p, st)))
                         @test_gradients(__f, ps; atol=1e-3, rtol=1e-3,
-                            soft_fail=[AutoFiniteDiff()])
+                            skip_backends=[AutoEnzyme()], soft_fail=[AutoFiniteDiff()])
 
                         __f = p -> sum(Base.Fix1(sum, abs2), first(rnn_seq(x, p, st)))
                         @test_gradients(__f, ps; atol=1e-3, rtol=1e-3,
-                            soft_fail=[AutoFiniteDiff()])
+                            skip_backends=[AutoEnzyme()], soft_fail=[AutoFiniteDiff()])
                     end
 
                     # Batched Time Series without data batches
@@ -362,11 +362,11 @@ end
 
                         __f = p -> sum(first(rnn(x, p, st)))
                         @test_gradients(__f, ps; atol=1e-3, rtol=1e-3,
-                            soft_fail=[AutoFiniteDiff()])
+                            skip_backends=[AutoEnzyme()], soft_fail=[AutoFiniteDiff()])
 
                         __f = p -> sum(Base.Fix1(sum, abs2), first(rnn_seq(x, p, st)))
                         @test_gradients(__f, ps; atol=1e-3, rtol=1e-3,
-                            soft_fail=[AutoFiniteDiff()])
+                            skip_backends=[AutoEnzyme()], soft_fail=[AutoFiniteDiff()])
                     end
                 end
             end
@@ -415,13 +415,17 @@ end
             @test all(x -> size(x) == (5, 2), y_[1])
 
             __f = p -> sum(Base.Fix1(sum, abs2), first(bi_rnn(x, p, st)))
-            @test_gradients(__f, ps; atol=1e-3, rtol=1e-3)
+            @test_gradients(__f, ps; atol=1e-3,
+                rtol=1e-3,
+                broken_backends=Sys.isapple() ? [AutoEnzyme()] : [])
 
             __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
-            @test_gradients(__f, ps; atol=1e-3, rtol=1e-3)
+            @test_gradients(__f, ps; atol=1e-3,
+                rtol=1e-3,
+                broken_backends=Sys.isapple() ? [AutoEnzyme()] : [])
 
             @testset "backward_cell: $_backward_cell" for _backward_cell in (
                 RNNCell, LSTMCell, GRUCell)
@@ -449,13 +453,17 @@ end
                 @test all(x -> size(x) == (5, 2), y_[1])
 
                 __f = p -> sum(Base.Fix1(sum, abs2), first(bi_rnn(x, p, st)))
-                @test_gradients(__f, ps; atol=1e-3, rtol=1e-3)
+                @test_gradients(__f, ps; atol=1e-3,
+                    rtol=1e-3,
+                    broken_backends=Sys.isapple() ? [AutoEnzyme()] : [])
 
                 __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
-                @test_gradients(__f, ps; atol=1e-3, rtol=1e-3)
+                @test_gradients(__f, ps; atol=1e-3,
+                    rtol=1e-3,
+                    broken_backends=Sys.isapple() ? [AutoEnzyme()] : [])
             end
         end
     end