tensorflow
'Data.Map.fromList' throws error
I've tried to install tensorflow v0.1.0.2, but it throws the following errors. I'm on macOS High Sierra and have installed all the tools mentioned in the script.
Any ideas?
Warning: The package list for 'hackage.haskell.org' is 56 days old.
Run 'cabal update' to get the latest list of available packages.
Resolving dependencies...
Configuring tensorflow-proto-0.1.0.0...
Building tensorflow-proto-0.1.0.0...
Failed to install tensorflow-proto-0.1.0.0
Build log ( /Users/lukas/.cabal/logs/ghc-8.2.2/tensorflow-proto-0.1.0.0-D7saAu502llB6QqUq2V7pm.log ):
cabal: Entering directory '/var/folders/2n/wsfq37nn2dv23rx8wcsn9d6m0000gn/T/cabal-tmp-49665/tensorflow-proto-0.1.0.0'
[1 of 1] Compiling Main ( /var/folders/2n/wsfq37nn2dv23rx8wcsn9d6m0000gn/T/cabal-tmp-49665/tensorflow-proto-0.1.0.0/dist/setup/setup.hs, /var/folders/2n/wsfq37nn2dv23rx8wcsn9d6m0000gn/T/cabal-tmp-49665/tensorflow-proto-0.1.0.0/dist/setup/Main.o )
Linking /var/folders/2n/wsfq37nn2dv23rx8wcsn9d6m0000gn/T/cabal-tmp-49665/tensorflow-proto-0.1.0.0/dist/setup/setup ...
Configuring tensorflow-proto-0.1.0.0...
Preprocessing library for tensorflow-proto-0.1.0.0..
Building library for tensorflow-proto-0.1.0.0..
[ 1 of 18] Compiling Proto.Tensorflow.Core.Framework.AllocationDescription ( dist/build/autogen/Proto/Tensorflow/Core/Framework/AllocationDescription.hs, dist/build/Proto/Tensorflow/Core/Framework/AllocationDescription.o )
dist/build/autogen/Proto/Tensorflow/Core/Framework/AllocationDescription.hs:159:15: error:
• Couldn't match expected type ‘Data.ProtoLens.MessageDescriptor
AllocationDescription’
with actual type ‘Data.Map.Map
Prelude.String
(Data.ProtoLens.FieldDescriptor AllocationDescription)
-> Data.ProtoLens.MessageDescriptor AllocationDescription’
• Probable cause: ‘Data.ProtoLens.MessageDescriptor’ is applied to too few arguments
In the expression:
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor),
(Data.ProtoLens.Tag 4, allocationId__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor),
("allocation_id", allocationId__field_descriptor), ....])
In the expression:
let
requestedBytes__field_descriptor
= Data.ProtoLens.FieldDescriptor
"requested_bytes"
(Data.ProtoLens.Int64Field ::
Data.ProtoLens.FieldTypeDescriptor Data.Int.Int64)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional requestedBytes) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
allocatedBytes__field_descriptor
= Data.ProtoLens.FieldDescriptor
"allocated_bytes"
(Data.ProtoLens.Int64Field ::
Data.ProtoLens.FieldTypeDescriptor Data.Int.Int64)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional allocatedBytes) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
allocatorName__field_descriptor
= Data.ProtoLens.FieldDescriptor
"allocator_name"
(Data.ProtoLens.StringField ::
Data.ProtoLens.FieldTypeDescriptor Data.Text.Text)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional allocatorName) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
....
in
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor), ....])
In an equation for ‘Data.ProtoLens.descriptor’:
Data.ProtoLens.descriptor
= let
requestedBytes__field_descriptor = ...
allocatedBytes__field_descriptor = ...
....
in
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor), ....])
|
159 | Data.ProtoLens.MessageDescriptor
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...
dist/build/autogen/Proto/Tensorflow/Core/Framework/AllocationDescription.hs:160:18: error:
• Couldn't match expected type ‘Data.Text.Text’
with actual type ‘Data.Map.Map
Data.ProtoLens.Tag
(Data.ProtoLens.FieldDescriptor AllocationDescription)’
• In the first argument of ‘Data.ProtoLens.MessageDescriptor’, namely
‘(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor),
(Data.ProtoLens.Tag 4, allocationId__field_descriptor), ....])’
In the expression:
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor),
(Data.ProtoLens.Tag 4, allocationId__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor),
("allocation_id", allocationId__field_descriptor), ....])
In the expression:
let
requestedBytes__field_descriptor
= Data.ProtoLens.FieldDescriptor
"requested_bytes"
(Data.ProtoLens.Int64Field ::
Data.ProtoLens.FieldTypeDescriptor Data.Int.Int64)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional requestedBytes) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
allocatedBytes__field_descriptor
= Data.ProtoLens.FieldDescriptor
"allocated_bytes"
(Data.ProtoLens.Int64Field ::
Data.ProtoLens.FieldTypeDescriptor Data.Int.Int64)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional allocatedBytes) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
allocatorName__field_descriptor
= Data.ProtoLens.FieldDescriptor
"allocator_name"
(Data.ProtoLens.StringField ::
Data.ProtoLens.FieldTypeDescriptor Data.Text.Text)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional allocatorName) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
....
in
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor), ....])
|
160 | (Data.Map.fromList
| ^^^^^^^^^^^^^^^^^...
dist/build/autogen/Proto/Tensorflow/Core/Framework/AllocationDescription.hs:167:18: error:
• Couldn't match type ‘[Prelude.Char]’ with ‘Data.ProtoLens.Tag’
Expected type: Data.Map.Map
Data.ProtoLens.Tag
(Data.ProtoLens.FieldDescriptor AllocationDescription)
Actual type: Data.Map.Map
[Prelude.Char]
(Data.ProtoLens.FieldDescriptor AllocationDescription)
• In the second argument of ‘Data.ProtoLens.MessageDescriptor’, namely
‘(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor),
("allocation_id", allocationId__field_descriptor), ....])’
In the expression:
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor),
(Data.ProtoLens.Tag 4, allocationId__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor),
("allocation_id", allocationId__field_descriptor), ....])
In the expression:
let
requestedBytes__field_descriptor
= Data.ProtoLens.FieldDescriptor
"requested_bytes"
(Data.ProtoLens.Int64Field ::
Data.ProtoLens.FieldTypeDescriptor Data.Int.Int64)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional requestedBytes) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
allocatedBytes__field_descriptor
= Data.ProtoLens.FieldDescriptor
"allocated_bytes"
(Data.ProtoLens.Int64Field ::
Data.ProtoLens.FieldTypeDescriptor Data.Int.Int64)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional allocatedBytes) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
allocatorName__field_descriptor
= Data.ProtoLens.FieldDescriptor
"allocator_name"
(Data.ProtoLens.StringField ::
Data.ProtoLens.FieldTypeDescriptor Data.Text.Text)
(Data.ProtoLens.PlainField
Data.ProtoLens.Optional allocatorName) ::
Data.ProtoLens.FieldDescriptor AllocationDescription
....
in
Data.ProtoLens.MessageDescriptor
(Data.Map.fromList
[(Data.ProtoLens.Tag 1, requestedBytes__field_descriptor),
(Data.ProtoLens.Tag 2, allocatedBytes__field_descriptor),
(Data.ProtoLens.Tag 3, allocatorName__field_descriptor), ....])
(Data.Map.fromList
[("requested_bytes", requestedBytes__field_descriptor),
("allocated_bytes", allocatedBytes__field_descriptor),
("allocator_name", allocatorName__field_descriptor), ....])
|
167 | (Data.Map.fromList
| ^^^^^^^^^^^^^^^^^...
cabal: Leaving directory '/var/folders/2n/wsfq37nn2dv23rx8wcsn9d6m0000gn/T/cabal-tmp-49665/tensorflow-proto-0.1.0.0'
cabal: Error: some packages failed to install:
hs-ml-0.1.0.0-363V9CZ7RT7C3io8MyqwFB depends on hs-ml-0.1.0.0 which failed to
install.
tensorflow-0.1.0.2-7XYTRIMIoHSHYi9V7yt0q0 depends on tensorflow-0.1.0.2 which
failed to install.
tensorflow-proto-0.1.0.0-D7saAu502llB6QqUq2V7pm failed during the building
phase. The exception was:
ExitFailure 1
I see you are using cabal. What version of proto-lens do you have installed? We are pegged at version proto-lens-0.2.2.0 and don't support the newest version yet, so I suspect that is the issue.
@fkm3 I don't think that your proposed explanation is correct. I have the same issue when trying to build with nixos 18.03, it pegs proto-lens-0.2.2.0 too.
Are you getting this same error? Or, are you getting the error reported in https://github.com/tensorflow/haskell/issues/190?
This is also being discussed on haskell-cafe: https://mail.haskell.org/pipermail/haskell-cafe/2018-May/129103.html
I'm not sure what exactly to blame, but a bunch of weird things are coinciding to bring you this error:
- The uploaded tarball tensorflow-proto-0.1.0.0 contains the auto-generated .hs sources for the contained protos, as generated by (seemingly) proto-lens-protoc <0.2.2
- proto-lens changed some internal types before proto-lens-0.2.2.0 that breaks compatibility with the generated code.
- Cabal is trying to compile the generated sources from the tarball rather than regenerating them with proto-lens-protoc, so it fails to build when proto-lens-0.2.2.* is selected.
If I 'cabal get' the package, delete the generated Haskell modules, and repackage it (with tar --format=ustar, since everything else makes cabal explode), it does actually start working again (Cabal-2.0.1.1, proto-lens-protoc-0.2.2.3, proto-lens-0.2.2.0), because the chosen version of proto-lens-protoc is used to generate the modules.
Unfortunately cabal and stack become very unhappy if you try to 'sdist' packages that mention Haskell files that don't exist, so the release process for packages that include modules generated by proto-lens is to generate the code, then 'sdist' them, which means the generated code is included in the uploads.
It might be appropriate to update the version bounds on the affected packages to require a version of proto-lens that's compatible with the included generated code (in this case, proto-lens <0.2.2) -- but if older versions of cabal can still compile against other versions, this would be unnecessarily restrictive.
It might also make sense to work around this by releasing a new tensorflow-proto version that's had the generated modules removed, and mark 0.1.0.0 as deprecated.
@awpr thanks for pinpointing the problem with the sdist file. I've created google/proto-lens#185 to use the autogen-modules field from Cabal-2.0, which lets us avoid including the generated files in the release tarball.
For tensorflow-proto, given that it's still using proto-lens-0.2.*, in the short term it might make sense to do a new manual release (as you suggested) with the generated files removed, using autogen-modules, and requiring cabal-version: >=2.0.
i've tried all sorts of workarounds for this on MacOs and Fedora, i assume that this is still an issue and not fixed yet? Or do i have to pull in some specific protoc/proto-lens versions. unfortunately i'm a beginner in the haskell ecosystem and don't understand how to make it compile. it's a shame, i was really looking forward to using this with jupyter + iHaskell.
I've released a new version to hackage, so the generated files should align with the newest proto-lens version that we claim to support. Does that fix the issue your experiencing?
I'd have done what @awpr and @judah suggested, but I'm not too familiar with the intricacies of cabal, so I was afraid I'd do more harm than good.