Hello all,
Does anyone have experience with random number generation in TensorFlow.jl?
At the moment, I am failing to create a random_normal. If I invoke
random_normal([5,5])
I receive following error message:
ERROR: Tensorflow error: Status: NodeDef missing attr 'dtype' from Op<name=RandomStandardNormal; signature=shape:T -> output:dtype; attr=seed:int,default=0; attr=seed2:int,default=0; attr=dtype:type,allowed=[DT_HALF, DT_FLOAT, DT_DOUBLE]; attr=T:type,allowed=[DT_INT32, DT_INT64]; is_stateful=true>; NodeDef: random_normal_11/RandomStandardNormal_11 = RandomStandardNormal[T=DT_INT64, _class=[], seed=0, seed2=0](random_normal_11/RandomStandardNormal_11/Const_95)
Stacktrace:
[1] check_status at /Users/tpevny/.julia/v0.6/TensorFlow/src/core.jl:405 [inlined]
[2] TensorFlow.Operation(::TensorFlow.NodeDescription) at /Users/tpevny/.julia/v0.6/TensorFlow/src/core.jl:969
[3] #random_standard_normal#1831(::Void, ::Void, ::Void, ::Void, ::Function, ::Array{Int64,1}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/ops/imported_ops.jl:18158
[4] (::TensorFlow.Ops.#kw##random_standard_normal)(::Array{Any,1}, ::TensorFlow.Ops.#random_standard_normal, ::Array{Int64,1}) at ./<missing>:0
[5] (::TensorFlow.##166#167{Float64,Float64,Void,Array{Any,1},Array{Int64,1}})() at /Users/tpevny/.julia/v0.6/TensorFlow/src/ops/sequences.jl:27
[6] with_op_name(::TensorFlow.##166#167{Float64,Float64,Void,Array{Any,1},Array{Int64,1}}, ::Void, ::String) at /Users/tpevny/.julia/v0.6/TensorFlow/src/core.jl:924
[7] #random_normal#165 at /Users/tpevny/.julia/v0.6/TensorFlow/src/ops/sequences.jl:26 [inlined]
[8] random_normal(::Array{Int64,1}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/ops/sequences.jl:25
and if I supply d_type
random_normal([5,5],dtype=Float32)
I receive
Error showing value of type TensorFlow.Tensor{Float64}:
ERROR: MethodError: Cannot `convert` an object of type Array{Int64,1} to an object of type TensorFlow.TensorShape
This may have arisen from a call to the constructor TensorFlow.TensorShape(...),
since type constructors fall back to convert methods.
Stacktrace:
[1] setindex!(::Dict{Tuple{String,Int64},TensorFlow.TensorShape}, ::Array{Int64,1}, ::Tuple{String,Int64}) at ./dict.jl:420
[2] _get_shape(::TensorFlow.Tensor{Float32}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:107
[3] (::TensorFlow.ShapeInference.##7#8)(::TensorFlow.Operation) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:144
[4] _get_shape(::TensorFlow.Tensor{Float64}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:103
[5] (::TensorFlow.ShapeInference.##17#18)(::TensorFlow.Operation) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:190
[6] _get_shape(::TensorFlow.Tensor{Float64}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:103
[7] (::TensorFlow.ShapeInference.##17#18)(::TensorFlow.Operation) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:190
[8] _get_shape(::TensorFlow.Tensor{Float64}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/shape_inference.jl:103
[9] show(::IOContext{Base.Terminals.TTYTerminal}, ::TensorFlow.Tensor{Float64}) at /Users/tpevny/.julia/v0.6/TensorFlow/src/show.jl:48
[10] display(::Base.REPL.REPLDisplay{Base.REPL.LineEditREPL}, ::MIME{Symbol("text/plain")}, ::TensorFlow.Tensor{Float64}) at ./REPL.jl:122
[11] display(::Base.REPL.REPLDisplay{Base.REPL.LineEditREPL}, ::TensorFlow.Tensor{Float64}) at ./REPL.jl:125
[12] display(::TensorFlow.Tensor{Float64}) at ./multimedia.jl:194
[13] eval(::Module, ::Any) at ./boot.jl:235
[14] print_response(::Base.Terminals.TTYTerminal, ::Any, ::Void, ::Bool, ::Bool, ::Void) at ./REPL.jl:144
[15] print_response(::Base.REPL.LineEditREPL, ::Any, ::Void, ::Bool, ::Bool) at ./REPL.jl:129
[16] (::Base.REPL.#do_respond#16{Bool,Base.REPL.##26#36{Base.REPL.LineEditREPL,Base.REPL.REPLHistoryProvider},Base.REPL.LineEditREPL,Base.LineEdit.Prompt})(::Base.LineEdit.MIState, ::Base.AbstractIOBuffer{Array{UInt8,1}}, ::Bool) at ./REPL.jl:646
I am rather puzzled here.
Furthermore, I would like to ask, if it is possible to create random tensor with a shape that will be inferred dynamically on basis of on other tensor. Something along the line
x=random_normal(shape(y))
where y will have shape [-1,d]
Thank you very much for answers. I have posted this as an issue to TensorFlow.jl