Merge pull request #1 from adamryczkowski/fbot/deps

Fix deprecations

docs/src/tutorial.md

@@ -64,7 +64,7 @@ end
 ### Evaluate the model
 
 ```julia
-correct_prediction = indmax(y, 2) .== indmax(y_, 2)
+correct_prediction = argmax(y, 2) .== argmax(y_, 2)
 accuracy=reduce_mean(cast(correct_prediction, Float32))
 testx, testy = load_test_set()
 
@@ -137,7 +137,7 @@ cross_entropy = reduce_mean(-reduce_sum(y_.*log(y_conv), axis=[2]))
 
 train_step = train.minimize(train.AdamOptimizer(1e-4), cross_entropy)
 
-correct_prediction = indmax(y_conv, 2) .== indmax(y_, 2)
+correct_prediction = argmax(y_conv, 2) .== argmax(y_, 2)
 
 accuracy = reduce_mean(cast(correct_prediction, Float32))
 

examples/mnist_full.jl

@@ -62,7 +62,7 @@ end
 
 train_step = train.minimize(train.AdamOptimizer(1e-4), cross_entropy)
 
-correct_prediction = indmax(y_conv, 2) .== indmax(y_, 2)
+correct_prediction = argmax(y_conv, 2) .== argmax(y_, 2)
 
 accuracy = reduce_mean(cast(correct_prediction, Float32))
 

examples/mnist_simple.jl

@@ -18,7 +18,7 @@ y = nn.softmax(x*W + b)
 cross_entropy = reduce_mean(-reduce_sum(y_ .* log(y), axis=[2]))
 train_step = train.minimize(train.GradientDescentOptimizer(.00001), cross_entropy)
 
-correct_prediction = indmax(y, 2) .== indmax(y_, 2)
+correct_prediction = argmax(y, 2) .== argmax(y_, 2)
 accuracy=reduce_mean(cast(correct_prediction, Float32))
 
 for i in 1:1000

src/TensorFlow.jl

@@ -1,4 +1,3 @@
-__precompile__(true)
 module TensorFlow
 
 @warn("Loading a new version of TensorFlow.jl for the first time. This initial load can take around 5 minutes as code is precompiled; subsequent usage will only take a few seconds.")

src/generate_ops.jl

@@ -69,7 +69,7 @@ Returns `true` if the given operation attribute is not meant to be supplied
 by the user and `false` otherwise.
 """
 function is_internal_arg(arg)
-    arg._type == "type" && ismatch(r"^T", arg.name)
+    arg._type == "type" && occursin(r"^T", arg.name)
 end
 
 function to_function(op::tensorflow.OpDef)
@@ -174,7 +174,7 @@ function to_function(op::tensorflow.OpDef)
             end
         end)
     end
-    unshift!(inputs, kwargs)
+    pushfirst!(inputs, kwargs)
     scalar_output = true
     if length(op.output_arg) > 1
         scalar_output = false
@@ -257,7 +257,7 @@ stringify_func(op::tensorflow.OpDef) = stringify_func(to_function(op))
 function load_default_imports()
     path = joinpath(@__DIR__, "../deps/default_imports.txt")
     names = readlines(path)
-    filtered = [name for name in names if !ismatch(r"^#", name)]
+    filtered = [name for name in names if !occursin(r"^#", name)]
     return filtered
 end
 
@@ -328,7 +328,7 @@ Returns a reference to a Julia function corresponding to the operation.
 function import_op(name)
     jl_name = opname_to_jlname(name)
     mod = TensorFlow.Ops
-    if jl_name ∉ names(mod, true)
+    if jl_name ∉ names(mod, all=true)
         ops = Dict(get_all_op_list())
         op = ops[name]
         op_desc = to_function(op)

src/shape_inference.jl

@@ -27,10 +27,10 @@ Base.copy(shape::TensorShape) = TensorShape(copy(shape.dims), shape.rank_unknown
 
 function Base.broadcast!(s1::TensorShape, s2::TensorShape)
     while length(s1.dims) < length(s2.dims)
-        unshift!(s1.dims, Nullable(1))
+        pushfirst!(s1.dims, Nullable(1))
     end
     while length(s2.dims) < length(s1.dims)
-        unshift!(s2.dims, Nullable(1))
+        pushfirst!(s2.dims, Nullable(1))
     end
     s1, s2
 end
@@ -261,7 +261,7 @@ function load_const(op)
         catch err
             if isa(err, tf.EmptyTensorError)
                 T = eltype(Tensor(op, 1))
-                value = Array{T}(0)
+                value = Array{T}(undef, 0)
             else
                 rethrow(err)
             end

src/show.jl

@@ -188,9 +188,9 @@ end
 
 function open_url(url)
     cmd = nothing
-    if is_apple()
+    if Sys.isapple()
         cmd = `open $url`
-    elseif is_unix()
+    elseif Sys.isunix()
         cmd = `xdg-open $url`
     end
     cmd === nothing || run(cmd)

src/variable.jl

@@ -186,7 +186,7 @@ end
 tf.get_tensors(v::Variable) = [v.var_node]
 
 function is_variable(name::AbstractString)
-    return ismatch(r"^(Variable|VariableV\d+)$", name)
+    return occursin(r"^(Variable|VariableV\d+)$", name)
 end
 
 is_variable(name::Union{tf.Operation, tf.AbstractTensor}) = is_variable(tf.get_op(name).op_name)

test/clipping.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 sess = TensorFlow.Session(TensorFlow.Graph())
 a_raw = rand(10, 10)

test/comp.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 sess = TensorFlow.Session(TensorFlow.Graph())
 a_raw = collect(1:5)
@@ -28,5 +28,5 @@ result = run(sess, TensorFlow.select(cond_tf, a, b))
 @test [1; 7; 3; 4; 10] == result
 
 
-@test run(sess, find(constant([true,true, false,true]))) == [1 2 4]'
-@test run(sess, find(constant([true true  false true; false true false true]))) == [1 1; 1 2; 1 4; 2 2; 2 4]
+@test run(sess, findall(constant([true,true, false,true]))) == [1 2 4]'
+@test run(sess, findall(constant([true true  false true; false true false true]))) == [1 1; 1 2; 1 4; 2 2; 2 4]

test/control.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 using TensorFlow
 
 

test/core.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 using TensorFlow
 const tf = TensorFlow
 

test/debug.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 sess = TensorFlow.Session()
 

test/hello.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 # Try your first TensorFlow program
 # https://github.com/tensorflow/tensorflow#try-your-first-tensorflow-program

test/image.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 
 sess = TensorFlow.Session(TensorFlow.Graph())
 

test/init_ops.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 
 sess = Session(Graph())

test/io.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 mktempdir() do dirname
     filename = joinpath(dirname, "tfrecords")

test/math.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 sess = TensorFlow.Session(TensorFlow.Graph())
 
@@ -89,15 +89,15 @@ end
 
     a_raw = rand(10)
     a = TensorFlow.constant(a_raw)
-    result = run(sess, indmin(a, 1))
-    @test indmin(a_raw) == result
-    result = run(sess, indmax(a, 1))
-    @test indmax(a_raw) == result
+    result = run(sess, argmin(a, 1))
+    @test argmin(a_raw) == result
+    result = run(sess, argmax(a, 1))
+    @test argmax(a_raw) == result
 
     #check it find the first instance of lowest/highers number as the result for indmin/indmax
     x=constant([1 2 3; 0 2 3; 0 0 3; 0 0 0]')
-    @test [2, 3, 4] == run(sess, indmin(x, 2))
-    @test [1, 1, 1] == run(sess, indmax(x, 2))
+    @test [2, 3, 4] == run(sess, argmin(x, 2))
+    @test [1, 1, 1] == run(sess, argmax(x, 2))
 end
 
 @testset "logic" begin

test/meta.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 using TensorFlow
 using Distributions
 

test/nn.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 using StatsFuns
 
 @testset "conv2d_transpose" begin
@@ -17,7 +17,7 @@ end
 
 
 @testset "Cross Entropy Loss" begin
-    srand(1)
+    Random.seed!(1)
     let
         sess = Session(Graph())
         targets = constant(collect(1:10))

test/ops.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 
 @testset "Importing" begin

test/run.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 using TensorFlow
 
 @testset "Placeholder Size Matching" begin
@@ -37,7 +37,7 @@ using TensorFlow
 end
 
 @testset begin
-    srand(1)
+    Random.seed!(1)
     data = rand(Int64.(1:10), 3,4)
     sess = Session(Graph())
 

test/runtests.jl

@@ -1,7 +1,7 @@
 using TensorFlow
-using Base.Test
+using Test
 
-srand(0)  # Make tests deterministic
+Random.seed!(0)  # Make tests deterministic
 
 include(joinpath(dirname(@__FILE__), "..", "examples", "logistic.jl"))
 

test/sequences.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 sess = Session(Graph())
 
@@ -12,7 +12,7 @@ sess = Session(Graph())
         x = random_normal(shape, dtype=dtype)
         @test get_shape(x) == TensorShape(shape)
         result = run(sess, x)
-        @test size(result) == (shape...)
+        @test size(result) == (shape...,)
         @test eltype(result) == dtype
     end
 end

test/shape_inference.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 k = placeholder(Float32; shape=[10, 20, -1])
 m = placeholder(Float32; shape=[10, 20, 30])
@@ -56,9 +56,9 @@ end
 end
 
 @testset "Find (i.e Where)" begin
-    @test get_shape(find(placeholder(Bool; shape=[10, 20, 30]))) == TensorShape([-1,3])
-    @test get_shape(find(placeholder(Bool; shape=[10, 20, -1]))) == TensorShape([-1,3])
-    @test get_shape(find(placeholder(Bool))) == TensorShape(nothing)
+    @test get_shape(findall(placeholder(Bool; shape=[10, 20, 30]))) == TensorShape([-1,3])
+    @test get_shape(findall(placeholder(Bool; shape=[10, 20, -1]))) == TensorShape([-1,3])
+    @test get_shape(findall(placeholder(Bool))) == TensorShape(nothing)
 end
 
 @testset "Stack/Unstack" begin
@@ -92,7 +92,7 @@ end
 
 
 @testset "ArgMinMax" begin
-    @testset "$f" for f in (indmin, indmax, Ops.arg_min, Ops.arg_max)
+    @testset "$f" for f in (argmin, argmax, Ops.arg_min, Ops.arg_max)
         @test get_shape(f(k, 1)) == TensorShape([20, -1])
         @test get_shape(f(k, 2)) == TensorShape([10, -1])
         @test get_shape(f(k, 3)) == TensorShape([10, 20])
@@ -180,8 +180,8 @@ end
         (m, i, nothing)
         ]
         # test commutativeness
-        @test get_shape(select(c, a1, a2)) == TensorShape(r)
-        @test get_shape(select(c, a2, a1)) == TensorShape(r)
+        @test get_shape(partialsort(c, a1, a2)) == TensorShape(r)
+        @test get_shape(partialsort(c, a2, a1)) == TensorShape(r)
     end
 end
 

test/show.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 @testset "Tensorboard" begin
     TensorFlow.get_tensorboard()

test/summary.jl

@@ -1,6 +1,6 @@
 using TensorFlow
 const tf = TensorFlow
-using Base.Test
+using Test
 
 graph = Graph()
 sess = Session(graph)

test/train.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 @testset "save and resore" begin
     try

test/training.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 using TensorFlow
 
 @testset "Training with 'gather' nodes" begin

test/transformations.jl

@@ -1,5 +1,5 @@
 using TensorFlow
-using Base.Test
+using Test
 
 
 sess = TensorFlow.Session(TensorFlow.Graph())
@@ -149,7 +149,7 @@ end
 # Tests after this point must provide their own sessions and graphs
 
 @testset "Concatenation Syntax" begin
-    srand(37)
+    Random.seed!(37)
     sess4 = Session(Graph())
 
     a_jl = rand(10,5); a = constant(a_jl);