=allow passing in the gradient for y #212

src/core.jl

@@ -1370,16 +1370,19 @@ Base.haskey(graph::Graph, name) = isnull(get_node_by_name(graph, name))
 
 
 
-node_name(xs::AbstractVector) = node_name.(xs)
+node_name(::Void) = nothing
+node_name(xs::AbstractVector)=node_name.(xs)
 
-function gradients(y, x::AbstractArray)
+
+function gradients(y, x::AbstractArray, grad_y=nothing)
     x_names = node_name(x)
     y_names = node_name(y)
+    grad_y_names = node_name(grad_y)
     meta_graph = train.export_meta_graph()
     b = IOBuffer()
     writeproto(b, meta_graph)
     graph_proto = @compat take!(b)
-    node_protos, grad_names = @py_proc py_gradients($graph_proto, $x_names, $y_names)
+    node_protos, grad_names = @py_proc py_gradients($graph_proto, $x_names, $y_names, $grad_y_names)
     extend_graph(node_protos)
     out = []
     for name in grad_names
@@ -1394,7 +1397,7 @@ function gradients(y, x::AbstractArray)
     return out
 end
 
-gradients(y, x) = gradients(y, [x])[1]
+gradients(y, x, grad_y=nothing) = gradients(y, [x], grad_y)[1]
 
 function get_num_outputs(op::Operation)
     @tfcall(:TF_OperationNumOutputs, Cint, (Ptr{Void},), op.ptr) |> Int

src/py.jl

@@ -70,16 +70,17 @@ function to_protos(py_graph)
     return protos
 end
 
-function py_gradients(jl_graph_proto, x_names, y_names)
+function py_gradients(jl_graph_proto, x_names, y_names, grad_y_names)
     py_graph = make_py_graph(jl_graph_proto)
 
     to_py_node(node_name) = py_graph[:get_tensor_by_name](string(node_name[1], ":", node_name[2]-1))
     to_py_node(node_names::AbstractVector) = to_py_node.(node_names) # Boardcast via dispatch
+    to_py_node(::Void) = nothing
 
     py_x = to_py_node(x_names)
     py_y = to_py_node(y_names)
-
-    @py_catch grad_node = py_tf[][:gradients](py_y, py_x)
+    py_grad_y = to_py_node(grad_y_names)
+    @py_catch grad_node = py_tf[][:gradients](py_y, py_x, py_grad_y)
     grad_names = []
     for node in grad_node
         if node === nothing

test/core.jl

@@ -1,26 +1,6 @@
 using Base.Test
 using TensorFlow
 
-@testset "Gradients" begin
-    let
-        sess = Session(Graph())
-        A = get_variable("A", (1,), Float32)
-        B = get_variable("B", (1,), Float32)
-
-        @test [[2.0f0]] == run(sess, gradients(2A, [A]))
-        @test [2.0f0] == run(sess, gradients(2A, A))
-
-        @test [[3.0f0], [5.0f0]] == run(sess, gradients(3A+5B, [A, B]))
-        @test [[8.0f0]] == run(sess, gradients([3A, 5A], [A]))
-
-        @test [[9.0f0], [3.0f0]] == run(sess, gradients([2A+3B, 7A], [A, B]))
-
-        @test [35.0f0] == run(sess, gradients(7A, A, 14))
-
-    end
-
-end
-
 @testset "Graph importing" begin
     if tf_version() >= v"1.0.0-rc1"
         graph_pb = read(joinpath(dirname(@__FILE__), "graph.pb"))
@@ -118,3 +98,23 @@ end
 end
 
 
+@testset "Gradients" begin
+    let
+        sess = Session(Graph())
+        A = get_variable("A", (1,), Float32)
+        B = get_variable("B", (1,), Float32)
+
+        @test [[2.0f0]] == run(sess, gradients(2A, [A]))
+        @test [2.0f0] == run(sess, gradients(2A, A))
+
+        @test [[3.0f0], [5.0f0]] == run(sess, gradients(3A+5B, [A, B]))
+        @test [[8.0f0]] == run(sess, gradients([3A, 5A], [A]))
+
+        @test [[9.0f0], [3.0f0]] == run(sess, gradients([2A+3B, 7A], [A, B]))
+
+        @test [35.0f0] == run(sess, gradients(7A, A, constant([5.0f0])))
+
+    end
+
+end
+