Gradient actually works

malmaud · Oct 23, 2017 · bf84a38 · bf84a38
1 parent 9fa6338
commit bf84a38
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Showing 2 changed files with 16 additions and 13 deletions.
diff --git a/src/core.jl b/src/core.jl
@@ -333,7 +333,7 @@ function get_collection end
     return g.collections[name]
 end
 
-const DEBUG_EXTEND_GRAPH = false
+const DEBUG_EXTEND_GRAPH = true
 
 function Base.convert(::Type{tensorflow.NodeDef}, proto::Vector{UInt8})
     b = IOBuffer()
@@ -351,14 +351,15 @@ end
     ph_names = Set{String}()
     for node_bytes in node_defs
         node_def = convert(tensorflow.NodeDef, node_bytes)
+        @show node_def
         if isnull(get_node_by_name(graph, node_def.name))
             # First try to directly add this node to the graph
-            try
-                new_op = Operation(node_def)
-                continue
-            catch err
-                DEBUG_EXTEND_GRAPH && warn(err)
-            end
+            # try
+            #     new_op = Operation(node_def)
+            #     continue
+            # catch err
+            #     DEBUG_EXTEND_GRAPH && warn(err)
+            # end
 
             # If that doesn't work (for example, the node has a
             # back edge), then import the node instead.

diff --git a/src/ops/control_flow.jl b/src/ops/control_flow.jl
@@ -248,7 +248,7 @@ Example using shape_invariants:
       shape_invariants=[i0.get_shape(), tensor_shape.TensorShape([None, 2])])
   ```
 """
-@op function while_loop(condition, body, variables; name=nothing, shape_invariants=nothing,
+@op function jl_while_loop(condition, body, variables; name=nothing, shape_invariants=nothing,
                         parallel_iterations=10, back_prop=true, swap_memory=false)
     g = Graph()
     def_graph = get_def_graph()
@@ -445,7 +445,8 @@ function WhileLoopOptions(;parallel_iterations=10, back_prop=true, swap_memory=f
     WhileLoopOptions(parallel_iterations, back_prop, swap_memory)
 end
 
-function c_while(condition, body, variables; name=nothing, options=WhileLoopOptions())
+function while_loop(condition, body, variables; name=nothing, options=WhileLoopOptions())
+    variables = Tensor.(variables)
     name === nothing && (name = "while")
     name = String(name)
     graph = get_def_graph()
@@ -485,7 +486,7 @@ function create_while_context(graph, name, n_inputs; options=WhileLoopOptions())
         loop_exit_names=String[])
     context_matcher = Regex("^$(name)/")
     for op in get_operations(graph)
-        @show op
+        # @show op
         if ismatch(context_matcher, get_def(op).name)
             def = get_def(op)
             n_outputs = length(get_op_def(def.op).output_arg)
@@ -494,18 +495,19 @@ function create_while_context(graph, name, n_inputs; options=WhileLoopOptions())
             end
         end
     end
-    push!(ctx.values_def.values, "$(name)/merge0:1")
-    push!(ctx.values_def.values, "$(name)/switch0:1")
+    # push!(ctx.values_def.values, "$(name)/merge0:1")
+    # push!(ctx.values_def.values, "$(name)/switch0:1")
     set_field!(ctx, :pivot_for_pred_name, "$(name)/merge0:0")
     switch_name = "$(name)/switch0"
     switch_op = get_node_by_name(switch_name) |> get |> get_def
     # We assume the pivot tensor is the second input to the switch statement.
-    # The first input is the result of the merge. 
+    # The first input is the result of the merge.
     cond_op = switch_op.input[2]
     set_field!(ctx, :pivot_for_body_name, "$(switch_name):0")
     set_field!(ctx, :pivot_name, "$(cond_op):0")
     for i in 1:n_inputs
         push!(ctx.loop_exit_names, "$(name)/exit$(i-1):0")
     end
+    # dump(ctx)
     return ctx
 end