Add missing check when deciding conv op and injective op are in the s…

…ame group (apache#1622)

nnvm/src/compiler/graph_fuse.cc

@@ -146,6 +146,7 @@ nnvm::Graph GraphFindFusibleGroups(nnvm::Graph g) {
     bool parent_out_ewise = false;
     bool parent_injective = false;
     for (const auto& e : inode.inputs) {
+      if (fuse_vec[e.node_id] != FuseRule::kFuseToMaster) continue;
       TOpPattern pt = pattern_vec[e.node_id];
       if (pt == kOutEWiseFusable) {
         parent_out_ewise = true;

nnvm/tests/python/compiler/test_op_fusion.py

@@ -110,6 +110,39 @@ def test_injective_conv2d():
         np.testing.assert_allclose(out.asnumpy(), c_np, rtol=1e-5)
 
 
+def test_concatenate_conv2d():
+    ch = 3
+    size = 8
+    data = sym.Variable(name="data")
+    concat = sym.concatenate(data, data, axis=1)
+    conv = sym.conv2d(data=concat, kernel_size=(1,1), channels=ch*2, use_bias=False, name="conv")
+    net = sym.elemwise_add(concat, conv)
+
+    dtype="float32"
+    dshape = (1, ch, size, size)
+    kshape = (ch*2, ch*2, 1, 1)
+    oshape = (1, ch*2, size, size)
+    shape_dict = {"data": dshape}
+
+    for target, ctx in ctx_list():
+        graph, lib, _ = nnvm.compiler.build(net, target, shape_dict)
+        # data, conv weight, conv op, concat
+        assert graph.index.num_nodes == 4
+
+        data = tvm.nd.array(np.random.uniform(size=dshape).astype(dtype))
+        kernel = tvm.nd.array(np.random.uniform(size=kshape).astype(dtype))
+        m = graph_runtime.create(graph, lib, ctx)
+        m.run(data=data, conv_weight=kernel)
+        # get output
+        out = m.get_output(0, tvm.nd.empty(oshape, dtype))
+
+        concat = np.concatenate((data.asnumpy(), data.asnumpy()), axis=1)
+        conv = topi.testing.conv2d_nchw_python(
+            concat, kernel.asnumpy(), (1,1), 'SAME')
+        ref = concat + conv
+        np.testing.assert_allclose(out.asnumpy(), ref, rtol=1e-5)
+
+
 def build_and_run(sym, params, data, out_shape, target, ctx, opt_level=2):
     with nnvm.compiler.build_config(opt_level=opt_level):
         graph, lib, params = nnvm.compiler.build(sym, target, shape={"data":data.shape}, params=params)
@@ -157,3 +190,4 @@ def get_sym(out_channel):
     test_conv_ewise_injective()
     test_fuse_conv2d_elu()
     test_injective_conv2d()
+    test_concatenate_conv2d()