Fix to accept chainer.Variable collection input

onnx_chainer/export.py

@@ -209,13 +209,13 @@ def export(model, args, filename=None, export_params=True,
         for i, arg in enumerate(args):
             if isinstance(arg, numpy.ndarray):
                 args[i] = chainer.Variable(arg)
-                network_inputs.append(args[i])
+            network_inputs.append(args[i])
         outputs = model(*args)
     elif isinstance(args, dict):
         for key, arg in args.items():
             if isinstance(arg, numpy.ndarray):
                 args[key] = chainer.Variable(arg)
-                network_inputs.append(args[key])
+            network_inputs.append(args[key])
         outputs = model(**args)
     elif isinstance(args, numpy.ndarray):
         args = chainer.Variable(args)

onnx_chainer/testing/test_onnxruntime.py

@@ -33,19 +33,24 @@ def check_output(model, x, fn, out_key='prob', opset_version=None):
         for i in x:
             assert isinstance(i, (np.ndarray, chainer.Variable))
         chainer_out = model(*x)
-        x = tuple(
+        x_rt = tuple(
             _x.array if isinstance(_x, chainer.Variable) else _x for _x in x)
+    elif isinstance(x, dict):
+        chainer_out = model(**x)
+        x_rt = tuple(_x.array if isinstance(_x, chainer.Variable) else _x
+                     for _, _x in x.items())
     elif isinstance(x, np.ndarray):
         chainer_out = model(chainer.Variable(x))
-        x = (x,)
+        x_rt = x,
     elif isinstance(x, chainer.Variable):
         chainer_out = model(x)
-        x = (x.array,)
+        x_rt = x.array,
     else:
         raise ValueError(
-            'The \'x\' argument should be a list or tuple of numpy.ndarray or '
-            'chainer.Variable, or simply a numpy.ndarray or a chainer.Variable'
-            ' itself. But a {} object was given.'.format(type(x)))
+            'The \'x\' argument should be a list, tuple or dict of '
+            'numpy.ndarray or chainer.Variable, or simply a numpy.ndarray or a'
+            ' chainer.Variable itself. But a {} object was given.'.format(
+                type(x)))
 
     if isinstance(chainer_out, (list, tuple)):
         chainer_out = (y.array for y in chainer_out)
@@ -74,7 +79,7 @@ def check_output(model, x, fn, out_key='prob', opset_version=None):
     assert input_names == list(sorted(graph_input_names))
 
     rt_out = sess.run(
-        None, {name: array for name, array in zip(input_names, x)})
+        None, {name: array for name, array in zip(input_names, x_rt)})
 
     for cy, my in zip(chainer_out, rt_out):
         np.testing.assert_almost_equal(cy, my, decimal=5)

tests/test_inout.py

@@ -0,0 +1,47 @@
+import unittest
+
+import chainer
+import chainer.functions as F
+import chainer.links as L
+import numpy as np
+
+from onnx_chainer.testing import test_onnxruntime
+
+
+class TestMultipleInputs(unittest.TestCase):
+
+    def setUp(self):
+
+        class Model(chainer.Chain):
+
+            def __init__(self):
+                super(Model, self).__init__()
+                with self.init_scope():
+                    self.prelu = L.PReLU()
+
+            def __call__(self, x, y, z):
+                return F.relu(x) + self.prelu(y) * z
+
+        self.model = Model()
+        self.ins = (np.zeros((1, 5), dtype=np.float32),
+                    np.zeros((1, 5), dtype=np.float32),
+                    np.zeros((1, 5), dtype=np.float32))
+        self.fn = 'MultiInputs.onnx'
+
+    def test_arrays(self):
+        test_onnxruntime.check_output(self.model, self.ins, self.fn)
+
+    def test_variables(self):
+        ins = [chainer.Variable(i) for i in self.ins]
+        test_onnxruntime.check_output(self.model, ins, self.fn)
+
+    def test_array_dicts(self):
+        arg_names = ['x', 'y', 'z']  # current exporter ignores these names
+        ins = {arg_names[i]: v for i, v in enumerate(self.ins)}
+        test_onnxruntime.check_output(self.model, ins, self.fn)
+
+    def test_variable_dicts(self):
+        arg_names = ['x', 'y', 'z']  # current exporter ignores these names
+        ins = {arg_names[i]: chainer.Variable(v)
+               for i, v in enumerate(self.ins)}
+        test_onnxruntime.check_output(self.model, ins, self.fn)