Merge pull request pfnet-research#159 from durswd/format

apply format
Rishav1 · Apr 13, 2019 · dd2bc00 · dd2bc00
2 parents 601f4d8 + 32185db
commit dd2bc00
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Showing 15 changed files with 426 additions and 235 deletions.
diff --git a/elichika/elichika/chainer2onnx.py b/elichika/elichika/chainer2onnx.py
@@ -24,12 +24,14 @@
 import elichika.layers_buikdin as lb
 import elichika.functions_buildin as fb
 
+
 class ONNXModel:
     def __init__(self):
         self.model = None
         self.inputs = []
         self.outputs = []
 
+
 def compile_model(model, inputs) -> 'ONNXModel':
 
     oc.chainer_f_converter.clear()
@@ -56,21 +58,23 @@ def compile_model(model, inputs) -> 'ONNXModel':
     oc.preprocess(graph_, True)
 
     generator = oc.ONNXGenerator()
-    model = generator.generate_model(graph_.input_values, graph_.output_values, graph_, model)
+    model = generator.generate_model(
+        graph_.input_values, graph_.output_values, graph_, model)
 
     # check inputs
 
-
     onnx_model = ONNXModel()
     onnx_model.model = model
     onnx_model.inputs = graph_.input_values
     onnx_model.outputs = graph_.output_values
     return onnx_model
 
-def save_model(path : 'str', model : 'ModelProto'):
+
+def save_model(path: 'str', model: 'ModelProto'):
     with open(path, "wb") as f:
         f.write(model.SerializeToString())
 
-def save_model_as_text(path : 'str', model : 'ModelProto'):
+
+def save_model_as_text(path: 'str', model: 'ModelProto'):
     with open(path, "w") as f:
         print(model, file=f)
diff --git a/elichika/elichika/functions_buildin.py b/elichika/elichika/functions_buildin.py
@@ -22,19 +22,22 @@
 
 import elichika.onnx_converters as oc
 
+
 def convert_relu(onnx_graph, node):
-    onnx_graph.add_node('Relu', 
-        [node.inputs[0]],
-        [node.outputs[0]],
-        name = str(node.lineprop))
+    onnx_graph.add_node('Relu',
+                        [node.inputs[0]],
+                        [node.outputs[0]],
+                        name=str(node.lineprop))
+
 
 def convert_softmax(onnx_graph, node):
     onnx_graph.add_node(
         "Softmax",
         [node.inputs[0]],
         [node.outputs[0]],
         str(node.lineprop),
-        axis = oc.try_get_attribute(node.inputs[1]))
+        axis=oc.try_get_attribute(node.inputs[1]))
+
 
 def convert_pad_sequence(onnx_graph, node):
     kwargs = {}
@@ -55,6 +58,7 @@ def convert_pad_sequence(onnx_graph, node):
         str(node.lineprop),
         **kwargs)
 
+
 def convert_softmax_cross_entropy(onnx_graph, node):
 
     onnx_graph.add_node(

diff --git a/elichika/elichika/layers_buikdin.py b/elichika/elichika/layers_buikdin.py
@@ -22,8 +22,9 @@
 
 import elichika.onnx_converters as oc
 
-def convert_onnx_chainer_linear(onnx_graph : 'ONNXGraph', node : 'nodes.Node'):
-    chainer_inst = node.func.owner.inst # type: chainer.links.Linear
+
+def convert_onnx_chainer_linear(onnx_graph: 'ONNXGraph', node: 'nodes.Node'):
+    chainer_inst = node.func.owner.inst  # type: chainer.links.Linear
     onnx_name = oc.node2onnx_parameter[node].onnx_name
 
     x = oc.ONNXValue(onnx_graph, node.inputs[0])
@@ -42,7 +43,8 @@ def convert_onnx_chainer_linear(onnx_graph : 'ONNXGraph', node : 'nodes.Node'):
 
     (batch_size_1,) = onnx_graph.add_node(
         'Gather',
-        [x_shape, oc.ONNXValue(onnx_graph, np.array(0, dtype=np.int64), [onnx_name, '/Zero'])],
+        [x_shape, oc.ONNXValue(onnx_graph, np.array(
+            0, dtype=np.int64), [onnx_name, '/Zero'])],
         [None],
         str(node.lineprop))
 
@@ -55,7 +57,8 @@ def convert_onnx_chainer_linear(onnx_graph : 'ONNXGraph', node : 'nodes.Node'):
 
     (mat_shape,) = onnx_graph.add_node(
         'Concat',
-        [batch_size_2, oc.ONNXValue(onnx_graph, np.array([-1], dtype=np.int64), [onnx_name, '/Minus1'])],
+        [batch_size_2, oc.ONNXValue(onnx_graph, np.array(
+            [-1], dtype=np.int64), [onnx_name, '/Minus1'])],
         [None],
         str(node.lineprop),
         axis=0)
@@ -92,8 +95,9 @@ def convert_onnx_chainer_linear(onnx_graph : 'ONNXGraph', node : 'nodes.Node'):
             [o],
             str(node.lineprop))
 
-def convert_onnx_chainer_convolution2d(onnx_graph : 'ONNXGraph', node : 'nodes.Node'):
-    chainer_inst = node.func.owner.inst # type: chainer.links.Convolution2D
+
+def convert_onnx_chainer_convolution2d(onnx_graph: 'ONNXGraph', node: 'nodes.Node'):
+    chainer_inst = node.func.owner.inst  # type: chainer.links.Convolution2D
     onnx_name = oc.node2onnx_parameter[node].onnx_name
 
     ksize = oc.size2d(chainer_inst.ksize)