nudles commented on a change in pull request #416: singa-onnx
URL: https://github.com/apache/incubator-singa/pull/416#discussion_r264084037
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File path: python/singa/sonnx.py
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@@ -257,24 +255,28 @@ def to_onnx_model(inputs, y, model_name='sonnx'):
the onnx model
'''
node = []
- inputsx=inputs
dependency = autograd.infer_dependency(y.creator)
ready = deque([y.creator])
- def output_name(op, index):
- return '{}:{}'.format(op.name, index)
+ def output_name(op):
+ return '{}'.format(op.name)
input_ids = set(id(x) for x in inputs)
X = []
+ for x in inputs:
+ dtype = TensorProto.FLOAT
+ if y.dtype == tensor.int32:
+ dtype = TensorProto.INT
+ X.append(helper.make_tensor_value_info(x.name, dtype, x.shape))
Y = [helper.make_tensor_value_info(
- output_name(y.creator, 0), TensorProto.FLOAT, y.shape)]
+ output_name(y.creator), TensorProto.FLOAT, y.shape)]
while len(ready) > 0:
op = ready.pop()
assert not isinstance(op, autograd.Dummy)
- outputs = [output_name(op, idx)
+ outputs = [output_name(op)
Review comment:
if there are multiple outputs, then they all would have the same name.
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