forked from mindspore-Ecosystem/mindspore
change printed log's level
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@ -235,7 +235,7 @@ void ProtoExporter::SetValueToProto(const ValuePtr &val, irpb::ValueProto *value
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value_proto->set_dtype(irpb::DT_TYPE);
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value_proto->mutable_type_val()->set_data_type(irpb::DT_BASE_COMPLEX);
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} else {
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MS_LOG(WARNING) << "Unsupported type " << val->type_name();
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MS_LOG(DEBUG) << "Unsupported type " << val->type_name();
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}
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}
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@ -471,7 +471,7 @@ void ProtoExporter::ExportCNode(const FuncGraphPtr &func_graph, const CNodePtr &
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// CNode/ConstGraph/Const/Parameter
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if (op->isa<CNode>() || IsValueNode<FuncGraph>(op) || op->isa<Parameter>()) {
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MS_LOG(WARNING) << "Operator must be a primitive";
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MS_LOG(DEBUG) << "Operator must be a primitive";
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} else {
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GetOpNodeTypeAndAttrs(func_graph, op, node_proto);
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node_proto->set_name(std::to_string(apply_idx));
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@ -17,6 +17,7 @@ import numpy as np
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import mindspore.context as context
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import mindspore.ops.composite as C
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from mindspore import Tensor, Parameter
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from mindspore import nn
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from mindspore.nn import Cell
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from mindspore.ops import operations as P
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@ -312,3 +313,23 @@ def test_pass_args_by_key_ward_way():
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grad_net = GradNet(net)
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sens = Tensor(np.ones((3, 3, 4), np.float32))
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grad_net(x, y=y, z=z, sens=sens)
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def test_none_input():
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"""
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Feature: Net's inputs
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Description: Support none input for the outermost net
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Expectation: no error
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"""
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class Net(Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.op = nn.ResizeBilinear()
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def construct(self, a, b, c, d):
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return self.op(a, b, c, d)
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x = Tensor(np.array([1, 2, 3, 4]).astype(np.float32).reshape((1, 1, 2, 2,)))
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net = Net()
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net(x, (4, 4), None, True)
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