diff --git a/onnxruntime/core/graph/contrib_ops/contrib_defs.cc b/onnxruntime/core/graph/contrib_ops/contrib_defs.cc index 58d585e3c1..0d5b89b1f3 100644 --- a/onnxruntime/core/graph/contrib_ops/contrib_defs.cc +++ b/onnxruntime/core/graph/contrib_ops/contrib_defs.cc @@ -32,63 +32,6 @@ void RegisterContribSchemas() { Sample echo operator.)DOC"); // register schemas for more operators here - ONNX_CONTRIB_OPERATOR_SCHEMA(ConvMaxPool) - .SetDomain(kMSDomain) - .SinceVersion(1) - .SetDoc(R"DOC( - Port Conv1D::ComputeConvMaxPoolWithActivationAndMask() method in TP3L1 c++ model.)DOC") - .Attr( - "auto_pad", - "", - AttributeProto::STRING, - std::string("NOTSET")) - .Attr( - "kernel_shape", - "", - AttributeProto::INTS, - OPTIONAL) - .Attr( - "dilations", - "", - AttributeProto::INTS, - OPTIONAL) - .Attr( - "strides", "", AttributeProto::INTS, OPTIONAL) - .Attr("pads", - "", - AttributeProto::INTS, OPTIONAL) - .Attr( - "group", - "", - AttributeProto::INT, - static_cast(1)) - .Attr( - "activation", - "", - AttributeProto::STRING, - OPTIONAL) - .Input( - 0, - "X", - "", - "T") - .Input( - 1, - "W", - "", - "T") - .Input(2, "B", "", "T", OpSchema::Optional) - .Input(3, "M", "mask", "T", OpSchema::Optional) - .Output( - 0, - "Y", - "", - "T") - .TypeConstraint("T", {"tensor(float16)", "tensor(float)", "tensor(double)"}, "Constrain input and output types to float tensors") - .TypeAndShapeInferenceFunction([](ONNX_NAMESPACE::InferenceContext& ctx) { - ONNX_NAMESPACE::convPoolTypeAndShapeInference(ctx, false, true); - }); - ONNX_CONTRIB_OPERATOR_SCHEMA(FusedConv) .SetDomain(kMSDomain) .SinceVersion(1) @@ -125,11 +68,6 @@ activation.)DOC") "", AttributeProto::STRING, OPTIONAL) - .Attr( - "alpha", - "", - AttributeProto::FLOAT, - OPTIONAL) .Input( 0, "X",