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Rename OX->ORT #31

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Sep 23, 2023
Merged

Rename OX->ORT #31

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69f2929
rename OX->ORT
jw3126 Sep 23, 2023
f7b7c0f
Merge branch 'main' into up
jw3126 Sep 23, 2023
e0bb88b
bump version
jw3126 Sep 23, 2023
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "ONNXRunTime"
uuid = "e034b28e-924e-41b2-b98f-d2bbeb830c6a"
authors = ["Jan Weidner <[email protected]> and contributors"]
version = "0.3.2"
version = "0.3.3"

[deps]
ArgCheck = "dce04be8-c92d-5529-be00-80e4d2c0e197"
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8 changes: 4 additions & 4 deletions README.md
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Expand Up @@ -14,11 +14,11 @@ Contributions are welcome.
The high level API works as follows:
```julia

julia> import ONNXRunTime as OX
julia> import ONNXRunTime as ORT

julia> path = OX.testdatapath("increment2x3.onnx"); # path to a toy model
julia> path = ORT.testdatapath("increment2x3.onnx"); # path to a toy model

julia> model = OX.load_inference(path);
julia> model = ORT.load_inference(path);

julia> input = Dict("input" => randn(Float32,2,3))
Dict{String, Matrix{Float32}} with 1 entry:
Expand All @@ -34,7 +34,7 @@ pkg> add CUDA

julia> import CUDA

julia> OX.load_inference(path, execution_provider=:cuda)
julia> ORT.load_inference(path, execution_provider=:cuda)
```

The low level API mirrors the offical [C-API](https://github.com/microsoft/onnxruntime/blob/v1.8.1/include/onnxruntime/core/session/onnxruntime_c_api.h#L347). The above example looks like this:
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14 changes: 7 additions & 7 deletions test/test_capi.jl
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Original file line number Diff line number Diff line change
@@ -1,13 +1,13 @@
module TestCAPI
using Test
using ONNXRunTime.CAPI
import ONNXRunTime as OX
import ONNXRunTime as ORT

@testset "Session" begin
@testset "increment2x3" begin
api = GetApi()
env = CreateEnv(api, name="myenv")
path = OX.testdatapath("increment2x3.onnx")
path = ORT.testdatapath("increment2x3.onnx")
session_options = CreateSessionOptions(api)
@test (sprint(show, session_options); true)
@test_throws Exception CreateSession(api, env, "does_not_exits.onnx", session_options)
Expand All @@ -20,9 +20,9 @@ import ONNXRunTime as OX
allocator = CreateAllocator(api, session, mem)
@test (sprint(show, allocator); true)
@test SessionGetInputName(api, session, 0, allocator) == "input"
@test_throws OX.OrtException SessionGetInputName(api, session, 1, allocator)
@test_throws ORT.OrtException SessionGetInputName(api, session, 1, allocator)
@test SessionGetOutputName(api, session, 0, allocator) == "output"
@test_throws OX.OrtException SessionGetOutputName(api, session, 1, allocator)
@test_throws ORT.OrtException SessionGetOutputName(api, session, 1, allocator)
input_vec = randn(Float32, 6)
input_array = [
input_vec[1] input_vec[2] input_vec[3];
Expand All @@ -46,7 +46,7 @@ import ONNXRunTime as OX
@testset "increment2x3 ModelMetadata" begin
api = GetApi()
env = CreateEnv(api, name="myenv")
path = OX.testdatapath("increment2x3.onnx")
path = ORT.testdatapath("increment2x3.onnx")
session_options = CreateSessionOptions(api)
@test (sprint(show, session_options); true)
@test_throws Exception CreateSession(api, env, "does_not_exits.onnx", session_options)
Expand All @@ -67,12 +67,12 @@ end
api = GetApi()
mem = CreateCpuMemoryInfo(api)
data = randn(2,3)
tensor = CreateTensorWithDataAsOrtValue(api, mem, vec(OX.reversedims(data)), size(data))
tensor = CreateTensorWithDataAsOrtValue(api, mem, vec(ORT.reversedims(data)), size(data))
@test IsTensor(api, tensor)
info = GetTensorTypeAndShape(api, tensor)
onnxelty = GetTensorElementType(api, info)
@test onnxelty isa ONNXTensorElementDataType
@test OX.juliatype(onnxelty) == eltype(data)
@test ORT.juliatype(onnxelty) == eltype(data)
@test GetDimensionsCount(api, info) == 2
@test GetDimensions(api, info) == [2,3]
data2 = GetTensorMutableData(api, tensor)
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14 changes: 7 additions & 7 deletions test/test_cuda.jl
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Expand Up @@ -2,18 +2,18 @@ module TestCUDA
import CUDA
using Test
using ONNXRunTime
const OX = ONNXRunTime
const ORT = ONNXRunTime
using ONNXRunTime: SessionOptionsAppendExecutionProvider_CUDA

#using Libdl
#Libdl.dlopen("/home/jan/.julia/artifacts/e2fd6cdf04b830a1d802fb35a6193788d0a3811a/lib/libcudart.so.11.0")

@testset "CUDA high level" begin
@testset "increment2x3.onnx" begin
path = OX.testdatapath("increment2x3.onnx")
model = OX.load_inference(path, execution_provider=:cuda)
@test OX.input_names(model) == ["input"]
@test OX.output_names(model) == ["output"]
path = ORT.testdatapath("increment2x3.onnx")
model = ORT.load_inference(path, execution_provider=:cuda)
@test ORT.input_names(model) == ["input"]
@test ORT.output_names(model) == ["output"]
input = randn(Float32, 2,3)
y = model((;input=input,), ["output"])
@test y == (output=input .+ 1f0,)
Expand All @@ -34,9 +34,9 @@ using ONNXRunTime.CAPI
mem = CreateCpuMemoryInfo(api)
allocator = CreateAllocator(api, session, mem)
@test SessionGetInputName(api, session, 0, allocator) == "input"
@test_throws OX.OrtException SessionGetInputName(api, session, 1, allocator)
@test_throws ORT.OrtException SessionGetInputName(api, session, 1, allocator)
@test SessionGetOutputName(api, session, 0, allocator) == "output"
@test_throws OX.OrtException SessionGetOutputName(api, session, 1, allocator)
@test_throws ORT.OrtException SessionGetOutputName(api, session, 1, allocator)
input_vec = randn(Float32, 6)
input_array = [
input_vec[1] input_vec[2] input_vec[3];
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84 changes: 42 additions & 42 deletions test/test_highlevel.jl
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Expand Up @@ -2,57 +2,57 @@ module TestHighlevel

using Test
using ONNXRunTime
const OX = ONNXRunTime
const ORT = ONNXRunTime
using ONNXRunTime: juliatype

@testset "high level" begin
@testset "increment2x3.onnx" begin
path = OX.testdatapath("increment2x3.onnx")
model = OX.load_inference(path, execution_provider=:cpu)
@test OX.input_names(model) == ["input"]
@test OX.output_names(model) == ["output"]
@test OX.input_names(model) === model.input_names
@test OX.output_names(model) === model.output_names
path = ORT.testdatapath("increment2x3.onnx")
model = ORT.load_inference(path, execution_provider=:cpu)
@test ORT.input_names(model) == ["input"]
@test ORT.output_names(model) == ["output"]
@test ORT.input_names(model) === model.input_names
@test ORT.output_names(model) === model.output_names
input = randn(Float32, 2,3)
#= this works =# model(Dict("input" => randn(Float32, 2,3)), ["output"])
@test_throws OX.ArgumentError model(Dict("nonsense" => input), ["output"])
@test_throws OX.ArgumentError model(Dict("input" => input), ["nonsense"])
@test_throws OX.OrtException model(Dict("input" => input), String[])
@test_throws OX.ArgumentError model(Dict("input" => input, "unused"=>input), ["output"])
@test_throws OX.ArgumentError model(Dict("input" => input, "unused"=>input), ["output"])
@test_throws OX.OrtException model(Dict("input" => randn(Float32, 3,2)), ["output"])
@test_throws ORT.ArgumentError model(Dict("nonsense" => input), ["output"])
@test_throws ORT.ArgumentError model(Dict("input" => input), ["nonsense"])
@test_throws ORT.OrtException model(Dict("input" => input), String[])
@test_throws ORT.ArgumentError model(Dict("input" => input, "unused"=>input), ["output"])
@test_throws ORT.ArgumentError model(Dict("input" => input, "unused"=>input), ["output"])
@test_throws ORT.OrtException model(Dict("input" => randn(Float32, 3,2)), ["output"])
@test_throws Exception model(Dict("input" => randn(Int, 2,3) ), ["output"])
@test_throws OX.OrtException model(Dict("input" => randn(Float64, 2,3)), ["output"])
@test_throws ORT.OrtException model(Dict("input" => randn(Float64, 2,3)), ["output"])
y = model(Dict("input" => input), ["output"])
@test y == Dict("output" => input .+ 1f0)
y = model(Dict("input" => input))
@test y == Dict("output" => input .+ 1f0)
end
@testset "adder1x2x3.onnx" begin
path = OX.testdatapath("adder1x2x3.onnx")
model = OX.load_inference(path)
@test OX.input_names(model) == ["x", "y"]
@test OX.output_names(model) == ["sum"]
path = ORT.testdatapath("adder1x2x3.onnx")
model = ORT.load_inference(path)
@test ORT.input_names(model) == ["x", "y"]
@test ORT.output_names(model) == ["sum"]
x = randn(Float32, 1,2,3)
y = randn(Float32, 1,2,3)
d = model(Dict("x" => x, "y"=>y))
@test d isa AbstractDict
@test d == Dict("sum" => x+y)
end
@testset "diagonal1x2x3x4.onnx" begin
path = OX.testdatapath("diagonal1x2x3x4.onnx")
model = OX.load_inference(path)
@test OX.input_names(model) == ["in"]
@test OX.output_names(model) == ["out1", "out2"]
path = ORT.testdatapath("diagonal1x2x3x4.onnx")
model = ORT.load_inference(path)
@test ORT.input_names(model) == ["in"]
@test ORT.output_names(model) == ["out1", "out2"]
x = randn(Float64, 1,2,3,4)
d = model(Dict("in" => x))
@test d == Dict("out1" => x, "out2" => x)
end
@testset "swap_x_.onnx" begin
path = OX.testdatapath("swap_x_.onnx")
model = OX.load_inference(path)
@test OX.input_names(model) == ["in1", "in2"]
@test OX.output_names(model) == ["out1", "out2"]
path = ORT.testdatapath("swap_x_.onnx")
model = ORT.load_inference(path)
@test ORT.input_names(model) == ["in1", "in2"]
@test ORT.output_names(model) == ["out1", "out2"]
in1 = randn(Float32, 2,3)
in2 = randn(Float32, 4,5)
res = model((;in1, in2))
Expand All @@ -68,22 +68,22 @@ using ONNXRunTime: juliatype
@test occursin("out2", s)
end
@testset "getindex_12.onnx" begin
path = OX.testdatapath("getindex_12.onnx")
model = OX.load_inference(path)
path = ORT.testdatapath("getindex_12.onnx")
model = ORT.load_inference(path)
inputs = (input=collect(reshape(1f0:20, 4,5)),)
out = model(inputs).output
@test inputs.input[2,3] == only(out)
end
@testset "copy2d.onnx" begin
path = OX.testdatapath("copy2d.onnx")
model = OX.load_inference(path)
path = ORT.testdatapath("copy2d.onnx")
model = ORT.load_inference(path)
inputs = (input=randn(Float32,3,4),)
out = model(inputs).output
@test inputs.input == out
end
@testset "matmul.onnx" begin
path = OX.testdatapath("matmul.onnx")
model = OX.load_inference(path)
path = ORT.testdatapath("matmul.onnx")
model = ORT.load_inference(path)
inputs = (
input1 = randn(Float32, 2,3),
input2 = randn(Float32, 3,4),
Expand All @@ -92,8 +92,8 @@ using ONNXRunTime: juliatype
@test out ≈ inputs.input1 * inputs.input2
end
@testset "xyz_3x4x5.onnx" begin
path = OX.testdatapath("xyz_3x4x5.onnx")
model = OX.load_inference(path)
path = ORT.testdatapath("xyz_3x4x5.onnx")
model = ORT.load_inference(path)
inputs = (input=randn(Float32,4,10),)
out = model(inputs)
@test out.identity == inputs.input
Expand All @@ -108,17 +108,17 @@ using ONNXRunTime: juliatype
end
end
@testset "Conv1d1.onnx" begin
path = OX.testdatapath("Conv1d1.onnx")
model = OX.load_inference(path)
path = ORT.testdatapath("Conv1d1.onnx")
model = ORT.load_inference(path)
inputs = (input=randn(Float32,4,2,10),)
out = model(inputs)
expected = fill(0f0, 4,3,8)
expected[:,2,:] .= 1
@test out.output == expected
end
@testset "Conv1d2.onnx" begin
path = OX.testdatapath("Conv1d2.onnx")
model = OX.load_inference(path)
path = ORT.testdatapath("Conv1d2.onnx")
model = ORT.load_inference(path)
input = Array{Float32,3}(undef, (1,2,3))
input[1,1,1] = 1
input[1,1,2] = 2
Expand All @@ -136,10 +136,10 @@ using ONNXRunTime: juliatype
@test out[1,2,3] == 0
end
@testset "Dict2Dict.onnx" begin
path = OX.testdatapath("Dict2Dict.onnx")
model = OX.load_inference(path, execution_provider=:cpu)
@test OX.input_names(model) == ["x", "y"]
@test OX.output_names(model) == ["x_times_y", "x_plus_y", "x_minus_y", "x_plus_1", "y_plus_2"]
path = ORT.testdatapath("Dict2Dict.onnx")
model = ORT.load_inference(path, execution_provider=:cpu)
@test ORT.input_names(model) == ["x", "y"]
@test ORT.output_names(model) == ["x_times_y", "x_plus_y", "x_minus_y", "x_plus_1", "y_plus_2"]
nb = rand(1:10)
x = randn(Float32, nb,3)
y = randn(Float32, nb,3)
Expand Down