ONNX Inference in Julia

ONNX.jl

julia> using ONNX, ONNX.Ghost

julia> dummy = rand(Float32, 78, 1);

julia> model = ONNX.load("./classifier_DF.onnx", dummy);

julia> x = range(0, Float32(0.5), length=78)
0.0f0:0.0064935065f0:0.5f0

julia> result = Ghost.play!(model, x)
1-element Vector{Float32}:
 0.99929035

onnxruntime.py

In [1]: import onnxruntime as onnx

In [2]: model = onnx.InferenceSession("./classifier_DF.onnx")

In [3]: input_name = model.get_inputs()[0].name

In [4]: input_name
Out[4]: 'dense_input'

In [5]: import numpy as np
  
In [26]: x = np.reshape(np.linspace(0, 0.5, 78, dtype=np.float32), (1, 78))

In [28]: result = model.run(None, {input_name: x})

In [29]: result
Out[29]: [array([[0.99929035]], dtype=float32)]