onnx-array-api: (Numpy) Array API for ONNX

importnumpyasnpfromonnx_array_api.npximportabsolute,jit_onnxfromonnx_array_api.plotting.text_plotimportonnx_simple_text_plotdefl1_loss(x,y):returnabsolute(x-y).sum()defl2_loss(x,y):return ((x-y)**2).sum()defmyloss(x,y):returnl1_loss(x[:,0],y[:,0])+l2_loss(x[:,1],y[:,1])jitted_myloss=jit_onnx(myloss)x=np.array([[0.1,0.2], [0.3,0.4]],dtype=np.float32)y=np.array([[0.11,0.22], [0.33,0.44]],dtype=np.float32)res=jitted_myloss(x,y)print(res)print(onnx_simple_text_plot(jitted_myloss.get_onnx()))

importnumpyasnpfromonnx_array_api.npximportabsolute,eager_onnxdefl1_loss(x,y):err=absolute(x-y).sum()print(f"l1_loss={err.numpy()}")returnerrdefl2_loss(x,y):err= ((x-y)**2).sum()print(f"l2_loss={err.numpy()}")returnerrdefmyloss(x,y):returnl1_loss(x[:,0],y[:,0])+l2_loss(x[:,1],y[:,1])eager_myloss=eager_onnx(myloss)x=np.array([[0.1,0.2], [0.3,0.4]],dtype=np.float32)y=np.array([[0.11,0.22], [0.33,0.44]],dtype=np.float32)res=eager_myloss(x,y)print(res)