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Commitd4771bf

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‎CHANGELOGS.rst‎

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@@ -4,6 +4,7 @@ Change Logs
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0.3.0
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+++++
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*:pr:`93`: fixes evaluator type in ``compare_onnx_execution``
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*:pr:`92`: avoids recursion errors in profiling
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*:pr:`87`: adds command line to replace contant by ConstantOfShape
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*:pr:`79`: first draft to export to GraphBuilder

‎_doc/index.rst‎

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@@ -187,5 +187,7 @@ to know onnx for that. See :ref:`l-numpy-api-onnx`.
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Older versions
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++++++++++++++
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* `0.3.0<../v0.3.0/index.html>`_
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* `0.2.0<../v0.2.0/index.html>`_
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* `0.1.3<../v0.1.3/index.html>`_
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* `0.1.2<../v0.1.2/index.html>`_

‎_unittests/ut_npx/test_npx.py‎

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@@ -208,7 +208,7 @@ def local1(
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returnx
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deflocal2(
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x:TensorType[ElemType.floats,"T"]
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x:TensorType[ElemType.floats,"T"],
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)->TensorType[ElemType.floats,"T"]:
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returnx
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‎onnx_array_api/__init__.py‎

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APIs to create ONNX Graphs.
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"""
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__version__="0.2.0"
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__version__="0.3.0"
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__author__="Xavier Dupré"

‎onnx_array_api/npx/npx_functions_test.py‎

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@npxapi_function
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def_min_max(
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x:TensorType[ElemType.numerics,"T"]
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x:TensorType[ElemType.numerics,"T"],
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)->TupleType[TensorType[ElemType.numerics,"T"],TensorType[ElemType.numerics,"T"]]:
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returntuple_var(var(x,op="ReduceMin"),var(x,op="ReduceMax"))
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@npxapi_inline
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def_min_max_inline(
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x:TensorType[ElemType.numerics,"T"]
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x:TensorType[ElemType.numerics,"T"],
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)->TupleType[TensorType[ElemType.numerics,"T"],TensorType[ElemType.numerics,"T"]]:
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returntuple_var(var(x,op="ReduceMin"),var(x,op="ReduceMax"))
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@npxapi_function
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defabsolute(
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x:TensorType[ElemType.numerics,"T"]
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x:TensorType[ElemType.numerics,"T"],
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)->TensorType[ElemType.numerics,"T"]:
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"See :func:`numpy.absolute`."
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returnvar(x,op="Abs")
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@npxapi_function
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defnegative(
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x:TensorType[ElemType.numerics,"T"]
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x:TensorType[ElemType.numerics,"T"],
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)->TensorType[ElemType.numerics,"T"]:
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"See :func:`numpy.negative`."
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returnvar(x,op="Neg")

‎onnx_array_api/validation/tools.py‎

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defrandomize_proto(
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onx:Union[ModelProto,GraphProto,FunctionProto,NodeProto,TensorProto]
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onx:Union[ModelProto,GraphProto,FunctionProto,NodeProto,TensorProto],
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)->Union[ModelProto,GraphProto,FunctionProto,NodeProto,TensorProto]:
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"""
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Randomizes float initializers or constant nodes.

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