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import numpy as np |
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import onnx |
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import onnx.helper |
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from onnxscript import script |
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from onnxscript.onnx_opset import opset17 as op |
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from tests.common.onnx_script_test_case import FunctionTestParams as Test |
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@script() |
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def int_attr(): |
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return op.Constant(value_int=17) |
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int_attr_test = Test(int_attr, input=[], output=[np.array(17, dtype=np.int64)]) |
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@script() |
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def ints_attr(): |
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return op.Constant(value_ints=[17, 19]) |
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ints_attr_test = Test(ints_attr, input=[], output=[np.array([17, 19], dtype=np.int64)]) |
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@script() |
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def float_attr(): |
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return op.Constant(value_float=17.0) |
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float_attr_test = Test(float_attr, input=[], output=[np.array(17.0, dtype=np.float32)]) |
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@script() |
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def floats_attr(): |
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return op.Constant(value_floats=[17.0, 19.0]) |
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floats_attr_test = Test( |
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floats_attr, input=[], output=[np.array([17.0, 19.0], dtype=np.float32)] |
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) |
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@script() |
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def string_attr(): |
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return op.Constant(value_string="hello") |
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string_attr_test = Test(string_attr, input=[], output=[np.array("hello")]) |
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@script() |
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def strings_attr(): |
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return op.Constant(value_strings=["hello", "world"]) |
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strings_attr_test = Test(strings_attr, input=[], output=[np.array(["hello", "world"])]) |
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tensor1 = onnx.helper.make_tensor("t", onnx.TensorProto.FLOAT, [2], [17.0, 19.0]) |
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@script() |
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def tensor_attr(): |
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return op.Constant(value=tensor1) |
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tensor_attr_test = Test( |
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tensor_attr, input=[], output=[np.array([17.0, 19.0], dtype=np.float32)] |
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) |
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