tensor-sensor

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"""
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MIT License
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Copyright (c) 2021 Terence Parr
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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"""
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from tsensor.ast import IncrEvalTrap
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from tsensor.parsing import PyExprParser
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import sys
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import numpy as np
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import torch
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def check(s,expected):
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    frame = sys._getframe()
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    caller = frame.f_back
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    p = PyExprParser(s)
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    t = p.parse()
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    bad_subexpr = None
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    try:
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        t.eval(caller)
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    except IncrEvalTrap as exc:
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        bad_subexpr = str(exc.offending_expr)
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    assert bad_subexpr==expected
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def test_missing_var():
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    a = 3
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    c = 5
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    check("a+b+c", "b")
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    check("z+b+c", "z")
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def test_matrix_mult():
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    W = torch.tensor([[1, 2], [3, 4]])
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    b = torch.tensor([[1,2,3]])
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    check("W@b+torch.abs(b)", "W@b")
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def test_bad_arg():
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    check("torch.abs('foo')", "torch.abs('foo')")
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def test_parens():
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    a = 3
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    b = 4
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    c = 5
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    check("(a+b)/0", "(a+b)/0")
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def test_array_literal():
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    a = torch.tensor([[1,2,3],[4,5,6]])
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    b = torch.tensor([[1,2,3]])
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    a+b
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    check("a + b@2", """b@2""")
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def test_array_literal2():
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    a = torch.tensor([[1,2,3],[4,5,6]])
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    b = torch.tensor([[1,2,3]])
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    a+b
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    check("(a+b)@2", """(a+b)@2""")
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