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6fd8e28a99
Change the names of the parameters in the `addmm` meta kernel to be more consistent with `mm`. Functionally, the only difference in behaviour should be that `addmm` meta kernel gets its options from the `input` tensor instead of from the `bias` parameter. Fixes #84930 CC: @ezyang @ngimel @wconstab @ke1337 @glebk-cerebras Pull Request resolved: https://github.com/pytorch/pytorch/pull/84960 Approved by: https://github.com/ezyang
35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
# Owner(s): ["oncall: jit"]
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import torch
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from torch.testing._internal.common_utils import TestCase
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import torch._lazy
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import torch._lazy.ts_backend
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torch._lazy.ts_backend.init()
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class TestMetaKernel(TestCase):
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def test_addmm_invalid_dtype(self):
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"""Tests that the addmm meta kernel returns the correct output type"""
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input = torch.ones(2, 2, dtype=torch.float16).to("lazy")
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self.assertTrue(input.dtype == torch.float16)
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fc_nobias = torch.nn.Linear(2, 2, bias=False, dtype=float32).to("lazy")
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with self.assertRaises(Exception):
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out_nobias = fc_nobias(input)
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def test_addmm(self):
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"""Tests that the addmm meta kernel returns the correct output type"""
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input = torch.ones(2, 2, dtype=torch.float16).to("lazy")
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self.assertEqual(input.dtype, torch.float16)
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fc_nobias = torch.nn.Linear(2, 2, bias=False, dtype=float16).to("lazy")
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out_nobias = fc_nobias(input)
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self.assertEqual(out_nobias.dtype, torch.float16)
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fc_bias = torch.nn.Linear(2, 2, bias=True, dtype=float16).to("lazy")
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out_bias = fc_bias(input)
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self.assertEqual(out_bias.dtype, torch.float16)
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