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bf7e290854
This PR is part of a series attempting to re-submit https://github.com/pytorch/pytorch/pull/134592 as smaller PRs. In jit tests: - Add and use a common raise_on_run_directly method for when a user runs a test file directly which should not be run this way. Print the file which the user should have run. - Raise a RuntimeError on tests which have been disabled (not run) Pull Request resolved: https://github.com/pytorch/pytorch/pull/154725 Approved by: https://github.com/clee2000
67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
# Owner(s): ["oncall: jit"]
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import torch
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import torch._C
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from torch.testing import FileCheck
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from torch.testing._internal.common_utils import raise_on_run_directly
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from torch.testing._internal.jit_utils import JitTestCase
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class TestGraphRewritePasses(JitTestCase):
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def test_fuse_linear(self):
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class FunctionalLinear(torch.nn.Module):
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def __init__(self, weight, bias):
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super().__init__()
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self.weight = weight
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self.bias = bias
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def forward(self, x):
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res = torch.matmul(x, self.weight.t())
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if self.bias is not None:
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res.add_(self.bias)
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return res
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x1 = torch.rand(3)
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w1 = torch.rand(5, 3)
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b1 = torch.rand(5)
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for has_bias in [True, False]:
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bias = b1 if has_bias else None
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model = torch.jit.trace(FunctionalLinear(w1, bias), [x1])
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for node in model.graph.nodes():
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if node.kind() == "aten::matmul":
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source_range_1 = node.sourceRange()
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torch._C._jit_pass_fuse_linear(model.graph)
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for node in model.graph.nodes():
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if node.kind() == "aten::linear":
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source_range_2 = node.sourceRange()
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FileCheck().check("aten::linear").run(model.graph)
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check_not = ["aten::matmul", "aten::addmm", "aten::add_", "aten::t("]
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for cn in check_not:
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FileCheck().check_not(cn).run(model.graph)
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self.assertTrue(source_range_1 == source_range_2)
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# make sure it runs
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model(x1)
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# check matmuls are not fused
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class Matmul(torch.nn.Module):
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def __init__(self, weight):
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super().__init__()
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self.weight = weight
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def forward(self, x):
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return torch.matmul(x, self.weight)
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x = torch.rand(5, 6, 5)
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w = torch.rand(5, 5, 100)
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model = torch.jit.trace(Matmul(w), [x])
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torch._C._jit_pass_fuse_linear(model.graph)
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# check 3d matmul is not fused
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FileCheck().check("aten::matmul").run(model.graph)
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FileCheck().check_not("aten::linear").run(model.graph)
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# make sure it runs
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model(x)
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if __name__ == "__main__":
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raise_on_run_directly("test/test_jit.py")
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