mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
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
115 lines
2.8 KiB
Python
115 lines
2.8 KiB
Python
# Owner(s): ["oncall: jit"]
|
|
|
|
import os
|
|
import sys
|
|
|
|
import torch
|
|
from torch import nn
|
|
|
|
|
|
# Make the helper files in test/ importable
|
|
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
|
|
sys.path.append(pytorch_test_dir)
|
|
from torch.testing._internal.common_utils import raise_on_run_directly
|
|
from torch.testing._internal.jit_utils import JitTestCase
|
|
|
|
|
|
class Sequence(nn.Module):
|
|
def __init__(self) -> None:
|
|
super().__init__()
|
|
self.lstm1 = nn.LSTMCell(1, 51)
|
|
self.lstm2 = nn.LSTMCell(51, 51)
|
|
self.linear = nn.Linear(51, 1)
|
|
|
|
def forward(self, input):
|
|
outputs = []
|
|
h_t = torch.zeros(input.size(0), 51)
|
|
c_t = torch.zeros(input.size(0), 51)
|
|
h_t2 = torch.zeros(input.size(0), 51)
|
|
c_t2 = torch.zeros(input.size(0), 51)
|
|
|
|
for input_t in input.split(1, dim=1):
|
|
h_t, c_t = self.lstm1(input_t, (h_t, c_t))
|
|
h_t2, c_t2 = self.lstm2(h_t, (h_t2, c_t2))
|
|
output = self.linear(h_t2)
|
|
outputs += [output]
|
|
outputs = torch.cat(outputs, dim=1)
|
|
return outputs
|
|
|
|
|
|
class TestScriptProfile(JitTestCase):
|
|
def test_basic(self):
|
|
seq = torch.jit.script(Sequence())
|
|
p = torch.jit._ScriptProfile()
|
|
p.enable()
|
|
seq(torch.rand((10, 100)))
|
|
p.disable()
|
|
self.assertNotEqual(p.dump_string(), "")
|
|
|
|
def test_script(self):
|
|
seq = Sequence()
|
|
|
|
p = torch.jit._ScriptProfile()
|
|
p.enable()
|
|
|
|
@torch.jit.script
|
|
def fn():
|
|
_ = seq(torch.rand((10, 100)))
|
|
|
|
fn()
|
|
p.disable()
|
|
|
|
self.assertNotEqual(p.dump_string(), "")
|
|
|
|
def test_multi(self):
|
|
seq = torch.jit.script(Sequence())
|
|
profiles = [torch.jit._ScriptProfile() for _ in range(5)]
|
|
for p in profiles:
|
|
p.enable()
|
|
|
|
last = None
|
|
while len(profiles) > 0:
|
|
seq(torch.rand((10, 10)))
|
|
p = profiles.pop()
|
|
p.disable()
|
|
stats = p.dump_string()
|
|
self.assertNotEqual(stats, "")
|
|
if last:
|
|
self.assertNotEqual(stats, last)
|
|
last = stats
|
|
|
|
def test_section(self):
|
|
seq = Sequence()
|
|
|
|
@torch.jit.script
|
|
def fn(max: int):
|
|
_ = seq(torch.rand((10, max)))
|
|
|
|
p = torch.jit._ScriptProfile()
|
|
p.enable()
|
|
fn(100)
|
|
p.disable()
|
|
s0 = p.dump_string()
|
|
|
|
fn(10)
|
|
p.disable()
|
|
s1 = p.dump_string()
|
|
|
|
p.enable()
|
|
fn(10)
|
|
p.disable()
|
|
s2 = p.dump_string()
|
|
|
|
self.assertEqual(s0, s1)
|
|
self.assertNotEqual(s1, s2)
|
|
|
|
def test_empty(self):
|
|
p = torch.jit._ScriptProfile()
|
|
p.enable()
|
|
p.disable()
|
|
self.assertEqual(p.dump_string(), "")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
raise_on_run_directly("test/test_jit.py")
|