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# Owner(s): ["oncall: jit"]
import os
import sys
import torch
# 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.jit_utils import JitTestCase
if __name__ == "__main__":
raise RuntimeError(
"This test file is not meant to be run directly, use:\n\n"
"\tpython test/test_jit.py TESTNAME\n\n"
"instead."
)
class TestTensorCreationOps(JitTestCase):
"""
A suite of tests for ops that create tensors.
"""
def test_randperm_default_dtype(self):
def randperm(x: int):
perm = torch.randperm(x)
# Have to perform assertion here because TorchScript returns dtypes
# as integers, which are not comparable against eager torch.dtype.
assert perm.dtype == torch.int64
self.checkScript(randperm, (3,))
def test_randperm_specifed_dtype(self):
def randperm(x: int):
perm = torch.randperm(x, dtype=torch.float)
# Have to perform assertion here because TorchScript returns dtypes
# as integers, which are not comparable against eager torch.dtype.
assert perm.dtype == torch.float
self.checkScript(randperm, (3,))
def test_triu_indices_default_dtype(self):
def triu_indices(rows: int, cols: int):
indices = torch.triu_indices(rows, cols)
# Have to perform assertion here because TorchScript returns dtypes
# as integers, which are not comparable against eager torch.dtype.
assert indices.dtype == torch.int64
self.checkScript(triu_indices, (3, 3))
def test_triu_indices_specified_dtype(self):
def triu_indices(rows: int, cols: int):
indices = torch.triu_indices(rows, cols, dtype=torch.int32)
# Have to perform assertion here because TorchScript returns dtypes
# as integers, which are not comparable against eager torch.dtype.
assert indices.dtype == torch.int32
self.checkScript(triu_indices, (3, 3))
def test_tril_indices_default_dtype(self):
def tril_indices(rows: int, cols: int):
indices = torch.tril_indices(rows, cols)
# Have to perform assertion here because TorchScript returns dtypes
# as integers, which are not comparable against eager torch.dtype.
assert indices.dtype == torch.int64
self.checkScript(tril_indices, (3, 3))
def test_tril_indices_specified_dtype(self):
def tril_indices(rows: int, cols: int):
indices = torch.tril_indices(rows, cols, dtype=torch.int32)
# Have to perform assertion here because TorchScript returns dtypes
# as integers, which are not comparable against eager torch.dtype.
assert indices.dtype == torch.int32
self.checkScript(tril_indices, (3, 3))
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