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[API Compatibility No.11、16、69、86] Add gcd, gcd_, lcm, lcm_ -part #787

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[API Compatibility No.11、16、69、86] Add gcd, gcd_, lcm, lcm_ -part #787

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28 changes: 2 additions & 26 deletions paconvert/api_mapping.json
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5707,19 +5707,7 @@
"Matcher": "ChangePrefixMatcher"
},
"torch.gcd": {
"Matcher": "GenericMatcher",
"paddle_api": "paddle.gcd",
"min_input_args": 2,
"args_list": [
"input",
"other",
"*",
"out"
],
"kwargs_change": {
"input": "x",
"other": "y"
}
"Matcher": "ChangePrefixMatcher"
},
"torch.ge": {
"Matcher": "ChangePrefixMatcher"
Expand Down Expand Up @@ -6243,19 +6231,7 @@
"Matcher": "ChangePrefixMatcher"
},
"torch.lcm": {
"Matcher": "GenericMatcher",
"paddle_api": "paddle.lcm",
"min_input_args": 2,
"args_list": [
"input",
"other",
"*",
"out"
],
"kwargs_change": {
"input": "x",
"other": "y"
}
"Matcher": "ChangePrefixMatcher"
},
"torch.ldexp": {
"Matcher": "GenericMatcher",
Expand Down
130 changes: 130 additions & 0 deletions tests/test_gcd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -88,3 +88,133 @@ def test_case_6():
"""
)
obj.run(pytorch_code, ["result", "out"])


def test_case_7():
"""Mixed positional and keyword arguments"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15])
b = torch.tensor([3, 4, 5])
result = torch.gcd(a, other=b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_8():
"""2D tensor input"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([[12, 18], [24, 36]])
b = torch.tensor([[8, 6], [16, 12]])
result = torch.gcd(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_9():
"""Negative values"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([-5, 10, -15])
b = torch.tensor([3, -4, -5])
result = torch.gcd(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_10():
"""Broadcasting"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([[12, 18, 24]])
b = torch.tensor([6])
result = torch.gcd(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_11():
"""Out parameter with positional args"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15])
b = torch.tensor([3, 4, 5])
out = torch.empty(3, dtype=torch.int64)
result = torch.gcd(a, b, out=out)
"""
)
obj.run(pytorch_code, ["result", "out"])


def test_case_12():
"""3D tensor input"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([[[12, 18], [24, 36]], [[8, 14], [20, 28]]])
b = torch.tensor([[[4, 6], [8, 12]], [[2, 7], [10, 14]]])
result = torch.gcd(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_13():
"""int32 dtype"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15], dtype=torch.int32)
b = torch.tensor([3, 4, 5], dtype=torch.int32)
result = torch.gcd(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_14():
"""Variable arguments"""
pytorch_code = textwrap.dedent(
"""
import torch
x = torch.tensor([12, 18, 24])
y = torch.tensor([8, 6, 16])
result = torch.gcd(x, y)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_15():
"""Zero values"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([0, 10, 0])
b = torch.tensor([5, 0, 0])
result = torch.gcd(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_16():
"""Expression as argument"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15])
result = torch.gcd(a, torch.tensor([3, 4, 5]))
"""
)
obj.run(pytorch_code, ["result"])
130 changes: 130 additions & 0 deletions tests/test_lcm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -100,3 +100,133 @@ def test_case_7():
"""
)
obj.run(pytorch_code, ["result", "out"])


def test_case_8():
"""Mixed positional and keyword arguments"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15])
b = torch.tensor([3, 4, 5])
result = torch.lcm(a, other=b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_9():
"""2D tensor input"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([[12, 18], [24, 36]])
b = torch.tensor([[8, 6], [16, 12]])
result = torch.lcm(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_10():
"""Negative values"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([-5, 10, -15])
b = torch.tensor([3, -4, -5])
result = torch.lcm(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_11():
"""Broadcasting"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([[12, 18, 24]])
b = torch.tensor([6])
result = torch.lcm(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_12():
"""Out parameter with positional args"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15])
b = torch.tensor([3, 4, 5])
out = torch.empty(3, dtype=torch.int64)
result = torch.lcm(a, b, out=out)
"""
)
obj.run(pytorch_code, ["result", "out"])


def test_case_13():
"""3D tensor input"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([[[12, 18], [24, 36]], [[8, 14], [20, 28]]])
b = torch.tensor([[[4, 6], [8, 12]], [[2, 7], [10, 14]]])
result = torch.lcm(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_14():
"""int32 dtype"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15], dtype=torch.int32)
b = torch.tensor([3, 4, 5], dtype=torch.int32)
result = torch.lcm(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_15():
"""Variable arguments"""
pytorch_code = textwrap.dedent(
"""
import torch
x = torch.tensor([12, 18, 24])
y = torch.tensor([8, 6, 16])
result = torch.lcm(x, y)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_16():
"""Zero values"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([0, 10, 0])
b = torch.tensor([5, 0, 0])
result = torch.lcm(a, b)
"""
)
obj.run(pytorch_code, ["result"])


def test_case_17():
"""Expression as argument"""
pytorch_code = textwrap.dedent(
"""
import torch
a = torch.tensor([5, 10, 15])
result = torch.lcm(a, torch.tensor([3, 4, 5]))
"""
)
obj.run(pytorch_code, ["result"])