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转换规则 No.272/282/318/324/326 (#149)
* Add tests * Fix * Fix
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‎paconvert/api_mapping.json‎

Lines changed: 62 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1024,7 +1024,20 @@
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"max"
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]
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},
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"torch.Tensor.histogram": {},
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"torch.Tensor.histogram": {
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"Matcher": "TensorHistogramMatcher",
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"paddle_api": "paddle.Tensor.histogram",
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"args_list": [
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"bins",
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"range",
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"weight",
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"density"
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],
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"unsupport_args": [
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"weight",
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"density"
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]
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},
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"torch.Tensor.hsplit": {},
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"torch.Tensor.hypot": {
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"Matcher": "HypotMatcher",
@@ -3186,6 +3199,19 @@
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"input": "x"
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}
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},
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"torch.corrcoef": {
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"Matcher": "GenericMatcher",
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"paddle_api": "paddle.linalg.corrcoef",
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"args_list": [
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"input"
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],
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"kwargs_change": {
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"input": "x"
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},
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"paddle_default_kwargs": {
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"rowvar": true
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}
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},
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"torch.cos": {
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"Matcher": "GenericMatcher",
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"paddle_api": "paddle.cos",
@@ -4109,6 +4135,17 @@
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"input": "x"
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}
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},
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"torch.frexp": {
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"Matcher": "GenericMatcher",
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"paddle_api": "paddle.frexp",
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"args_list": [
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"input",
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"out"
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],
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"kwargs_change": {
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"input": "x"
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}
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},
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"torch.from_numpy": {
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"Matcher": "GenericMatcher",
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"paddle_api": "paddle.to_tensor",
@@ -7424,6 +7461,17 @@
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"input": "x"
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}
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},
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"torch.nn.functional.mish": {
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"Matcher": "GenericMatcher",
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"paddle_api": "paddle.nn.functional.mish",
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"args_list": [
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"input",
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"inplace"
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],
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"kwargs_change": {
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"input": "x"
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}
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},
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"torch.nn.functional.mse_loss": {
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"Matcher": "SizeAverageMatcher",
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"paddle_api": "paddle.nn.functional.mse_loss",
@@ -8585,6 +8633,19 @@
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"input": "x"
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}
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},
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"torch.special.log_softmax": {
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"Matcher": "GenericMatcher",
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"paddle_api": "paddle.nn.functional.log_softmax",
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"args_list": [
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"input",
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"dim",
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"dtype"
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],
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"kwargs_change": {
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"input": "x",
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"dim": "axis"
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}
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},
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"torch.special.logsumexp": {
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"Matcher": "LogsumexpMatcher",
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"paddle_api": "paddle.logsumexp",

‎paconvert/api_matcher.py‎

Lines changed: 9 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -2978,6 +2978,15 @@ def generate_code(self, kwargs):
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return code
29792979

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class TensorHistogramMatcher(BaseMatcher):
2982+
def generate_code(self, kwargs):
2983+
if "range" in kwargs:
2984+
kwargs["min"] = "int({}[0])".format(kwargs["range"])
2985+
kwargs["max"] = "int({}[1])".format(kwargs["range"])
2986+
del kwargs["range"]
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return GenericMatcher.generate_code(self, kwargs)
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29812990
class SpecialNdtriMatcher(BaseMatcher):
29822991
def generate_code(self, kwargs):
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‎tests/test_Tensor_histogram.py‎

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,59 @@
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
13+
# limitations under the License.
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import textwrap
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from apibase import APIBase
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obj = APIBase("torch.Tensor.histogram")
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def test_case_1():
23+
pytorch_code = textwrap.dedent(
24+
"""
25+
import torch
26+
result = torch.tensor([[1., 2, 1]]).histogram(bins=4, range=(0., 3.))
27+
if hasattr(result, "hist"):
28+
result = result.hist
29+
result = result.to(torch.float32)
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"""
31+
)
32+
obj.run(pytorch_code, ["result"])
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def test_case_2():
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pytorch_code = textwrap.dedent(
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"""
38+
import torch
39+
input = torch.tensor([[1, 2], [3, 4]], dtype=torch.float32)
40+
result = input.histogram(bins=4, range=(0., 3.))
41+
if hasattr(result, "hist"):
42+
result = result.hist
43+
result = result.to(torch.float32)
44+
"""
45+
)
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obj.run(pytorch_code, ["result"])
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def test_case_3():
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pytorch_code = textwrap.dedent(
51+
"""
52+
import torch
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result = torch.tensor([[1., 2, 1]]).histogram()
54+
if hasattr(result, "hist"):
55+
result = result.hist
56+
result = result.to(torch.float32)
57+
"""
58+
)
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obj.run(pytorch_code, ["result"])

‎tests/test_corrcoef.py‎

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,65 @@
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
7+
# http://www.apache.org/licenses/LICENSE-2.0
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#
9+
# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
11+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# See the License for the specific language governing permissions and
13+
# limitations under the License.
14+
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import textwrap
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from apibase import APIBase
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obj = APIBase("torch.corrcoef")
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def test_case_1():
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pytorch_code = textwrap.dedent(
24+
"""
25+
import torch
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x = torch.tensor([[ 0.7308, 1.0060, 0.5270, 1.4516],
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[-0.1383, 1.5706, 0.4724, 0.4141],
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[ 0.1193, 0.2829, 0.9037, 0.3957],
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[-0.8202, -0.6474, -0.1631, -0.6543]])
30+
result = torch.corrcoef(x)
31+
"""
32+
)
33+
obj.run(pytorch_code, ["result"])
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35+
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def test_case_2():
37+
pytorch_code = textwrap.dedent(
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"""
39+
import torch
40+
x = torch.tensor([[-0.1533, 2.3020, -0.1771, 0.5928],
41+
[ 0.4338, -0.6537, 0.2296, 0.5946],
42+
[-0.4932, 1.8386, -0.1039, 1.0440],
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[ 0.1735, -0.8303, -0.3821, -0.4384],
44+
[-0.1533, 2.3020, -0.1771, 0.5928],
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[ 0.4338, -0.6537, 0.2296, 0.5946],
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[-0.4932, 1.8386, -0.1039, 1.0440],
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[ 0.1735, -0.8303, -0.3821, -0.4384]])
48+
result = torch.corrcoef(x)
49+
"""
50+
)
51+
obj.run(pytorch_code, ["result"])
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53+
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def test_case_3():
55+
pytorch_code = textwrap.dedent(
56+
"""
57+
import torch
58+
x = torch.tensor([[ 0.7308, 1.0060, 0.5270, 1.4516],
59+
[-0.1383, 1.5706, 0.4724, 0.4141],
60+
[ 0.1193, 0.2829, 0.9037, 0.3957],
61+
[-0.8202, -0.6474, -0.1631, -0.6543]])
62+
result = torch.corrcoef(input=x)
63+
"""
64+
)
65+
obj.run(pytorch_code, ["result"])

‎tests/test_nn_functional_mish.py‎

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@@ -0,0 +1,58 @@
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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#
3+
# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
5+
# You may obtain a copy of the License at
6+
#
7+
# http://www.apache.org/licenses/LICENSE-2.0
8+
#
9+
# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
11+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# See the License for the specific language governing permissions and
13+
# limitations under the License.
14+
15+
import textwrap
16+
17+
from apibase import APIBase
18+
19+
obj = APIBase("torch.nn.functional.mish")
20+
21+
22+
def test_case_1():
23+
pytorch_code = textwrap.dedent(
24+
"""
25+
import torch
26+
import torch.nn.functional as F
27+
x = torch.tensor([[[-1.3020, -0.1005, 0.5766, 0.6351, -0.8893, 0.0253, -0.1756, 1.2913],
28+
[-0.8833, -0.1369, -0.0168, -0.5409, -0.1511, -0.1240, -1.1870, -1.8816]]])
29+
result = F.mish(x)
30+
"""
31+
)
32+
obj.run(pytorch_code, ["result"])
33+
34+
35+
def test_case_2():
36+
pytorch_code = textwrap.dedent(
37+
"""
38+
import torch
39+
import torch.nn.functional as F
40+
x = torch.tensor([[[-1.3020, -0.1005, 0.5766, 0.6351, -0.8893, 0.0253, -0.1756, 1.2913],
41+
[-0.8833, -0.1369, -0.0168, -0.5409, -0.1511, -0.1240, -1.1870, -1.8816]]])
42+
result = F.mish(input=x)
43+
"""
44+
)
45+
obj.run(pytorch_code, ["result"])
46+
47+
48+
def test_case_3():
49+
pytorch_code = textwrap.dedent(
50+
"""
51+
import torch
52+
import torch.nn.functional as F
53+
x = torch.tensor([[[-1.3020, -0.1005, 0.5766, 0.6351, -0.8893, 0.0253, -0.1756, 1.2913],
54+
[-0.8833, -0.1369, -0.0168, -0.5409, -0.1511, -0.1240, -1.1870, -1.8816]]])
55+
result = F.mish(input=x, inplace=False)
56+
"""
57+
)
58+
obj.run(pytorch_code, ["result"])

‎tests/test_special_log_softmax.py‎

Lines changed: 52 additions & 0 deletions
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@@ -0,0 +1,52 @@
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
2+
#
3+
# Licensed under the Apache License, Version 2.0 (the "License");
4+
# you may not use this file except in compliance with the License.
5+
# You may obtain a copy of the License at
6+
#
7+
# http://www.apache.org/licenses/LICENSE-2.0
8+
#
9+
# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
11+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# See the License for the specific language governing permissions and
13+
# limitations under the License.
14+
15+
import textwrap
16+
17+
from apibase import APIBase
18+
19+
obj = APIBase("torch.special.log_softmax")
20+
21+
22+
def test_case_1():
23+
pytorch_code = textwrap.dedent(
24+
"""
25+
import torch
26+
input = torch.tensor([1.4907, 1.0593, 1.5696])
27+
result = torch.special.log_softmax(input, 0)
28+
"""
29+
)
30+
obj.run(pytorch_code, ["result"])
31+
32+
33+
def test_case_2():
34+
pytorch_code = textwrap.dedent(
35+
"""
36+
import torch
37+
input = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
38+
result = torch.special.log_softmax(input, dim=1)
39+
"""
40+
)
41+
obj.run(pytorch_code, ["result"])
42+
43+
44+
def test_case_3():
45+
pytorch_code = textwrap.dedent(
46+
"""
47+
import torch
48+
input = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
49+
result = torch.special.log_softmax(input, 1, dtype=torch.float32)
50+
"""
51+
)
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obj.run(pytorch_code, ["result"])

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