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【Hackathon 7th No.38】为 Paddle 代码转换工具新增 API 转换规则（第5组） #486

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【Hackathon 7th No.38】为 Paddle 代码转换工具新增 API 转换规则（第5组） #486

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409 changes: 205 additions & 204 deletions paconvert/api_alias_mapping.json
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33,107 changes: 16,631 additions & 16,476 deletions paconvert/api_mapping.json
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257 changes: 255 additions & 2 deletions paconvert/api_matcher.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1450,6 +1450,14 @@ def generate_code(self, kwargs):
return GenericMatcher.generate_code(self, kwargs)


class ScatterReduceMatcher(BaseMatcher):
def generate_code(self, kwargs):
reduce_mapping = {'"""sum"""': '"add"', '"""prod"""': '"multiply"'}
if "reduce" in kwargs and kwargs["reduce"] in reduce_mapping:
kwargs["reduce"] = reduce_mapping[kwargs["reduce"]]
return GenericMatcher.generate_code(self, kwargs)


class SparseSoftmaxMatcher(BaseMatcher):
def generate_code(self, kwargs):
code = ""
Expand Down Expand Up @@ -3138,6 +3146,16 @@ def generate_code(self, kwargs):
return code


class CartesianProdMatcher(BaseMatcher):
def get_paddle_nodes(self, args, kwargs):
new_args = self.parse_args(args)
code = "paddle.cartesian_prod([ {}".format(new_args[0])
for arg in new_args[1:]:
code = code + ", {}".format(arg)
code = code + "])"
return ast.parse(code).body


class Chain_MatmulMatcher(BaseMatcher):
def get_paddle_nodes(self, args, kwargs):
if len(args) == 1 and isinstance(args[0], ast.Starred):
Expand Down Expand Up @@ -4274,11 +4292,246 @@ def generate_code(self, kwargs):
return "paddle_aux._CONVERT_SYMEIG({})".format(self.kwargs_to_str(kwargs))


class CanCastMatcher(BaseMatcher):
def generate_aux_code(self):
CODE_TEMPLATE = textwrap.dedent(
"""
def can_cast(from_, to):
can_cast_dict = {
paddle.bfloat16: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False
},
paddle.float16: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.float32: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.float64: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.complex64: {
paddle.bfloat16: False,
paddle.float16: False,
paddle.float32: False,
paddle.float64: False,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.complex128: {
paddle.bfloat16: False,
paddle.float16: False,
paddle.float32: False,
paddle.float64: False,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: False,
paddle.int8: False,
paddle.int16: False,
paddle.int32: False,
paddle.int64: False,
paddle.bool: False,
},
paddle.uint8: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int8: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int16: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int32: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.int64: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: False,
},
paddle.bool: {
paddle.bfloat16: True,
paddle.float16: True,
paddle.float32: True,
paddle.float64: True,
paddle.complex64: True,
paddle.complex128: True,
paddle.uint8: True,
paddle.int8: True,
paddle.int16: True,
paddle.int32: True,
paddle.int64: True,
paddle.bool: True,
}
}
return can_cast_dict[from_][to]
setattr(paddle, 'can_cast', can_cast)
"""
)
return CODE_TEMPLATE

def generate_code(self, kwargs):
self.write_aux_code()
_from_dtype = kwargs["from_"][3:-3]
_to_dtype = kwargs["to"][3:-3]
code = "paddle_aux.can_cast(paddle.{}, paddle.{})".format(
_from_dtype, _to_dtype
)
return code


class FloatPowerMatcher(BaseMatcher):
def generate_code(self, kwargs):
return "{}.cast(paddle.float64).pow({})".format(
self.paddleClass, kwargs["exponent"]
if "input" not in kwargs:
return "{}.cast(paddle.float64).pow({}.cast(paddle.float64) if isinstance({}, paddle.Tensor) else {})".format(
self.paddleClass,
kwargs["exponent"],
kwargs["exponent"],
kwargs["exponent"],
)
else:
if "out" not in kwargs:
return "paddle.pow({}.cast(paddle.float64), {}.cast(paddle.float64) if isinstance({}, paddle.Tensor) else {})".format(
kwargs["input"],
kwargs["exponent"],
kwargs["exponent"],
kwargs["exponent"],
)
else:
return "paddle.assign(paddle.pow({}.cast(paddle.float64), {}.cast(paddle.float64) if isinstance({}, paddle.Tensor) else {}), {})".format(
kwargs["input"],
kwargs["exponent"],
kwargs["exponent"],
kwargs["exponent"],
kwargs["out"],
)


class PositiveMatcher(BaseMatcher):
def generate_code(self, kwargs):
API_TEMPLATE = textwrap.dedent(
"""
def positive({}):
if {}.dtype != paddle.bool:
return {}
else:
raise RuntimeError("boolean tensors is not supported.")

positive({})
"""
)
if "input" not in kwargs:
code = API_TEMPLATE.format(
self.paddleClass, self.paddleClass, self.paddleClass, self.paddleClass
)
else:
code = API_TEMPLATE.format(
kwargs["input"], kwargs["input"], kwargs["input"], kwargs["input"]
)
return code


class FloatPowerInplaceMatcher(BaseMatcher):
Expand Down
51 changes: 51 additions & 0 deletions tests/test_Tensor_isneginf.py
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@@ -0,0 +1,51 @@
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import textwrap

from apibase import APIBase

obj = APIBase("torch.Tensor.isneginf")


def test_case_1():
pytorch_code = textwrap.dedent(
"""
import torch
result = torch.tensor([1, float('inf'), 2, float('-inf'), float('nan')]).isneginf()
"""
)
obj.run(pytorch_code, ["result"])


def test_case_2():
pytorch_code = textwrap.dedent(
"""
import torch
input = torch.tensor([1, float('inf'), 2, float('-inf'), float('nan')])
result = input.isneginf()
"""
)
obj.run(pytorch_code, ["result"])


def test_case_3():
pytorch_code = textwrap.dedent(
"""
import torch
input = torch.tensor([1, 6.9, 2])
result = input.isneginf()
"""
)
obj.run(pytorch_code, ["result"])
51 changes: 51 additions & 0 deletions tests/test_Tensor_isposinf.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,51 @@
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import textwrap

from apibase import APIBase

obj = APIBase("torch.Tensor.isposinf")


def test_case_1():
pytorch_code = textwrap.dedent(
"""
import torch
result = torch.tensor([1, float('inf'), 2, float('-inf'), float('nan')]).isposinf()
"""
)
obj.run(pytorch_code, ["result"])


def test_case_2():
pytorch_code = textwrap.dedent(
"""
import torch
input = torch.tensor([1, float('inf'), 2, float('-inf'), float('nan')])
result = input.isposinf()
"""
)
obj.run(pytorch_code, ["result"])


def test_case_3():
pytorch_code = textwrap.dedent(
"""
import torch
input = torch.tensor([1, 6.9, 2])
result = input.isposinf()
"""
)
obj.run(pytorch_code, ["result"])
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