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[Typing][A-17] Add type annotations for conv layers #65183

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merged 8 commits into from
Jun 28, 2024
Merged

[Typing][A-17] Add type annotations for conv layers #65183

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f4b5378
Typing_conv.py
liyongchao911 Jun 14, 2024
65452d4
update
liyongchao911 Jun 17, 2024
06faaf3
update
liyongchao911 Jun 19, 2024
cdf0aad
update
liyongchao911 Jun 25, 2024
3039158
Merge branch 'develop' into Typing_fix2
SigureMo Jun 28, 2024
125721f
revert all
SigureMo Jun 28, 2024
ee8d5d6
annotate conv layer
SigureMo Jun 28, 2024
f29d247
remove auto import
SigureMo Jun 28, 2024
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2 changes: 1 addition & 1 deletion python/paddle/nn/functional/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@
]
_DropoutMode: TypeAlias = Literal['upscale_in_train', 'downscale_in_infer']
_PaddingTensorMode: TypeAlias = Literal[
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为啥要加 zeros? 我记得当时单独在 conv 里面加了一个

    _ConvPaddingMode: TypeAlias = Literal[
        "zero", "reflect", "replicate", "circular"
    ]

_PaddingTensorMode 是 constant ... ，_ConvPaddingMode 是 zeros ... ～

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没必要区分到这种程度，而且这名字也很奇怪

"constant", "reflect", "replicate", "circular"
"zeros", "constant", "reflect", "replicate", "circular"
]
_PaddingSizeMode: TypeAlias = Literal[ # noqa: PYI047
'valid', 'same', 'VALID', 'SAME'
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31 changes: 16 additions & 15 deletions python/paddle/nn/functional/conv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@
DataLayout1D,
DataLayout2D,
DataLayout3D,
DataLayoutND,
Size1,
Size2,
Size3,
Expand Down Expand Up @@ -127,20 +128,20 @@ def _update_padding_nd(padding, channel_last, num_dims):


def _conv_nd(
x,
weight,
bias=None,
stride=1,
padding=0,
x: Tensor,
weight: Tensor,
bias: Tensor | None = None,
stride: int | Sequence[int] = 1,
padding: _PaddingSizeMode | int | Sequence[int] | Sequence[Size2] = 0,
padding_algorithm=None,
dilation=1,
groups=1,
data_format="NCHW",
channel_dim=1,
op_type="conv2d",
use_cudnn=True,
name=None,
):
dilation: int | Sequence[int] = 1,
groups: int = 1,
data_format: DataLayoutND = "NCHW",
channel_dim: int = 1,
op_type: str = "conv2d",
use_cudnn: bool = True,
name: str | None = None,
) -> Tensor:
# Due to the poor performance of NHWC, we transpose the input to NCHW.
if in_dynamic_or_pir_mode() and op_type == "conv2d":
pre_bias = _C_ops.conv2d(
Expand Down Expand Up @@ -777,7 +778,7 @@ def conv1d_transpose(
weight: Tensor,
bias: Tensor | None = None,
stride: Size1 = 1,
padding: _PaddingSizeMode | Size1 | Size2 = 0,
padding: _PaddingSizeMode | Size1 | Size2 | Sequence[Size2] = 0,
output_padding: Size1 = 0,
groups: int = 1,
dilation: Size1 = 1,
Expand Down Expand Up @@ -1356,7 +1357,7 @@ def conv3d(
weight: Tensor,
bias: Tensor | None = None,
stride: Size3 = 1,
padding=0,
padding: _PaddingSizeMode | Size3 | Size6 | Sequence[Size2] = 0,
dilation: Size3 = 1,
groups: int = 1,
data_format: DataLayout3D = "NCDHW",
Expand Down
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