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Update output_padding argument in convolution transpose layer #21383

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Merged
merged 1 commit into from
Jun 17, 2025
Merged

Update output_padding argument in convolution transpose layer #21383

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1 change: 1 addition & 0 deletions keras/src/layers/convolutional/base_conv_transpose.py
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Original file line number Diff line number Diff line change
Expand Up @@ -112,6 +112,7 @@ def __init__(
output_padding,
rank,
"output_padding",
allow_zero=True,
)
self.data_format = standardize_data_format(data_format)
self.activation = activations.get(activation)
Expand Down
13 changes: 11 additions & 2 deletions keras/src/layers/convolutional/conv1d_transpose.py
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Expand Up @@ -29,15 +29,22 @@ class Conv1DTranspose(BaseConvTranspose):
`"valid"` means no padding. `"same"` results in padding evenly to
the left/right or up/down of the input such that output has the same
height/width dimension as the input.
output_padding: An integer tuple/list of 1 integer specifying the
amount of padding along the time dimension of the output tensor.
The amount of output padding must be lower than the stride.
If set to `None` (default), the output shape is inferred.
data_format: string, either `"channels_last"` or `"channels_first"`.
The ordering of the dimensions in the inputs. `"channels_last"`
corresponds to inputs with shape `(batch, steps, features)`
while `"channels_first"` corresponds to inputs with shape
`(batch, features, steps)`. It defaults to the `image_data_format`
value found in your Keras config file at `~/.keras/keras.json`.
If you never set it, then it will be `"channels_last"`.
dilation_rate: int or tuple/list of 1 integers, specifying the dilation
rate to use for dilated transposed convolution.
dilation_rate: An integer tuple/list of 1 integer, specifying
the dilation rate to use for dilated convolution.
Currently, specifying a `dilation_rate` value != 1 is
incompatible with specifying a stride value != 1.
Also dilation rate larger than 1 is not currently supported.
activation: Activation function. If `None`, no activation is applied.
use_bias: bool, if `True`, bias will be added to the output.
kernel_initializer: Initializer for the convolution kernel. If `None`,
Expand Down Expand Up @@ -97,6 +104,7 @@ def __init__(
kernel_size,
strides=1,
padding="valid",
output_padding=None,
data_format=None,
dilation_rate=1,
activation=None,
Expand All @@ -116,6 +124,7 @@ def __init__(
kernel_size=kernel_size,
strides=strides,
padding=padding,
output_padding=output_padding,
data_format=data_format,
dilation_rate=dilation_rate,
activation=activation,
Expand Down
19 changes: 17 additions & 2 deletions keras/src/layers/convolutional/conv2d_transpose.py
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Expand Up @@ -29,6 +29,14 @@ class Conv2DTranspose(BaseConvTranspose):
`"valid"` means no padding. `"same"` results in padding evenly to
the left/right or up/down of the input. When `padding="same"` and
`strides=1`, the output has the same size as the input.
output_padding: An integer or tuple/list of 2 integers,
specifying the amount of padding along the height and width
of the output tensor.
Can be a single integer to specify the same value for all
spatial dimensions.
The amount of output padding along a given dimension must be
lower than the stride along that same dimension.
If set to `None` (default), the output shape is inferred.
data_format: string, either `"channels_last"` or `"channels_first"`.
The ordering of the dimensions in the inputs. `"channels_last"`
corresponds to inputs with shape
Expand All @@ -38,8 +46,13 @@ class Conv2DTranspose(BaseConvTranspose):
`image_data_format` value found in your Keras config file at
`~/.keras/keras.json`. If you never set it, then it will be
`"channels_last"`.
dilation_rate: int or tuple/list of 1 integers, specifying the dilation
rate to use for dilated transposed convolution.
dilation_rate: An integer or tuple/list of 2 integers,
specifying the dilation rate for
all spatial dimensions for dilated convolution.
Specifying different dilation rates
for different dimensions is not supported.
Currently, specifying any `dilation_rate` value != 1 is
incompatible with specifying any stride value != 1.
activation: Activation function. If `None`, no activation is applied.
use_bias: bool, if `True`, bias will be added to the output.
kernel_initializer: Initializer for the convolution kernel. If `None`,
Expand Down Expand Up @@ -99,6 +112,7 @@ def __init__(
kernel_size,
strides=(1, 1),
padding="valid",
output_padding=None,
data_format=None,
dilation_rate=(1, 1),
activation=None,
Expand All @@ -118,6 +132,7 @@ def __init__(
kernel_size=kernel_size,
strides=strides,
padding=padding,
output_padding=output_padding,
data_format=data_format,
dilation_rate=dilation_rate,
activation=activation,
Expand Down
18 changes: 16 additions & 2 deletions keras/src/layers/convolutional/conv3d_transpose.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,14 @@ class Conv3DTranspose(BaseConvTranspose):
`"valid"` means no padding. `"same"` results in padding evenly to
the left/right or up/down of the input. When `padding="same"` and
`strides=1`, the output has the same size as the input.
output_padding: An integer or tuple/list of 3 integers,
specifying the amount of padding along the depth, height, and
width.
Can be a single integer to specify the same value for all
spatial dimensions.
The amount of output padding along a given dimension must be
lower than the stride along that same dimension.
If set to `None` (default), the output shape is inferred.
data_format: string, either `"channels_last"` or `"channels_first"`.
The ordering of the dimensions in the inputs. `"channels_last"`
corresponds to inputs with shape
Expand All @@ -38,8 +46,12 @@ class Conv3DTranspose(BaseConvTranspose):
It defaults to the `image_data_format` value found in your Keras
config file at `~/.keras/keras.json`. If you never set it, then it
will be `"channels_last"`.
dilation_rate: int or tuple/list of 1 integers, specifying the dilation
rate to use for dilated transposed convolution.
dilation_rate: an integer or tuple/list of 3 integers, specifying
the dilation rate to use for dilated convolution.
Can be a single integer to specify the same value for
all spatial dimensions.
Currently, specifying any `dilation_rate` value != 1 is
incompatible with specifying any stride value != 1.
activation: Activation function. If `None`, no activation is applied.
use_bias: bool, if `True`, bias will be added to the output.
kernel_initializer: Initializer for the convolution kernel. If `None`,
Expand Down Expand Up @@ -105,6 +117,7 @@ def __init__(
strides=(1, 1, 1),
padding="valid",
data_format=None,
output_padding=None,
dilation_rate=(1, 1, 1),
activation=None,
use_bias=True,
Expand All @@ -123,6 +136,7 @@ def __init__(
kernel_size=kernel_size,
strides=strides,
padding=padding,
output_padding=output_padding,
data_format=data_format,
dilation_rate=dilation_rate,
activation=activation,
Expand Down