tf.keras.ops.separable_conv | TensorFlow v2.16.1 (original) (raw)
tf.keras.ops.separable_conv
General N-D separable convolution.
View aliases
Main aliases
tf.keras.ops.nn.separable_conv
tf.keras.ops.separable_conv(
inputs,
depthwise_kernel,
pointwise_kernel,
strides=1,
padding='valid',
data_format=None,
dilation_rate=1
)
This ops supports 1D and 2D separable convolution. separable_conv is a depthwise conv followed by a pointwise conv.
| Args | |
|---|---|
| inputs | Tensor of rank N+2. inputs has shape(batch_size,) + inputs_spatial_shape + (num_channels,) ifdata_format="channels_last", or(batch_size, num_channels) + inputs_spatial_shape ifdata_format="channels_first". |
| depthwise_kernel | Tensor of rank N+2. depthwise_kernel has shape [kernel_spatial_shape, num_input_channels, num_channels_multiplier],num_input_channels should match the number of channels ininputs. |
| pointwise_kernel | Tensor of rank N+2. pointwise_kernel has shape(*ones_like(kernel_spatial_shape), num_input_channels * num_channels_multiplier, num_output_channels). |
| strides | int or int tuple/list of len(inputs_spatial_shape), specifying the strides of the convolution along each spatial dimension. If strides is int, then every spatial dimension shares the same strides. |
| padding | string, either "valid" or "same". "valid" means no padding is applied, and "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 when strides=1. |
| data_format | A string, either "channels_last" or "channels_first".data_format determines the ordering of the dimensions in the inputs. If data_format="channels_last", inputs is of shape(batch_size, ..., channels) while ifdata_format="channels_first", inputs is of shape(batch_size, channels, ...). |
| dilation_rate | int or int tuple/list of len(inputs_spatial_shape), specifying the dilation rate to use for dilated convolution. Ifdilation_rate is int, then every spatial dimension shares the same dilation_rate. |
| Returns |
|---|
| A tensor of rank N+2, the result of the depthwise conv operation. |
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Last updated 2024-06-07 UTC.