22 lines
1.4 KiB
JSON
22 lines
1.4 KiB
JSON
{
|
|
"type": "Conv 2D Transpose Layer",
|
|
"definition": {
|
|
"text": "Transposed convolutional layer (sometimes called Deconvolution). The need for transposed convolutions generally arises from the desire to use a transformation going in the opposite direction of a normal convolution, i.e., from something that has the shape of the output of some convolution to something that has the shape of its input while maintaining a connectivity pattern that is compatible with said convolution.",
|
|
"updated": 1613218678919
|
|
},
|
|
"paragraphs": [
|
|
{
|
|
"style": "Text",
|
|
"text": "When using this layer as the first layer in a model, provide the configuration inputShape (Array of integers, does not include the sample axis), e.g., inputShape: [128, 128, 3] for 128x128 RGB pictures in dataFormat: 'channelsLast'.",
|
|
"updated": 1613218856414
|
|
},
|
|
{
|
|
"style": "List",
|
|
"text": "Input shape: 4D tensor with shape: [batch, channels, rows, cols] if dataFormat is 'channelsFirst'. or 4D tensor with shape [batch, rows, cols, channels] if dataFormat is 'channelsLast."
|
|
},
|
|
{
|
|
"style": "List",
|
|
"text": "Output shape: 4D tensor with shape: [batch, filters, newRows, newCols] if dataFormat is 'channelsFirst'. or 4D tensor with shape: [batch, newRows, newCols, filters] if dataFormat is 'channelsLast'."
|
|
}
|
|
]
|
|
} |