LayerDict¶
- class paddle.nn. LayerDict ( sublayers=None ) [source]
-
LayerDict holds sublayers in the ordered dictionary, and sublayers it contains are properly registered. Holded sublayers can be accessed like a regular ordered python dictionary.
- Parameters
-
sublayers (LayerDict|OrderedDict|list[(key,Layer)...], optional) – iterable of key/value pairs, the type of value is ‘paddle.nn.Layer’ .
- Examplex:
-
import paddle import numpy as np from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) layers_dict = paddle.nn.LayerDict(sublayers=sublayers) l = layers_dict['conv1d'] for k in layers_dict: l = layers_dict[k] len(layers_dict) #3 del layers_dict['conv2d'] len(layers_dict) #2 conv1d = layers_dict.pop('conv1d') len(layers_dict) #1 layers_dict.clear() len(layers_dict) #0
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clear
(
)
clear¶
-
Clear all the sublayers in the LayerDict.
- Parameters
-
None. –
- Examplex:
-
import paddle from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) layer_dict = paddle.nn.LayerDict(sublayers=sublayers) len(layer_dict) #3 layer_dict.clear() len(layer_dict) #0
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pop
(
key
)
pop¶
-
Remove the key from the LayerDict and return the layer of the key.
- Parameters
-
key (str) – the key to be removed.
Examples
import paddle from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) layer_dict = paddle.nn.LayerDict(sublayers=sublayers) len(layer_dict) #3 layer_dict.pop('conv2d') len(layer_dict) #2
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keys
(
)
keys¶
-
Return the iterable of the keys in LayerDict.
- Parameters
-
None. –
Examples
import paddle from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) layer_dict = paddle.nn.LayerDict(sublayers=sublayers) for k in layer_dict.keys(): print(k) #conv1d #conv2d #conv3d
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items
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items¶
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Return the iterable of the key/value pairs in LayerDict.
- Parameters
-
None. –
Examples
import paddle from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) layer_dict = paddle.nn.LayerDict(sublayers=sublayers) for k, v in layer_dict.items(): print(k, ":", v) #conv1d : Conv1D(3, 2, kernel_size=[3], data_format=NCL) #conv2d : Conv2D(3, 2, kernel_size=[3, 3], data_format=NCHW) #conv3d : Conv3D(4, 6, kernel_size=[3, 3, 3], data_format=NCDHW)
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values
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values¶
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Return the iterable of the values in LayerDict.
- Parameters
-
None. –
Examples
import paddle from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) layer_dict = paddle.nn.LayerDict(sublayers=sublayers) for v in layer_dict.values(): print(v) #Conv1D(3, 2, kernel_size=[3], data_format=NCL) #Conv2D(3, 2, kernel_size=[3, 3], data_format=NCHW) #Conv3D(4, 6, kernel_size=[3, 3, 3], data_format=NCDHW)
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update
(
sublayers
)
update¶
-
Update the key/values pairs in sublayers to the LayerDict, overwriting the existing keys.
- Parameters
-
sublayers (LayerDict|OrderedDict|list[(key,Layer)...]) – iterable of key/value pairs, the type of value is ‘paddle.nn.Layer’ .
Examples
import paddle from collections import OrderedDict sublayers = OrderedDict([ ('conv1d', paddle.nn.Conv1D(3, 2, 3)), ('conv2d', paddle.nn.Conv2D(3, 2, 3)), ('conv3d', paddle.nn.Conv3D(4, 6, (3, 3, 3))), ]) new_sublayers = OrderedDict([ ('relu', paddle.nn.ReLU()), ('conv2d', paddle.nn.Conv2D(4, 2, 4)), ]) layer_dict = paddle.nn.LayerDict(sublayers=sublayers) layer_dict.update(new_sublayers) for k, v in layer_dict.items(): print(k, ":", v) #conv1d : Conv1D(3, 2, kernel_size=[3], data_format=NCL) #conv2d : Conv2D(4, 2, kernel_size=[4, 4], data_format=NCHW) #conv3d : Conv3D(4, 6, kernel_size=[3, 3, 3], data_format=NCDHW) #relu : ReLU()