ij LdZddlmZddlmZedGddeZy)z"Adaptive Average Pooling 1D layer.) keras_export)BaseAdaptiveAveragePoolingz%keras.layers.AdaptiveAveragePooling1Dc$eZdZdZdfd ZxZS)AdaptiveAveragePooling1DaAdaptive average pooling operation for 1D temporal or spatial data. This layer applies an adaptive average pooling operation, which pools the input such that the output has a target length specified by `output_size`, regardless of the input length. The kernel size and stride are automatically computed to achieve the target output size. Args: output_size: Integer specifying the target output length. data_format: string, either `"channels_last"` or `"channels_first"`. `"channels_last"` corresponds to inputs with shape `(batch, length, channels)`. `"channels_first"` corresponds to inputs with shape `(batch, channels, length)`. Defaults to the value found in your Keras config file at `~/.keras/keras.json`. If never set, `"channels_last"` is used. Input shape: - If `data_format="channels_last"`: 3D tensor `(batch_size, length, channels)` - If `data_format="channels_first"`: 3D tensor `(batch_size, channels, length)` Output shape: - If `data_format="channels_last"`: `(batch_size, output_length, channels)` - If `data_format="channels_first"`: `(batch_size, channels, output_length)` Examples: >>> import numpy as np >>> input_seq = np.random.rand(1, 64, 3) >>> layer = AdaptiveAveragePooling1D(output_size=32) >>> output_seq = layer(input_seq) >>> output_seq.shape (1, 32, 3) c t|tr|f}nXt|ttfr(t |dk7rt d|t|}nt d|dt|t|$||fi|y)Nz@For 1D input, `output_size` tuple must have length 1. Received: zB`output_size` must be an integer or tuple of 1 integer. Received: z of type ) isinstanceinttuplelistlen ValueError TypeErrortypesuper__init__)self output_size data_formatkwargs __class__s /var/www/html/emotional.easysim.app/public_html/venv/lib/python3.12/site-packages/keras/src/layers/pooling/adaptive_average_pooling1d.pyrz!AdaptiveAveragePooling1D.__init__1s k3 '&.K  eT] 3;1$ !!, / ,K(M4 3D2EG  kr"s2(- 567=97=77=r