o
    bi5	                     @   sD   d dl mZ d dlmZ d dlmZ eddgG dd deZdS )	    )ops)keras_export)BaseGlobalPoolingzkeras.layers.GlobalMaxPooling1Dzkeras.layers.GlobalMaxPool1Dc                       s*   e Zd ZdZd fdd	Zdd Z  ZS )	GlobalMaxPooling1Dal  Global max pooling operation for temporal data.

    Args:
        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"`.
        keepdims: A boolean, whether to keep the temporal dimension or not.
            If `keepdims` is `False` (default), the rank of the tensor is
            reduced for spatial dimensions. If `keepdims` is `True`, the
            temporal dimension are retained with length 1.
            The behavior is the same as for `tf.reduce_mean` or `np.mean`.

    Input shape:

    - If `data_format='channels_last'`:
        3D tensor with shape:
        `(batch_size, steps, features)`
    - If `data_format='channels_first'`:
        3D tensor with shape:
        `(batch_size, features, steps)`

    Output shape:

    - If `keepdims=False`:
        2D tensor with shape `(batch_size, features)`.
    - If `keepdims=True`:
        - If `data_format="channels_last"`:
            3D tensor with shape `(batch_size, 1, features)`
        - If `data_format="channels_first"`:
            3D tensor with shape `(batch_size, features, 1)`

    Example:

    >>> x = np.random.rand(2, 3, 4)
    >>> y = keras.layers.GlobalMaxPooling1D()(x)
    >>> y.shape
    (2, 4)
    NFc                    s   t  jdd||d| d S )N   )pool_dimensionsdata_formatkeepdims )super__init__)selfr   r	   kwargs	__class__r
   a/home/ubuntu/.local/lib/python3.10/site-packages/keras/src/layers/pooling/global_max_pooling1d.pyr   8   s   
zGlobalMaxPooling1D.__init__c                 C   s$   | j dkrdnd}tj||| jdS )Nchannels_lastr      )axisr	   )r   r   maxr	   )r   inputs
steps_axisr
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   r   call@   s   zGlobalMaxPooling1D.call)NF)__name__
__module____qualname____doc__r   r   __classcell__r
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   r   r   r      s    +r   N)	keras.srcr   keras.src.api_exportr   ,keras.src.layers.pooling.base_global_poolingr   r   r
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