o i e|@sdZddlmZddlmZddlmZddlZddlmZddl m Z ddl m Z e d gd Gd d d ej e jZ e d gd    d0ddZe dgd Gdddeje jZe dgd    d0ddZe dgd Gdddeje jZe dgd    d0ddZe dgd Gdd d eje jZe d!gd    d0d"d#Ze d$gd Gd%d&d&eje jZe d'gd    d0d(d)Ze d*gd Gd+d,d,eje jZe d-gd    d0d.d/ZeZeZeZeZdS)1z@Contains the pooling layer classes and their functional aliases.)absolute_import)division)print_functionN)layers)base) keras_exportz1keras.__internal__.legacy.layers.AveragePooling1D)v1c(eZdZdZ   dfdd ZZS)AveragePooling1Da4Average Pooling layer for 1D inputs. Args: pool_size: An integer or tuple/list of a single integer, representing the size of the pooling window. strides: An integer or tuple/list of a single integer, specifying the strides of the pooling operation. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch, length, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, length)`. name: A string, the name of the layer. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.AveragePooling1D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python pooling = tf.compat.v1.layers.AveragePooling1D(pool_size=2, strides=2) ``` After: ```python pooling = tf.keras.layers.AveragePooling1D(pool_size=2, strides=2) ``` @end_compatibility valid channels_lastNc 2|durtdtjd|||||d|dSNz$Argument `strides` must not be None. pool_sizestridespadding data_formatname ValueErrorsuper__init__selfrrrrrkwargs __class__rQ/var/www/myenv/lib/python3.10/site-packages/keras/src/legacy_tf_layers/pooling.pyrP  zAveragePooling1D.__init__r r N__name__ __module__ __qualname____doc__r __classcell__rrrrr  4r z2keras.__internal__.legacy.layers.average_pooling1dr r cC(tjdddt|||||d}||S)aAverage Pooling layer for 1D inputs. Args: inputs: The tensor over which to pool. Must have rank 3. pool_size: An integer or tuple/list of a single integer, representing the size of the pooling window. strides: An integer or tuple/list of a single integer, specifying the strides of the pooling operation. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch, length, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, length)`. name: A string, the name of the layer. Returns: The output tensor, of rank 3. Raises: ValueError: if eager execution is enabled. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.AveragePooling1D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python y = tf.compat.v1.layers.average_pooling1d(x, pool_size=2, strides=2) ``` After: To migrate code using TF1 functional layers use the [Keras Functional API] (https://www.tensorflow.org/guide/keras/functional): ```python x = tf.keras.Input((28, 28, 1)) y = tf.keras.layers.AveragePooling1D(pool_size=2, strides=2)(x) model = tf.keras.Model(x, y) ``` @end_compatibility z`tf.layers.average_pooling1d` is deprecated and will be removed in a future version. Please use `tf.keras.layers.AveragePooling1D` instead. stacklevelr)warningswarnr inputsrrrrrlayerrrraverage_pooling1deDr2z-keras.__internal__.legacy.layers.MaxPooling1Dcr ) MaxPooling1Da$Max Pooling layer for 1D inputs. Args: pool_size: An integer or tuple/list of a single integer, representing the size of the pooling window. strides: An integer or tuple/list of a single integer, specifying the strides of the pooling operation. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch, length, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, length)`. name: A string, the name of the layer. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.MaxPooling1D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python pooling = tf.compat.v1.layers.MaxPooling1D(pool_size=2, strides=2) ``` After: ```python pooling = tf.keras.layers.MaxPooling1D(pool_size=2, strides=2) ``` @end_compatibility r r Nc r rrrrrrrr zMaxPooling1D.__init__r!r"rrrrr4r(r4z.keras.__internal__.legacy.layers.max_pooling1dcCr))aMax Pooling layer for 1D inputs. Args: inputs: The tensor over which to pool. Must have rank 3. pool_size: An integer or tuple/list of a single integer, representing the size of the pooling window. strides: An integer or tuple/list of a single integer, specifying the strides of the pooling operation. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch, length, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, length)`. name: A string, the name of the layer. Returns: The output tensor, of rank 3. Raises: ValueError: if eager execution is enabled. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.MaxPooling1D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python y = tf.compat.v1.layers.max_pooling1d(x, pool_size=2, strides=2) ``` After: To migrate code using TF1 functional layers use the [Keras Functional API] (https://www.tensorflow.org/guide/keras/functional): ```python x = tf.keras.Input((28, 28, 1)) y = tf.keras.layers.MaxPooling1D(pool_size=2, strides=2)(x) model = tf.keras.Model(x, y) ``` @end_compatibility z`tf.layers.max_pooling1d` is deprecated and will be removed in a future version. Please use `tf.keras.layers.MaxPooling1D` instead.r*r+r)r-r.r4r/rrr max_pooling1dr3r5z1keras.__internal__.legacy.layers.AveragePooling2Dcr )AveragePooling2Da Average pooling layer for 2D inputs (e.g. images). Args: pool_size: An integer or tuple/list of 2 integers: (pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 2 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`. name: A string, the name of the layer. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.AveragePooling2D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python pooling = tf.compat.v1.layers.AveragePooling2D(pool_size=2, strides=2) ``` After: ```python pooling = tf.keras.layers.AveragePooling2D(pool_size=2, strides=2) ``` @end_compatibility r r Nc r rrrrrrrr zAveragePooling2D.__init__r!r"rrrrr6T 8r6z2keras.__internal__.legacy.layers.average_pooling2dcCr))aAverage pooling layer for 2D inputs (e.g. images). Args: inputs: The tensor over which to pool. Must have rank 4. pool_size: An integer or tuple/list of 2 integers: (pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 2 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`. name: A string, the name of the layer. Returns: Output tensor. Raises: ValueError: if eager execution is enabled. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.AveragePooling2D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python y = tf.compat.v1.layers.average_pooling2d(x, pool_size=2, strides=2) ``` After: To migrate code using TF1 functional layers use the [Keras Functional API] (https://www.tensorflow.org/guide/keras/functional): ```python x = tf.keras.Input((28, 28, 1)) y = tf.keras.layers.AveragePooling2D(pool_size=2, strides=2)(x) model = tf.keras.Model(x, y) ``` @end_compatibility z`tf.layers.average_pooling2d` is deprecated and will be removed in a future version. Please use `tf.keras.layers.AveragePooling2D` instead.r*r+r)r-r.r6r/rrraverage_pooling2dHr8z-keras.__internal__.legacy.layers.MaxPooling2Dcr ) MaxPooling2DaMax pooling layer for 2D inputs (e.g. images). Args: pool_size: An integer or tuple/list of 2 integers: (pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 2 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`. name: A string, the name of the layer. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.MaxPooling2D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python pooling = tf.compat.v1.layers.MaxPooling2D(pool_size=2, strides=2) ``` After: ```python pooling = tf.keras.layers.MaxPooling2D(pool_size=2, strides=2) ``` @end_compatibility r r Nc r rrrrrrr-r zMaxPooling2D.__init__r!r"rrrrr:r7r:z.keras.__internal__.legacy.layers.max_pooling2dcCr))a{Max pooling layer for 2D inputs (e.g. images). Args: inputs: The tensor over which to pool. Must have rank 4. pool_size: An integer or tuple/list of 2 integers: (pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 2 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`. name: A string, the name of the layer. Returns: Output tensor. Raises: ValueError: if eager execution is enabled. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.MaxPooling2D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python y = tf.compat.v1.layers.max_pooling2d(x, pool_size=2, strides=2) ``` After: To migrate code using TF1 functional layers use the [Keras Functional API] (https://www.tensorflow.org/guide/keras/functional): ```python x = tf.keras.Input((28, 28, 1)) y = tf.keras.layers.MaxPooling2D(pool_size=2, strides=2)(x) model = tf.keras.Model(x, y) ``` @end_compatibility z`tf.layers.max_pooling2d` is deprecated and will be removed in a future version. Please use `tf.keras.layers.MaxPooling2D` instead.r*r+r)r-r.r:r/rrr max_pooling2dBr9r;z1keras.__internal__.legacy.layers.AveragePooling3Dcr )AveragePooling3DaKAverage pooling layer for 3D inputs (e.g. volumes). Args: pool_size: An integer or tuple/list of 3 integers: (pool_depth, pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 3 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, depth, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, depth, height, width)`. name: A string, the name of the layer. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.AveragePooling3D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python pooling = tf.compat.v1.layers.AveragePooling3D(pool_size=2, strides=2) ``` After: ```python pooling = tf.keras.layers.AveragePooling3D(pool_size=2, strides=2) ``` @end_compatibility r r Nc r rrrrrrrr zAveragePooling3D.__init__r!r"rrrrr< :r<z2keras.__internal__.legacy.layers.average_pooling3dcCr))aAverage pooling layer for 3D inputs (e.g. volumes). Args: inputs: The tensor over which to pool. Must have rank 5. pool_size: An integer or tuple/list of 3 integers: (pool_depth, pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 3 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, depth, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, depth, height, width)`. name: A string, the name of the layer. Returns: Output tensor. Raises: ValueError: if eager execution is enabled. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.AveragePooling3D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python y = tf.compat.v1.layers.average_pooling3d(x, pool_size=2, strides=2) ``` After: To migrate code using TF1 functional layers use the [Keras Functional API] (https://www.tensorflow.org/guide/keras/functional): ```python x = tf.keras.Input((28, 28, 1)) y = tf.keras.layers.AveragePooling3D(pool_size=2, strides=2)(x) model = tf.keras.Model(x, y) ``` @end_compatibility z`tf.layers.average_pooling3d` is deprecated and will be removed in a future version. Please use `tf.keras.layers.AveragePooling3D` instead.r*r+r)r-r.r<r/rrraverage_pooling3dsJr>z-keras.__internal__.legacy.layers.MaxPooling3Dcr ) MaxPooling3Da;Max pooling layer for 3D inputs (e.g. volumes). Args: pool_size: An integer or tuple/list of 3 integers: (pool_depth, pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 3 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, depth, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, depth, height, width)`. name: A string, the name of the layer. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.MaxPooling3D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python pooling = tf.compat.v1.layers.MaxPooling3D(pool_size=2, strides=2) ``` After: ```python pooling = tf.keras.layers.MaxPooling3D(pool_size=2, strides=2) ``` @end_compatibility r r Nc r rrrrrrryr zMaxPooling3D.__init__r!r"rrrrr?Ar=r?z.keras.__internal__.legacy.layers.max_pooling3dcCr))aMax pooling layer for 3D inputs (e.g. volumes). Args: inputs: The tensor over which to pool. Must have rank 5. pool_size: An integer or tuple/list of 3 integers: (pool_depth, pool_height, pool_width) specifying the size of the pooling window. Can be a single integer to specify the same value for all spatial dimensions. strides: An integer or tuple/list of 3 integers, specifying the strides of the pooling operation. Can be a single integer to specify the same value for all spatial dimensions. padding: A string. The padding method, either 'valid' or 'same'. Case-insensitive. data_format: A string. The ordering of the dimensions in the inputs. `channels_last` (default) and `channels_first` are supported. `channels_last` corresponds to inputs with shape `(batch, depth, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, depth, height, width)`. name: A string, the name of the layer. Returns: Output tensor. Raises: ValueError: if eager execution is enabled. @compatibility(TF2) This API is a legacy api that is only compatible with eager execution and `tf.function` if you combine it with `tf.compat.v1.keras.utils.track_tf1_style_variables` Please refer to [tf.layers model mapping section of the migration guide] (https://www.tensorflow.org/guide/migrate/model_mapping) to learn how to use your TensorFlow v1 model in TF2 with Keras. The corresponding TensorFlow v2 layer is `tf.keras.layers.MaxPooling3D`. #### Structural Mapping to Native TF2 None of the supported arguments have changed name. Before: ```python y = tf.compat.v1.layers.max_pooling3d(x, pool_size=2, strides=2) ``` After: To migrate code using TF1 functional layers use the [Keras Functional API] (https://www.tensorflow.org/guide/keras/functional): ```python x = tf.keras.Input((28, 28, 1)) y = tf.keras.layers.MaxPooling3D(pool_size=2, strides=2)(x) model = tf.keras.Model(x, y) ``` @end_compatibility z`tf.layers.max_pooling3d` is deprecated and will be removed in a future version. Please use `tf.keras.layers.MaxPooling3D` instead.r*r+r)r-r.r?r/rrr max_pooling3dsIr@r!)r& __future__rrrr- keras.srcr keras_layerskeras.src.legacy_tf_layersr tensorflow.python.util.tf_exportrr Layerr2r4r5r6r8r:r;r<r>r?r@ AvgPool2D MaxPool2D max_pool2d avg_pool2drrrrsl        F S F S J W J W L Y L Z