None of the supported arguments have changed name.
Before:
flatten=tf.compat.v1.layers.Flatten()
After:
flatten=tf.keras.layers.Flatten()
Description
Args
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, ..., channels) while channels_first corresponds to
inputs with shape (batch, channels, ...).
Examples:
x=tf.compat.v1.placeholder(shape=(None,4,4),dtype='float32')y=Flatten()(x)# now `y` has shape `(None, 16)`x=tf.compat.v1.placeholder(shape=(None,3,None),dtype='float32')y=Flatten()(x)# now `y` has shape `(None, None)`
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.compat.v1.layers.Flatten\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v2.13.1/keras/legacy_tf_layers/core.py#L425-L478) |\n\nFlattens an input tensor while preserving the batch axis (axis 0).\n\nInherits From: [`Flatten`](../../../../tf/keras/layers/Flatten), [`Layer`](../../../../tf/compat/v1/layers/Layer), [`Layer`](../../../../tf/keras/layers/Layer), [`Module`](../../../../tf/Module) \n\n tf.compat.v1.layers.Flatten(\n data_format=None, **kwargs\n )\n\n\u003cbr /\u003e\n\nMigrate to TF2\n--------------\n\n\u003cbr /\u003e\n\n| **Caution:** This API was designed for TensorFlow v1. Continue reading for details on how to migrate from this API to a native TensorFlow v2 equivalent. See the [TensorFlow v1 to TensorFlow v2 migration guide](https://www.tensorflow.org/guide/migrate) for instructions on how to migrate the rest of your code.\n\nThis API is a legacy api that is only compatible with eager execution and\n[`tf.function`](../../../../tf/function) if you combine it with\n[`tf.compat.v1.keras.utils.track_tf1_style_variables`](../../../../tf/compat/v1/keras/utils/track_tf1_style_variables)\n\nPlease refer to [tf.layers model mapping section of the migration guide](https://www.tensorflow.org/guide/migrate/model_mapping)\nto learn how to use your TensorFlow v1 model in TF2 with Keras.\n\nThe corresponding TensorFlow v2 layer is [`tf.keras.layers.Flatten`](../../../../tf/keras/layers/Flatten).\n\n#### Structural Mapping to Native TF2\n\nNone of the supported arguments have changed name.\n\nBefore: \n\n flatten = tf.compat.v1.layers.Flatten()\n\nAfter: \n\n flatten = tf.keras.layers.Flatten()\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nDescription\n-----------\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `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, ..., channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, ...)`. |\n\n\u003cbr /\u003e\n\n#### Examples:\n\n x = tf.compat.v1.placeholder(shape=(None, 4, 4), dtype='float32')\n y = Flatten()(x)\n # now `y` has shape `(None, 16)`\n\n x = tf.compat.v1.placeholder(shape=(None, 3, None), dtype='float32')\n y = Flatten()(x)\n # now `y` has shape `(None, None)`\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|--------------|---------------|\n| `graph` | \u003cbr /\u003e \u003cbr /\u003e |\n| `scope_name` | \u003cbr /\u003e \u003cbr /\u003e |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `apply`\n\n[View source](https://github.com/keras-team/keras/tree/v2.13.1/keras/legacy_tf_layers/base.py#L239-L240) \n\n apply(\n *args, **kwargs\n )\n\n### `get_losses_for`\n\n[View source](https://github.com/keras-team/keras/tree/v2.13.1/keras/engine/base_layer_v1.py#L1467-L1484) \n\n get_losses_for(\n inputs\n )\n\nRetrieves losses relevant to a specific set of inputs.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|----------------------------------------------|\n| `inputs` | Input tensor or list/tuple of input tensors. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| List of loss tensors of the layer that depend on `inputs`. ||\n\n\u003cbr /\u003e\n\n### `get_updates_for`\n\n[View source](https://github.com/keras-team/keras/tree/v2.13.1/keras/engine/base_layer_v1.py#L1448-L1465) \n\n get_updates_for(\n inputs\n )\n\nRetrieves updates relevant to a specific set of inputs.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|----------------------------------------------|\n| `inputs` | Input tensor or list/tuple of input tensors. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| List of update ops of the layer that depend on `inputs`. ||\n\n\u003cbr /\u003e"]]
View source on GitHub