tf.compat.v1.layers.flatten

Flattens an input tensor while preserving the batch axis (axis 0).

tf.compat.v1.layers.flatten(
    inputs, name=None, data_format='channels_last'
)

Migrate to TF2

This API is not compatible with eager execution ortf.function.

Please refer to tf.layers section of the migration guide to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2 layer is tf.keras.layers.Flatten.

Structural Mapping to Native TF2

None of the supported arguments have changed name.

Before:

 y = tf.compat.v1.layers.flatten(x)

After:

To migrate code using TF1 functional layers use the Keras Functional API:

 x = tf.keras.Input((28, 28, 1))
 y = tf.keras.layers.Flatten()(x)
 model = tf.keras.Model(x, y)

Description

Args
`inputs`	Tensor input.
`name`	The name of the layer (string).
`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, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`.

Returns
Reshaped tensor.

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)`