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

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).

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)`