It takes as input a list of tensors, all of the same shape except for the concatenation axis, and returns a single tensor that is the concatenation of all inputs.
Arguments
- inputs
layers to combine
- ...
Standard layer keyword arguments.
- axis
Axis along which to concatenate.
Examples
x <- op_arange(20) |> op_reshape(c(2, 2, 5))
y <- op_arange(21, 40) |> op_reshape(c(2, 2, 5))
layer_concatenate(x, y, axis = 2)## tf.Tensor(
## [[[ 1. 2. 3. 4. 5.]
## [ 6. 7. 8. 9. 10.]
## [21. 22. 23. 24. 25.]
## [26. 27. 28. 29. 30.]]
##
## [[11. 12. 13. 14. 15.]
## [16. 17. 18. 19. 20.]
## [31. 32. 33. 34. 35.]
## [36. 37. 38. 39. 40.]]], shape=(2, 4, 5), dtype=float32)
Usage in a Keras model:
x1 <- op_arange(10) |> op_reshape(c(5, 2)) |> layer_dense(8)
x2 <- op_arange(11, 20) |> op_reshape(c(5, 2)) |> layer_dense(8)
y <- layer_concatenate(x1, x2)See also
Other merging layers: layer_add() layer_average() layer_dot() layer_maximum() layer_minimum() layer_multiply() layer_subtract()
Other layers: Layer() layer_activation() layer_activation_elu() layer_activation_leaky_relu() layer_activation_parametric_relu() layer_activation_relu() layer_activation_softmax() layer_activity_regularization() layer_add() layer_additive_attention() layer_alpha_dropout() layer_attention() layer_aug_mix() layer_auto_contrast() layer_average() layer_average_pooling_1d() layer_average_pooling_2d() layer_average_pooling_3d() layer_batch_normalization() layer_bidirectional() layer_category_encoding() layer_center_crop() layer_conv_1d() layer_conv_1d_transpose() layer_conv_2d() layer_conv_2d_transpose() layer_conv_3d() layer_conv_3d_transpose() layer_conv_lstm_1d() layer_conv_lstm_2d() layer_conv_lstm_3d() layer_cropping_1d() layer_cropping_2d() layer_cropping_3d() layer_cut_mix() layer_dense() layer_depthwise_conv_1d() layer_depthwise_conv_2d() layer_discretization() layer_dot() layer_dropout() layer_einsum_dense() layer_embedding() layer_equalization() layer_feature_space() layer_flatten() layer_flax_module_wrapper() layer_gaussian_dropout() layer_gaussian_noise() layer_global_average_pooling_1d() layer_global_average_pooling_2d() layer_global_average_pooling_3d() layer_global_max_pooling_1d() layer_global_max_pooling_2d() layer_global_max_pooling_3d() layer_group_normalization() layer_group_query_attention() layer_gru() layer_hashed_crossing() layer_hashing() layer_identity() layer_integer_lookup() layer_jax_model_wrapper() layer_lambda() layer_layer_normalization() layer_lstm() layer_masking() layer_max_num_bounding_boxes() layer_max_pooling_1d() layer_max_pooling_2d() layer_max_pooling_3d() layer_maximum() layer_mel_spectrogram() layer_minimum() layer_mix_up() layer_multi_head_attention() layer_multiply() layer_normalization() layer_permute() layer_rand_augment() layer_random_brightness() layer_random_color_degeneration() layer_random_color_jitter() layer_random_contrast() layer_random_crop() layer_random_erasing() layer_random_flip() layer_random_gaussian_blur() layer_random_grayscale() layer_random_hue() layer_random_invert() layer_random_perspective() layer_random_posterization() layer_random_rotation() layer_random_saturation() layer_random_sharpness() layer_random_shear() layer_random_translation() layer_random_zoom() layer_repeat_vector() layer_rescaling() layer_reshape() layer_resizing() layer_rms_normalization() layer_rnn() layer_separable_conv_1d() layer_separable_conv_2d() layer_simple_rnn() layer_solarization() layer_spatial_dropout_1d() layer_spatial_dropout_2d() layer_spatial_dropout_3d() layer_spectral_normalization() layer_stft_spectrogram() layer_string_lookup() layer_subtract() layer_text_vectorization() layer_tfsm() layer_time_distributed() layer_torch_module_wrapper() layer_unit_normalization() layer_upsampling_1d() layer_upsampling_2d() layer_upsampling_3d() layer_zero_padding_1d() layer_zero_padding_2d() layer_zero_padding_3d() rnn_cell_gru() rnn_cell_lstm() rnn_cell_simple() rnn_cells_stack()