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| "binary_crossentropy", |
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| delayed_r_to_py_R6ClassGenerator |
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| format.keras.engine.training.Model |
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| freeze_weights |
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| install_keras |
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| isFALSE |
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|
| is_keras_implementation |
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| is_keras_tensor |
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| is_layer |
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| is_mac_arm64 |
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| is_main_thread_generator |
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| is_main_thread_generator.default |
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| is_main_thread_generator.function |
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| is_main_thread_generator.keras.preprocessing.image.Iterator |
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| is_main_thread_generator.keras_preprocessing.image.Iterator |
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| is_main_thread_generator.keras_preprocessing.sequence.Timeseries |
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| is_main_thread_generator.tensorflow.python.data.ops.dataset_ops. |
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| is_marked_active |
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| is_osx |
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| is_scalar |
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| is_tensorflow_dataset |
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| k_abs |
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| k_repeat |
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| k_repeat_elements |
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| k_reset_uids |
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| k_reshape |
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| k_resize_images |
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| k_resize_volumes |
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| k_reverse |
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| k_rnn |
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| k_round |
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| k_separable_conv2d |
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| k_set_epsilon |
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| k_set_floatx |
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| k_set_session |
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| k_shape |
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| k_sigmoid |
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| k_sign |
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| k_sin |
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| k_softmax |
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| k_softplus |
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| k_softsign |
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| k_sparse_categorical_crossentropy |
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| k_spatial_2d_padding |
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| k_sqrt |
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| k_square |
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| k_squeeze |
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| k_stack |
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| k_std |
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| k_stop_gradient |
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| k_sum |
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| k_switch |
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| k_tanh |
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| k_temporal_padding |
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| k_tile |
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| k_to_dense |
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| k_transpose |
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| k_truncated_normal |
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| k_unstack |
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| k_update |
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| k_update_add |
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| k_update_sub |
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| k_var |
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| k_variable |
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| k_zeros |
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| k_zeros_like |
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| keras |
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| keras_model_sequential |
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| keras_not_found_message |
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| keras_training_history |
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| keras_version |
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| layer_activation |
Man page
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| layer_activation_elu |
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| layer_activation_leaky_relu |
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| layer_activation_parametric_relu |
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| layer_activation_relu |
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| layer_activation_selu |
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| layer_activation_softmax |
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| layer_activation_thresholded_relu |
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| layer_activity_regularization |
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| layer_add |
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| layer_additive_attention |
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| layer_alpha_dropout |
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| layer_attention |
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| layer_average |
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| layer_average_pooling_1d |
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| layer_average_pooling_2d |
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| layer_average_pooling_3d |
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| layer_batch_normalization |
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| layer_category_encoding |
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| layer_center_crop |
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| layer_concatenate |
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| layer_conv_1d |
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| layer_conv_1d_transpose |
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| layer_conv_2d |
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| layer_conv_2d_transpose |
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| layer_conv_3d |
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| layer_conv_3d_transpose |
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| layer_conv_lstm_1d |
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| layer_conv_lstm_2d |
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| layer_conv_lstm_3d |
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| layer_cropping_1d |
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| layer_cropping_2d |
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| layer_cropping_3d |
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| layer_cudnn_gru |
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| layer_cudnn_lstm |
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| layer_dense |
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| layer_dense_features |
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| layer_depthwise_conv_1d |
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| layer_depthwise_conv_2d |
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| layer_discretization |
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| layer_dot |
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| layer_dropout |
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| layer_embedding |
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| layer_flatten |
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| layer_gaussian_dropout |
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| layer_gaussian_noise |
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| layer_global_average_pooling_1d |
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| layer_global_average_pooling_2d |
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| layer_global_average_pooling_3d |
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| layer_global_max_pooling_1d |
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| layer_global_max_pooling_2d |
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| layer_global_max_pooling_3d |
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| layer_gru |
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| layer_gru_cell |
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| layer_hashing |
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| layer_input |
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| layer_integer_lookup |
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| layer_lambda |
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| layer_layer_normalization |
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| layer_locally_connected_1d |
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| layer_locally_connected_2d |
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| layer_lstm |
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| layer_lstm_cell |
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| layer_masking |
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| layer_max_pooling_1d |
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| layer_max_pooling_2d |
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| layer_max_pooling_3d |
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| layer_maximum |
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| layer_minimum |
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| layer_multi_head_attention |
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| layer_multiply |
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| layer_permute |
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| layer_random_zoom |
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| layer_repeat_vector |
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| layer_rescaling |
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| layer_reshape |
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| layer_resizing |
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| layer_rnn |
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| layer_separable_conv_1d |
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| layer_separable_conv_2d |
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| layer_simple_rnn |
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| layer_simple_rnn_cell |
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| layer_spatial_dropout_1d |
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| layer_spatial_dropout_2d |
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| layer_spatial_dropout_3d |
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| layer_stacked_rnn_cells |
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| layer_string_lookup |
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| layer_subtract |
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| layer_text_vectorization |
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| layer_unit_normalization |
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| layer_upsampling_1d |
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| layer_upsampling_2d |
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| layer_upsampling_3d |
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| layer_zero_padding_1d |
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| layer_zero_padding_2d |
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| layer_zero_padding_3d |
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| learning_rate_schedule_cosine_decay |
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| learning_rate_schedule_cosine_decay_restarts |
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| learning_rate_schedule_exponential_decay |
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| learning_rate_schedule_inverse_time_decay |
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| learning_rate_schedule_piecewise_constant_decay |
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| learning_rate_schedule_polynomial_decay |
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| load_model |
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| load_model_hdf5 |
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| load_model_tf |
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| load_model_weights_hdf5 |
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| load_model_weights_tf |
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| load_text_tokenizer |
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| loss-functions |
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| loss_binary_crossentropy |
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| loss_categorical_crossentropy |
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| loss_categorical_hinge |
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| loss_cosine_proximity |
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| loss_cosine_similarity |
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| loss_hinge |
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| loss_huber |
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| loss_kl_divergence |
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| loss_kullback_leibler_divergence |
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| loss_logcosh |
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| loss_mean_absolute_error |
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| loss_mean_absolute_percentage_error |
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| loss_mean_squared_error |
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| loss_mean_squared_logarithmic_error |
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| loss_poisson |
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| loss_sparse_categorical_crossentropy |
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| loss_squared_hinge |
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| make_sampling_table |
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| mark_active |
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| maybe_delayed_r_to_py_R6ClassGenerator |
Source code
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| metric-or-Metric |
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| metric_accuracy |
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| metric_auc |
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| metric_binary_accuracy |
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| metric_binary_crossentropy |
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| metric_categorical_accuracy |
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| metric_categorical_crossentropy |
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| metric_categorical_hinge |
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| metric_cosine_proximity |
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| metric_cosine_similarity |
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| metric_false_negatives |
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| metric_false_positives |
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| metric_hinge |
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| metric_kullback_leibler_divergence |
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| metric_logcosh_error |
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| metric_mean |
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| metric_mean_absolute_error |
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| metric_mean_absolute_percentage_error |
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| metric_mean_iou |
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| metric_mean_relative_error |
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| metric_mean_squared_error |
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| metric_mean_squared_logarithmic_error |
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| metric_mean_tensor |
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| metric_mean_wrapper |
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| metric_poisson |
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| metric_precision |
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| metric_precision_at_recall |
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| metric_recall |
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| metric_recall_at_precision |
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| metric_root_mean_squared_error |
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| metric_sensitivity_at_specificity |
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| metric_sparse_categorical_accuracy |
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| metric_sparse_categorical_crossentropy |
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| metric_sparse_top_k_categorical_accuracy |
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| metric_specificity_at_sensitivity |
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| metric_squared_hinge |
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| metric_sum |
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| metric_top_k_categorical_accuracy |
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| metric_true_negatives |
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| metric_true_positives |
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| mobilenet_decode_predictions |
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| mobilenet_load_model_hdf5 |
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| mobilenet_preprocess_input |
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| mobilenet_v2_decode_predictions |
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| mobilenet_v2_load_model_hdf5 |
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| mobilenet_v2_preprocess_input |
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| model_from_json |
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| model_from_saved_model |
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|
| model_from_yaml |
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| model_to_json |
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| model_to_saved_model |
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| model_to_yaml |
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Source code
|
| multi_gpu_model |
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Source code
|
| nasnet_preprocess_input |
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| new_application_resnet_wrapper |
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| new_callback_class |
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| new_get_private |
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| new_layer_class |
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| new_learning_rate_schedule_class |
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| new_loss_class |
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| new_metric_class |
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| new_model_class |
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| new_py_class |
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| normalize |
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| normalize_callbacks |
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| normalize_callbacks_with_metrics |
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| normalize_cropping |
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| normalize_padding |
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| normalize_path |
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| normalize_scale |
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| normalize_shape |
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| objects_with_py_function_names |
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| optimizer_adadelta |
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| optimizer_adagrad |
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| optimizer_adam |
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| optimizer_adamax |
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| optimizer_ftrl |
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| optimizer_nadam |
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| optimizer_rmsprop |
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| optimizer_sgd |
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| pad_sequences |
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| plot.keras.engine.training.Model |
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Source code
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| plot.keras_training_history |
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| pop_layer |
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| predict.keras.engine.training.Model |
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| predict_classes |
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| predict_generator |
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| predict_generator_legacy |
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| predict_on_batch |
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| predict_proba |
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| preprocess_input |
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| print.keras.engine.training.Model |
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| print.keras_training_history |
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| print.kerastools.model.RModel |
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| print.py_R6ClassGenerator |
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| py_callable_as_function2 |
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| py_class |
Man page
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| py_formals |
Source code
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| py_metric_wrapper |
Source code
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| py_str.keras.engine.training.Model |
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| py_to_r.keras.utils.generic_utils.SharedObjectConfig |
Source code
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| py_to_r_wrapper.keras.engine.base_layer.Layer |
Source code
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| py_to_r_wrapper.keras.engine.training.Model |
Source code
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| py_to_r_wrapper.kerastools.model.RModel |
Source code
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| r_formals_to_py__signature__ |
Source code
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| r_to_py.R6ClassGenerator |
Source code
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| r_to_py.keras_layer_wrapper |
Source code
|
| reexports |
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|
| regularizer_l1 |
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Source code
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| regularizer_l1_l2 |
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| regularizer_l2 |
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| regularizer_orthogonal |
Man page
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| relative_to |
Source code
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| reload_model |
Source code
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| rename_to_dunder |
Source code
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| require_tf_version |
Source code
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| reset_states |
Man page
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| resnet_preprocess_input |
Man page
Source code
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| resnet_v2_preprocess_input |
Man page
Source code
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| resolve_callbacks |
Source code
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| resolve_implementation_module |
Source code
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| resolve_input_data |
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| resolve_main_thread_generators |
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| resolve_py_type_inherits |
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| resolve_tensorflow_dataset |
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| resolve_utils |
Source code
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| resolve_validation_data |
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| resolve_view_metrics |
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| run_dir |
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| save_model_hdf5 |
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| save_model_tf |
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| save_model_weights_hdf5 |
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| save_model_weights_tf |
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| save_text_tokenizer |
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Source code
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| sequences_to_matrix |
Man page
Source code
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| sequential_model_input_layer |
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Source code
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| serialize_model |
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Source code
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| set_vocabulary |
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| set_weights |
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| shape |
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| skipgrams |
Man page
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| split_dots_named_unnamed |
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| summary.keras.engine.training.Model |
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| summary.kerastools.model.RModel |
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| tensorboard |
Man page
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| tensorflow_on_before_use_session |
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| tensorflow_on_use_session |
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| test_on_batch |
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| text_dataset_from_directory |
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| text_hashing_trick |
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| text_one_hot |
Man page
Source code
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| text_to_word_sequence |
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| text_tokenizer |
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Source code
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| texts_to_matrix |
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| texts_to_sequences |
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Source code
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| texts_to_sequences_generator |
Man page
Source code
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| time_distributed |
Man page
Source code
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| timeseries_dataset_from_array |
Man page
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| timeseries_generator |
Man page
Source code
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| to_categorical |
Man page
Source code
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| to_keras_training_history |
Source code
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| train_on_batch |
Man page
Source code
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| tuple |
Man page
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| type_sum.py_R6ClassGenerator |
Source code
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| unfreeze_weights |
Man page
Source code
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| unserialize_model |
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Source code
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| use_backend |
Man page
Source code
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| use_condaenv |
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| use_implementation |
Man page
Source code
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| use_python |
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| use_session_with_seed |
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| use_virtualenv |
Man page
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| verify_application_prerequistes |
Source code
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| warn_callback |
Source code
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| with_custom_object_scope |
Man page
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| write_history_metadata |
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| xception_preprocess_input |
Man page
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| zip_lists |
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