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Functions625 in github.com/Dobiasd/frugally-deep

⨍ Functions 625◇ Types & classes 108
↓ 1 callersFunctionprepare_filter_weights_conv_1d_transpose
Change dimension order of 1d filter weights to the one used in fdeep
keras_export/convert_model.py:215
↓ 1 callersFunctionprepare_filter_weights_conv_2d_transpose
Change dimension order of 2d filter weights to the one used in fdeep
keras_export/convert_model.py:221
↓ 1 callersFunctionprepare_filter_weights_conv_3d
Change dimension order of 3d filter weights to the one used in fdeep
keras_export/convert_model.py:227
↓ 1 callersFunctionprepare_filter_weights_conv_3d_transpose
Change dimension order of 3d transpose filter weights to the one used in fdeep
keras_export/convert_model.py:233
↓ 1 callersFunctionreduce_single_axis
include/fdeep/tensor.hpp:743
↓ 1 callersFunctionreplace_none_with
Replace every None with a fixed value.
keras_export/convert_model.py:92
↓ 1 callersFunctionresize2d_area
include/fdeep/tensor.hpp:1108
↓ 1 callersFunctionresize3d_nearest
include/fdeep/tensor.hpp:976
↓ 1 callersFunctionreverse_size_dim_4_dimension
include/fdeep/convolution3d.hpp:182
↓ 1 callersMethodset_activation
include/fdeep/layers/layer.hpp:44
↓ 1 callersFunctionset_shape_idx_0_to_1_if_none
Change first element in tuple to 1.
keras_export/convert_model.py:134
↓ 1 callersFunctionshow_tensors
include/fdeep/tensor.hpp:1219
↓ 1 callersMethodshrink_rank
include/fdeep/tensor.hpp:115
↓ 1 callersMethodshrink_rank_with_min
include/fdeep/tensor.hpp:119
↓ 1 callersFunctionslice_along_axis
include/fdeep/tensor.hpp:721
↓ 1 callersFunctiontensor_into_bytes
Converts a tensor into a memory block holding 8-bit values. Data will be stored row-wise (and channels_last). Scales the values from range [low, high]
include/fdeep/tensor.hpp:1251
↓ 1 callersFunctiontensor_max_pos
include/fdeep/tensor.hpp:315
↓ 1 callersFunctiontensor_min_max_pos
include/fdeep/tensor.hpp:281
↓ 1 callersFunctiontensor_shape_equals_tensor_shape_variable
include/fdeep/tensor_shape.hpp:246
↓ 1 callersFunctionto_singleton_value
include/fdeep/tensor.hpp:184
Methodactivation_function
include/fdeep/layers/elu_layer.hpp:26
Methodactivation_function
include/fdeep/layers/celu_layer.hpp:26
Methodactivation_layer
include/fdeep/layers/activation_layer.hpp:26
Methodadapt_range
Adaptive pooling maps output index i to input range [floor(i * in / out), ceil((i+1) * in / out)). For length-1 input dimensions (which can occur for
include/fdeep/layers/adaptive_pooling_3d_layer.hpp:52
Methodadaptive_pooling_3d_layer
include/fdeep/layers/adaptive_pooling_3d_layer.hpp:26
Methodadd_bias
Adds bias broadcast over the configured bias_axes (a subset of rhs). Keras stores the bias variable with its dims in rhs char order, not in the litera
include/fdeep/layers/einsum_dense_layer.hpp:202
Methodadd_layer
include/fdeep/layers/add_layer.hpp:18
Methodadditive_attention_layer
include/fdeep/layers/additive_attention_layer.hpp:19
Methodapply_head
include/fdeep/layers/multi_head_attention_layer.hpp:74
Methodapply_impl
include/fdeep/layers/prelu_layer.hpp:29
Methodapply_impl
include/fdeep/layers/pooling_3d_layer.hpp:81
Methodapply_impl
include/fdeep/layers/rescaling_layer.hpp:34
Methodapply_impl
include/fdeep/layers/depthwise_conv_2d_layer.hpp:51
Methodapply_impl
include/fdeep/layers/centercrop_layer.hpp:28
Methodapply_impl
include/fdeep/layers/conv_2d_layer.hpp:44
Methodapply_impl
include/fdeep/layers/conv_lstm_3d_layer.hpp:69
Methodapply_impl
include/fdeep/layers/input_layer.hpp:25
Methodapply_impl
include/fdeep/layers/upsampling_2d_layer.hpp:32
Methodapply_impl
include/fdeep/layers/dot_layer.hpp:28
Methodapply_impl
include/fdeep/layers/concatenate_layer.hpp:25
Methodapply_impl
include/fdeep/layers/attention_layer.hpp:30
Methodapply_impl
include/fdeep/layers/upsampling_1d_layer.hpp:31
Methodapply_impl
include/fdeep/layers/conv_3d_transpose_layer.hpp:44
Methodapply_impl
include/fdeep/layers/subtract_layer.hpp:24
Methodapply_impl
include/fdeep/layers/global_pooling_layer.hpp:30
Methodapply_impl
include/fdeep/layers/einsum_dense_layer.hpp:224
Methodapply_impl
include/fdeep/layers/simple_rnn_layer.hpp:41
Methodapply_impl
include/fdeep/layers/zero_padding_3d_layer.hpp:36
Methodapply_impl
include/fdeep/layers/conv_lstm_2d_layer.hpp:84
Methodapply_impl
include/fdeep/layers/activation_layer.hpp:30
Methodapply_impl
include/fdeep/layers/dense_layer.hpp:44
Methodapply_impl
include/fdeep/layers/separable_conv_2d_layer.hpp:47
Methodapply_impl
include/fdeep/layers/resizing_layer.hpp:35
Methodapply_impl
include/fdeep/layers/multiply_layer.hpp:24
Methodapply_impl
include/fdeep/layers/model_layer.hpp:51
Methodapply_impl
include/fdeep/layers/conv_3d_layer.hpp:43
Methodapply_impl
include/fdeep/layers/repeat_vector_layer.hpp:27
Methodapply_impl
include/fdeep/layers/multi_head_attention_layer.hpp:98
Methodapply_impl
include/fdeep/layers/lstm_layer.hpp:43
Methodapply_impl
include/fdeep/layers/maximum_layer.hpp:24
Methodapply_impl
include/fdeep/layers/group_query_attention_layer.hpp:192
Methodapply_impl
include/fdeep/layers/upsampling_3d_layer.hpp:31
Methodapply_impl
include/fdeep/layers/unit_normalization_layer.hpp:28
Methodapply_impl
include/fdeep/layers/normalization_layer.hpp:37
Methodapply_impl
include/fdeep/layers/stacked_rnn_layer.hpp:33
Methodapply_impl
include/fdeep/layers/bidirectional_layer.hpp:53
Methodapply_impl
include/fdeep/layers/add_layer.hpp:24
Methodapply_impl
include/fdeep/layers/additive_attention_layer.hpp:26
Methodapply_impl
include/fdeep/layers/average_layer.hpp:24
Methodapply_impl
include/fdeep/layers/minimum_layer.hpp:24
Methodapply_impl
include/fdeep/layers/gru_layer.hpp:45
Methodapply_impl
include/fdeep/layers/permute_layer.hpp:27
Methodapply_impl
include/fdeep/layers/embedding_layer.hpp:31
Methodapply_impl
include/fdeep/layers/conv_2d_transpose_layer.hpp:44
Methodapply_impl
include/fdeep/layers/batch_normalization_layer.hpp:48
Methodapply_impl
include/fdeep/layers/layer_normalization_layer.hpp:37
Methodapply_impl
include/fdeep/layers/group_normalization_layer.hpp:42
Methodapply_impl
include/fdeep/layers/cropping_3d_layer.hpp:36
Methodapply_impl
include/fdeep/layers/flatten_layer.hpp:25
Methodapply_impl
include/fdeep/layers/rms_normalization_layer.hpp:35
Methodapply_impl
include/fdeep/layers/category_encoding_layer.hpp:31
Methodapply_impl
include/fdeep/layers/integer_lookup_layer.hpp:57
Methodapply_impl
include/fdeep/layers/discretization_layer.hpp:30
Methodapply_impl
include/fdeep/layers/time_distributed_layer.hpp:34
Methodapply_impl
include/fdeep/layers/reshape_layer.hpp:27
Methodapply_impl
include/fdeep/layers/adaptive_pooling_3d_layer.hpp:100
Methodapply_sigmoid_gate
include/fdeep/layers/group_query_attention_layer.hpp:156
Methodassert_is_shape_2
include/fdeep/tensor_shape.hpp:99
Methodassert_is_shape_3
include/fdeep/tensor_shape.hpp:106
Functionassert_model_type
(model: Model)
keras_export/convert_model.py:1004
Methodattention_distribution
Build the (T_q, T_k) softmax distribution for one query/kv-head pair.
include/fdeep/layers/group_query_attention_layer.hpp:96
Methodattention_layer
include/fdeep/layers/attention_layer.hpp:19
Methodaverage_layer
include/fdeep/layers/average_layer.hpp:18
Methodaverage_pooling_3d_layer
include/fdeep/layers/average_pooling_3d_layer.hpp:46
Methodbatch_normalization_layer
include/fdeep/layers/batch_normalization_layer.hpp:20
Methodbidirectional_layer
include/fdeep/layers/bidirectional_layer.hpp:19
Methodbuild_vocab_index
num_oov_indices > 1 needs Keras's FarmHash, which fdeep does not currently replicate. num_oov_indices == 0 ("strict" mode) raises on OOV, also unsuppo
include/fdeep/layers/integer_lookup_layer.hpp:45
Methodcategory_encoding_layer
include/fdeep/layers/category_encoding_layer.hpp:19
Methodcelu_layer
include/fdeep/layers/celu_layer.hpp:18
Methodcentercrop_layer
include/fdeep/layers/centercrop_layer.hpp:18
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