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36 <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 15rem; margin-top: .5rem; margin-left 13px"/>
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Nikhil Raj1dc83fe2024-05-16 09:47:51 +0100[diff] [blame]39 &#160;<span id="projectnumber">24.05</span>
Nikhil Raj03c7ff32023-08-22 12:00:04 +0100[diff] [blame]40 </div>
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93
94<div class="contents">
95<div class="textblock">Here is a list of all class members with links to the classes they belong to:</div>
96
97<h3><a id="index_f"></a>- f -</h3><ul>
98<li>FactoryFunction
99: <a class="el" href="classarmnn_1_1_backend_registry.html#aa33ac375677ee8436456a585dd6f68d9">BackendRegistry</a>
100</li>
101<li>FactoryId
102: <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory</a>
103</li>
104<li>FactoryStorage
105: <a class="el" href="classarmnn_1_1_backend_registry.html#a20fb10b59fccc99291e7fe993cd814bb">BackendRegistry</a>
106</li>
107<li>FakeQuantizationDescriptor()
108: <a class="el" href="structarmnn_1_1_fake_quantization_descriptor.html#a07e9336ef20ef3348c954f620d9a31f3">FakeQuantizationDescriptor</a>
109</li>
110<li>FakeQuantizationLayer()
111: <a class="el" href="classarmnn_1_1_fake_quantization_layer.html#a1ced02069893e08574433978a7ecd55b">FakeQuantizationLayer</a>
112</li>
113<li>FakeQuantizationQueueDescriptor()
114: <a class="el" href="structarmnn_1_1_fake_quantization_queue_descriptor.html#a275fbb91c39758c86dc9426cf40b3903">FakeQuantizationQueueDescriptor</a>
115</li>
116<li>fbb_
117: <a class="el" href="structarmnn_1_1_cl_context_builder.html#a97a08cdc2145003f012dd9dc6839627c">ClContextBuilder</a>
118, <a class="el" href="structarmnn_1_1_program_builder.html#a97a08cdc2145003f012dd9dc6839627c">ProgramBuilder</a>
119</li>
120<li>FileLine()
121: <a class="el" href="structarmnn_1_1_check_location.html#ac1184445a1323e07e0da084a54aec535">CheckLocation</a>
122</li>
123<li>FillDescriptor()
124: <a class="el" href="structarmnn_1_1_fill_descriptor.html#ab424db19258eeff7f27ff87e9b74bf5e">FillDescriptor</a>
125</li>
126<li>FillLayer()
127: <a class="el" href="classarmnn_1_1_fill_layer.html#ad6e7b358fc6cac001f14d5b465b546d9">FillLayer</a>
128</li>
129<li>Finish()
130: <a class="el" href="structarmnn_1_1_cl_context_builder.html#aff108affe64f8866613fe9581ab883dd">ClContextBuilder</a>
131, <a class="el" href="structarmnn_1_1_program_builder.html#ac1457929dc85df13e80c1822b1ab282c">ProgramBuilder</a>
132</li>
133<li>FinishStrategy()
134: <a class="el" href="classarmnn_1_1_i_strategy.html#adf2f7effbf860b32e9a4ef2a73f84190">IStrategy</a>
135</li>
136<li>first_argument_type
137: <a class="el" href="structarmnn_1_1maximum.html#a9e9bfdf07be793850c9f72f5907c5ab9">maximum&lt; T &gt;</a>
138, <a class="el" href="structarmnn_1_1minimum.html#a9e9bfdf07be793850c9f72f5907c5ab9">minimum&lt; T &gt;</a>
139, <a class="el" href="structarmnn_1_1power.html#a9e9bfdf07be793850c9f72f5907c5ab9">power&lt; T &gt;</a>
140, <a class="el" href="structarmnn_1_1squared_difference.html#a9e9bfdf07be793850c9f72f5907c5ab9">squaredDifference&lt; T &gt;</a>
141</li>
142<li>FirstInputTypedWorkload()
143: <a class="el" href="classarmnn_1_1_first_input_typed_workload.html#a25445e32b355feb06cd17f31667e0ecd">FirstInputTypedWorkload&lt; QueueDescriptor, DataType &gt;</a>
144</li>
145<li>Float16Decoder()
146: <a class="el" href="classarmnn_1_1_float16_decoder.html#ae32147bae37227ffbd320fd9056a6696">Float16Decoder</a>
147</li>
148<li>Float16Encoder()
149: <a class="el" href="classarmnn_1_1_float16_encoder.html#abb210b769f62a2b8e3d5cd4ca93e866c">Float16Encoder</a>
150</li>
151<li>Float32Decoder()
152: <a class="el" href="classarmnn_1_1_float32_decoder.html#a6ff91a91407c5bb2d912a6aba510fdea">Float32Decoder</a>
153</li>
154<li>Float32Encoder()
155: <a class="el" href="classarmnn_1_1_float32_encoder.html#a5e0071e4be4f33494b05240304d8eb5b">Float32Encoder</a>
156</li>
157<li>Float32ToBFloat16()
158: <a class="el" href="classarmnn_1_1_b_float16.html#a3ff08d61c8f7403c9f790e2b96d91a9d">BFloat16</a>
159</li>
160<li>FloorLayer()
161: <a class="el" href="classarmnn_1_1_floor_layer.html#abc0b06adfadf3c59b4f91640cc791c36">FloorLayer</a>
162</li>
163<li>FoldPadIntoConvolution2dImpl()
164: <a class="el" href="classarmnn_1_1optimizations_1_1pad__fold_1_1_fold_pad_into_convolution2d_impl.html#a008dac8de51c0f701621e64c91c6b9f8">FoldPadIntoConvolution2dImpl</a>
165</li>
166<li>FoldPadIntoDepthwiseConvolution2dImpl()
167: <a class="el" href="classarmnn_1_1optimizations_1_1pad__fold_1_1_fold_pad_into_depthwise_convolution2d_impl.html#aaca45051409c6c4abacece8ad7b56c14">FoldPadIntoDepthwiseConvolution2dImpl</a>
168</li>
169<li>FoldPadIntoPooling2dImpl()
170: <a class="el" href="classarmnn_1_1optimizations_1_1pad__fold_1_1_fold_pad_into_pooling2d_impl.html#ac299be827c8031d777d2b0a5b721a3ae">FoldPadIntoPooling2dImpl</a>
171</li>
172<li>ForEachIConnectableLayer()
173: <a class="el" href="classarmnn_1_1_subgraph_view.html#a89db17358856d60f03966a0e2e8cb25c">SubgraphView</a>
174</li>
175<li>ForEachLayer()
176: <a class="el" href="classarmnn_1_1_graph.html#ad6521013ad981519904822f2ada2c4ec">Graph</a>
177, <a class="el" href="classarmnn_1_1_subgraph_view.html#ad6521013ad981519904822f2ada2c4ec">SubgraphView</a>
178</li>
179<li>free()
180: <a class="el" href="classarmnn_1_1_cl_backend_1_1_cl_backend_custom_allocator_wrapper.html#abbd17af5b3fbeff226e4051433c1b929">ClBackend::ClBackendCustomAllocatorWrapper</a>
181, <a class="el" href="classarmnn_1_1_cl_backend_default_allocator.html#abbd17af5b3fbeff226e4051433c1b929">ClBackendDefaultAllocator</a>
182, <a class="el" href="classarmnn_1_1_default_allocator.html#abbd17af5b3fbeff226e4051433c1b929">DefaultAllocator</a>
183</li>
184<li>Free()
185: <a class="el" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.html#a49db2bfde3ca4fac7d1042a3aa5778aa">IWorkingMemHandle</a>
186, <a class="el" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a2688c89e6bdec61e0f483d9be6fd688c">WorkingMemHandle</a>
187</li>
188<li>free()
Nikhil Raj38b600d2024-02-15 15:02:19 +0000[diff] [blame]189: <a class="el" href="classarmnn_1_1_gpu_fsa_backend_1_1_gpu_fsa_backend_custom_allocator_wrapper.html#abbd17af5b3fbeff226e4051433c1b929">GpuFsaBackend::GpuFsaBackendCustomAllocatorWrapper</a>
190, <a class="el" href="classarmnn_1_1_gpu_fsa_backend_default_allocator.html#abbd17af5b3fbeff226e4051433c1b929">GpuFsaBackendDefaultAllocator</a>
191, <a class="el" href="classarmnn_1_1_i_custom_allocator.html#a7dbeba9295a3f52ea54698c31e555dff">ICustomAllocator</a>
Nikhil Raj03c7ff32023-08-22 12:00:04 +0100[diff] [blame]192</li>
193<li>FreeWorkingMemory()
194: <a class="el" href="classarmnn_1_1_loaded_network.html#aaf8558a23ae9be6e7ea165989f1fa808">LoadedNetwork</a>
195</li>
196<li>FullyConnectedDescriptor()
197: <a class="el" href="structarmnn_1_1_fully_connected_descriptor.html#ab70cd7344da13580556ea1af358a8a8b">FullyConnectedDescriptor</a>
198</li>
199<li>FullyConnectedLayer()
200: <a class="el" href="classarmnn_1_1_fully_connected_layer.html#a88ae76d1f14ba0eaf81701eb38e3682a">FullyConnectedLayer</a>
201</li>
202<li>Func()
203: <a class="el" href="structarmnn_1_1optimizations_1_1_float16_to_float32.html#a0617fdc915ac5caefaf3e4e78a7f28a2">Float16ToFloat32</a>
204, <a class="el" href="structarmnn_1_1optimizations_1_1_float32_to_float16.html#a0617fdc915ac5caefaf3e4e78a7f28a2">Float32ToFloat16</a>
205</li>
206<li>FuseBatchNorm()
207: <a class="el" href="classarmnn_1_1optimizations_1_1_fuse_batch_norm.html#abe49327783cb8bdc12c085c987db14db">FuseBatchNorm&lt; ConvLayer, ArmnnType, T &gt;</a>
208</li>
Nikhil Raj6f92c8e2023-11-22 11:41:15 +0000[diff] [blame]209<li>FusedDescriptor()
210: <a class="el" href="structarmnn_1_1_fused_descriptor.html#ae1331e1a851068243183fce2040d566d">FusedDescriptor</a>
211</li>
212<li>FusedLayer()
213: <a class="el" href="classarmnn_1_1_fused_layer.html#a084fce3d6b96b1c0bf9de5901201da93">FusedLayer</a>
214</li>
Nikhil Raj03c7ff32023-08-22 12:00:04 +0100[diff] [blame]215</ul>
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Nikhil Raj1dc83fe2024-05-16 09:47:51 +0100[diff] [blame]221 <li class="footer">Generated on Thu May 16 2024 09:32:01 for Arm NN by
Nikhil Raj03c7ff32023-08-22 12:00:04 +0100[diff] [blame]222 <a href="http://www.doxygen.org/index.html">
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