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Tf 214 #220
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Tf 214 #220
Commits on Feb 21, 2022
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Commits on Mar 13, 2022
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Commits on Mar 14, 2022
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Commits on Mar 19, 2022
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Commits on Mar 28, 2022
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Commits on Mar 30, 2022
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Commits on Apr 2, 2022
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Commits on Apr 3, 2022
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Commits on Apr 4, 2022
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dense function combines dydense/dyrelu/linearscaling/gating into one function
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Commits on Apr 8, 2022
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Add logit gating, dense_layer, stop file, make dyrelu slopes/intercepts trainable
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Commits on Apr 13, 2022
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Commits on Apr 23, 2022
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Weight gen (simple_gen) generates attention weights from each square by compressing then doing a batched dense to 64; buckets divides the training data based on material left.
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Merge pull request #1 from Ergodice/multiple-nets
Weight gen, buckets
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Commits on Apr 24, 2022
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dytalking_heads, fix visible device issue
Dytalking heads at this stage dynamically generates the projection matrices for the attention weights (same for all square pairs). Fixed set_visible_devices error by initializing tensorflow first in TFProcess and making DyDense temperature an instance attribute.
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Commits on Apr 26, 2022
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DyDense layers had issue saving sublayers so the design approach of the squeeze-excite layers is used, i.e., sublayers are moved outside into a function.
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Commits on May 8, 2022
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Fullgen compresses the tokens and combines them to extract global information into attention weights.
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Commits on May 12, 2022
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Commits on Aug 17, 2022
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Dytalking heads adds residual to matrix specifying linear transformation
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Commits on Aug 22, 2022
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Remove legacy code, add arc encoding and example yaml
Removed old modules which were not useful including yaml references, also removed legacy resnet code. Added arc's encoding with option in yaml and also added example.yaml
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Update Readme, remove old files
update Readme to describe talking heads, fullgen, and dynamic kernel methods. Removed leelalogs and configs, except for example.yaml.
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Commits on Aug 25, 2022
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Fixed typo in tfprocess and Readme, made some config stuff oprtional, fixed arc encoding, removed fullgen bias
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Commits on Sep 1, 2022
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Added search_loss, which is one over the prediction for the best move, and confident_accuracy, which is the accuracy for positions where there is a clear best move. Removed simple gating. Also updated README to include info on auxiliary losses.
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Commits on Nov 22, 2022
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Smolgen is more efficient version of fullgen, also added square relu which adds 0.5% pol acc
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Commits on Dec 12, 2022
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Merge branch 'attention-net-body' of https://github.com/Ergodice/lcze…
…ro-training into attention-net-body-ergo
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Commits on Dec 13, 2022
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Commits on Dec 14, 2022
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Merge pull request #2 from almaudoh/attention-net-body-smolgen
Smolgen protobuf updates
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Commits on Dec 25, 2022
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Nadam, RMSprop, better multigpu, onnx continuation
Nadam and RMSprop optimizers, ability to choose particular gpu's (not all or one gpu but 0, 1 out of 4 etc, onnx save folder naming changes to fix continuation failure bug)
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tfprocess.py typo fix in comment about net to model hack
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Commits on Dec 26, 2022
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Merge pull request #3 from teck45/patch-1
Nadam, RMSprop, better multigpu, onnx continuation
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policy rl is the amount of policy loss that can be reduced (i.e., policy loss minus entropy of target)
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FastDepthwise acts as a depthwise convolution but far faster. use_depthwise_process in the yaml adds a dense layer with sqrrelu activation followed by layer norm and FastDepthwise
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Commits on Jan 10, 2023
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FastLayerNormalization, switch layernorm alphas, mish activation, update depthwise process
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Commits on Jan 15, 2023
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Commits on Jan 31, 2023
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Reverted obsolete features and allowed ffn to be specified more cleanly
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Commits on Feb 25, 2023
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Commits on Feb 28, 2023
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make_value_buckets did not receive num_buckets
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Commits on Mar 2, 2023
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default activation was incorreclty set to None
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Commits on May 4, 2023
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RMSNorm support, value cat -> value error, more organized outputs (dict rather than tuple)
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Commits on May 5, 2023
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new stuff: ip_val_err and ip_emb_preproc. In the backend for the engine, RMSNorm and no norm at all should be recognized by the lack of beta/both gamma and beta
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Commits on May 6, 2023
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Didn't work before with gpus separated by commas
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Commits on May 14, 2023
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Setting p=x in quantized_conv gives it p bits of precision
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Used for regularization, was found to speed up training in Katago
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Commits on Oct 11, 2023
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Merge pull request #5 from almaudoh/attention-net-updates
Fix net.py to match current proto.
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