shishishu
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| GATEWAY_FLAGS := -I. -I/usr/local/include -I$(GOPATH)/src/github.com/grpc-ecosystem/grpc-gateway/third_party/googleapis -I/usr/local/include | |
| GRPC_FLAGS := --python_out=. --grpc_python_out=. | |
| code: | |
| python -m grpc_tools.protoc $(GRPC_FLAGS) $(GATEWAY_FLAGS) *.proto | |
| gw: | |
| protoc $(GATEWAY_FLAGS) \ | |
| --go_out=Mgoogle/api/annotations.proto=github.com/grpc-ecosystem/grpc-gateway/third_party/googleapis/google/api,plugins=grpc:. \ |
siemanko
/ tf_lstm.py
Last active
November 22, 2025 10:34
Simple implementation of LSTM in Tensorflow in 50 lines (+ 130 lines of data generation and comments)
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| """Short and sweet LSTM implementation in Tensorflow. | |
| Motivation: | |
| When Tensorflow was released, adding RNNs was a bit of a hack - it required | |
| building separate graphs for every number of timesteps and was a bit obscure | |
| to use. Since then TF devs added things like `dynamic_rnn`, `scan` and `map_fn`. | |
| Currently the APIs are decent, but all the tutorials that I am aware of are not | |
| making the best use of the new APIs. | |
| Advantages of this implementation: |