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* WIP. * Fix float32 conversion in OneHot preprocessor (would cause float64 in eager, then NN-matmul-failure). Add proper seq-len + state-in construction in eager_tf_policy.py::_compute_gradients(). * LINT. * eager_tf_policy.py: Only set samples["seq_lens"] if RNN. Otherwise, eager-tracing will throw flattened-dict key-mismatch error. * Move issue code to examples folder. Co-authored-by: Eric Liang <ekhliang@gmail.com>