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feature(Inference): Created the inference process, added model saving. (#153)
* feat: Basic scaffolding up for inference process after training. * feat: Saving and loading models works. Inference works nearly. * feat: Added inference pipeline. * feat: Saving model now accoring to date and time; loading models now selects from latest file. Fixed the creation of dictionary of models. * feat: Added lightweight asset config, but full pipeline. * feat: Added new naming for dictionary. * fix: Fixed dictionary naming convention. * fix: Fixed naming again, now the model structure is good * fix: Changed the output path and the return values from run_pipeline. * feat: Added function to make sure folder exists for output models. Co-authored-by: Daniel Szemerey <szemereydaniel@gmail.com>
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@@ -8,6 +8,8 @@ __daily_etf = ["GLD", "IEF", "QQQ", "SPY", "TLT"]
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__daily_crypto = ["ADA_USD", "BCH_USD", "BNB_USD", "BTC_USD", "DOT_USD", "ETC_USD", "ETH_USD", "FIL_USD", "LTC_USD", "SOL_USD", "THETA_USD", "TRX_USD", "UNI_USD", "XLM_USD", "XRP_USD", "XTZ_USD"]
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__daily_crypto_lightweight = ["ADA_USD", "BCH_USD"]
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__hourly_crypto = ["BTC_USD", "DASH_USD", "ETC_USD", "ETH_USD", "LTC_USD", "TRX_USD", "XLM_USD", "XMR_USD", "XRP_USD"]
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__daily_glassnode = ['rhodl_ratio',
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@@ -41,6 +43,7 @@ __daily_glassnode = ['rhodl_ratio',
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data_collections = dict(
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daily_only_btc = transform_to_data_collection("data/daily_crypto", ['BTC_USD']),
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daily_crypto = transform_to_data_collection("data/daily_crypto", __daily_crypto),
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daily_crypto_lightweight = transform_to_data_collection("data/daily_crypto", __daily_crypto_lightweight),
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daily_etf = transform_to_data_collection("data/daily_etf", __daily_etf),
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hourly_crypto = transform_to_data_collection("data/hourly_crypto", __hourly_crypto),
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daily_glassnode =transform_to_data_collection("data/daily_glassnode", __daily_glassnode),
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