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a91020aed0
* initial documentation * rename mask to attention_mask * smaller tests * fixup * fix copies * move to time series section * sort docs * isort fix * batch_size is not a configuration * rename to TimesFMModelForPrediction * initial script * add check_outputs * remove dropout_rate * works with torch.Tensor inputs * rename script * fix docstrings * fix freq when window_size is given * add loss * fix _quantile_loss * formatting * fix isort * add weight init * add support for sdpa and flash_attention_2 * fixes for flash_attention * formatting * remove flash_attention * fix tests * fix file name * fix quantile loss * added initial TimesFMModelIntegrationTests * fix formatting * fix import order * fix _quantile_loss * add doc for SDPA * use timesfm 2.0 * bug fix in timesfm decode function. * compare mean forecasts * refactor type hints, use CamelCase * consolidate decode func * more readable code for weight conversion * fix-copies * simpler init * renaem TimesFmMLP * use T5LayerNorm * fix tests * use initializer_range * TimesFmModel instead of TimesFmDecoder * TimesFmPositionalEmbedding takes config for its init * 2.0-500m-pytorch default configs * use TimesFmModel * fix formatting * ignore TimesFmModel for testing * fix docstring * override generate as its not needed * add doc strings * fix logging * add docstrings to output data classes * initial copy from t5 * added config and attention layers * add TimesFMPositionalEmbedding * calcuate scale_factor once * add more configs and TimesFMResidualBlock * fix input_dims * standardize code format with black * remove unneeded modules * TimesFM Model * order of imports * copy from Google official implementation * remove covariate forecasting * Adapting TimesFM to HF format * restructing in progress * adapted to HF convention * timesfm test * the model runs * fixing unit tests * fixing unit tests in progress * add post_init * do not change TimesFMOutput * fixing unit tests * all unit tests passed * remove timesfm_layers * add intermediate_size and initialize with config * initial documentation * rename mask to attention_mask * smaller tests * fixup * fix copies * move to time series section * sort docs * isort fix * batch_size is not a configuration * rename to TimesFMModelForPrediction * initial script * add check_outputs * remove dropout_rate * works with torch.Tensor inputs * rename script * fix docstrings * fix freq when window_size is given * add loss * fix _quantile_loss * formatting * fix isort * add weight init * add support for sdpa and flash_attention_2 * fixes for flash_attention * formatting * remove flash_attention * fix tests * fix file name * fix quantile loss * added initial TimesFMModelIntegrationTests * fix formatting * fix import order * fix _quantile_loss * add doc for SDPA * use timesfm 2.0 * bug fix in timesfm decode function. * compare mean forecasts * refactor type hints, use CamelCase * consolidate decode func * more readable code for weight conversion * fix-copies * simpler init * renaem TimesFmMLP * use T5LayerNorm * fix tests * use initializer_range * TimesFmModel instead of TimesFmDecoder * TimesFmPositionalEmbedding takes config for its init * 2.0-500m-pytorch default configs * use TimesFmModel * fix formatting * ignore TimesFmModel for testing * fix docstring * override generate as its not needed * add doc strings * fix logging * add docstrings to output data classes * add _CHECKPOINT_FOR_DOC * fix comments * Revert "fix comments" This reverts commit |
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| _config.py | ||