src/gluonts/mx/util.py (8 lines):
	- line 210: # FIXME: we persist input/output formats of hybrid blocks as mxnet does not
	- line 211: # FIXME: https://github.com/apache/incubator-mxnet/issues/17488
	- line 247: # FIXME: prevents mxnet from failing with empty saved parameters list
	- line 248: # FIXME: https://github.com/apache/incubator-mxnet/issues/17488
	- line 255: # FIXME: mx.gluon.SymbolBlock cannot infer float_type and uses default np.float32
	- line 256: # FIXME: https://github.com/apache/incubator-mxnet/issues/11849
	- line 264: # FIXME: try to retrieve input/output format
	- line 265: # FIXME: https://github.com/apache/incubator-mxnet/issues/17488


src/gluonts/dataset/common.py (8 lines):
	- line 216: # TODO: given that we only support json, should we also filter json
	- line 217: # TODO: in the extension?
	- line 271: # TODO: find out whether this is a duplicate
	- line 367: # TODO: find a fast way to assert absence of nans.
	- line 401: # TODO: create a FormatDescriptor object that can be derived from a
	- line 402: # TODO: Metadata and pass it instead of freq.
	- line 403: # TODO: In addition to passing freq, the descriptor should be carry
	- line 404: # TODO: information about required features.


src/gluonts/evaluation/backtest.py (6 lines):
	- line 97: # TODO filter out time series with target shorter than prediction length
	- line 98: # TODO or fix the evaluator so it supports missing values instead (all
	- line 99: # TODO the test set may be gone otherwise with such a filtering)
	- line 187: # TODO does it make sense to have this then?
	- line 211: ),  # TODO: use load
	- line 214: ),  # TODO: use load


src/gluonts/nursery/autogluon_tabular/predictor.py (6 lines):
	- line 72: # TODO check if anything can be optimized here
	- line 211: # TODO clean up
	- line 212: # TODO optimize
	- line 262: # TODO clean up
	- line 263: # TODO optimize
	- line 385: # TODO this is temporary, we should make the callable object serializable in the first place


src/gluonts/nursery/SCott/pts/evaluation/backtest.py (5 lines):
	- line 89: # TODO filter out time series with target shorter than prediction length
	- line 90: # TODO or fix the evaluator so it supports missing values instead (all
	- line 91: # TODO the test set may be gone otherwise with such a filtering)
	- line 217: #             ),  # TODO: use load
	- line 220: #             ),  # TODO: use load


src/gluonts/mx/trainer/_base.py (5 lines):
	- line 152: # TODO param disable_default_callbacks to get backwards compatibility
	- line 210: # TODO the following is done for backwards compatibility. For future
	- line 240: ) -> None:  # TODO: we may want to return some training information here
	- line 293: kvstore="device",  # FIXME: initialize properly
	- line 474: )  # TODO: handle possible exception


src/gluonts/mx/distribution/isqf.py (4 lines):
	- line 220: # TODO: update to mxnet cumsum when it supports axis=-1
	- line 901: # TODO: update to mxnet cumsum when it supports axis=-1
	- line 951: # FIXME number 1
	- line 968: # FIXME number 2


src/gluonts/model/seq2seq/_seq2seq_network.py (4 lines):
	- line 146: # TODO: there used to be "nansum" here, to be fully equivalent we
	- line 147: # TODO: should have a "nanmean" here
	- line 148: # TODO: shouldn't we sum and divide by the number of observed values
	- line 149: # TODO: here?


src/gluonts/nursery/sagemaker_sdk/estimator.py (4 lines):
	- line 197: # TODO add support for HPO
	- line 417: # TODO: handle conversion from image name to params, once default
	- line 428: # TODO implement local mode support
	- line 510: # TODO hyperparameter override for hyper parameter optimization


src/gluonts/mx/linalg_util.py (3 lines):
	- line 187: # TODO: Add support for symbolic case: Cannot use < operator with symbolic variables
	- line 206: # TODO: Add support for symbolic case: Cannot use <= operator with symbolic variables
	- line 209: except Exception:  # TODO: this looks weird


src/gluonts/nursery/sagemaker_sdk/entry_point_scripts/train_entry_point.py (3 lines):
	- line 33: # TODO: implement model_fn, input_fn, predict_fn, and output_fn !!
	- line 34: # TODO: segment script for readability
	- line 92: # TODO switch to click


src/gluonts/model/seq2seq/_forking_network.py (3 lines):
	- line 176: # TODO: This assumes that future_feat_dynamic has no missing values
	- line 177: # TODO: Output the scale as well to be used by the decoder
	- line 195: # TODO: optimize what we pass to the decoder for the prediction case,


src/gluonts/nursery/SCott/pts/dataset/artificial.py (2 lines):
	- line 367: TODO: This could be converted to a RecipeDataset to avoid code duplication.
	- line 875: # TODO: Fix for missing values


src/gluonts/mx/block/decoder.py (2 lines):
	- line 52: # TODO: add support for static variables at some point
	- line 105: # TODO: add support for static input at some point


src/gluonts/time_feature/_base.py (2 lines):
	- line 128: # TODO:
	- line 143: # TODO:


src/gluonts/mx/distribution/piecewise_linear.py (2 lines):
	- line 446: # TODO: computations on knot spacings could be avoided here
	- line 463: # TODO: use event_shape


src/gluonts/nursery/sagemaker_sdk/entry_point_scripts/run_entry_point.py (2 lines):
	- line 31: # TODO: WRITE YOUR CUSTOM CODE HERE
	- line 57: # TODO: DONT FORGET TO PARSE ANY ADDITIONAL ARGUMENTS YOU SPECIFIED, FOR EXAMPLE THE INPUTS


src/gluonts/model/estimator.py (2 lines):
	- line 37: # TODO validation of prediction_length and freq could also
	- line 38: # TODO be bubbled-up here from subclasses classes


src/gluonts/dataset/loader.py (2 lines):
	- line 121: # TODO make timeout configurable
	- line 130: # TODO: the following are for backward compatibility


src/gluonts/model/lstnet/_network.py (2 lines):
	- line 112: # TODO: add temporal attention option
	- line 126: # TODO: GRUCell activation is fixed to tanh


src/gluonts/mx/distribution/transformed_distribution.py (2 lines):
	- line 228: # TODO: cover the multivariate case here too
	- line 235: # TODO: crps


src/gluonts/dataset/stat.py (2 lines):
	- line 139: # TODO: reorganize modules to avoid circular dependency
	- line 140: # TODO: and substitute Any with Dataset


src/gluonts/model/canonical/_network.py (2 lines):
	- line 101: F.ones_like(past_target),  # TODO: pass the actual observed here
	- line 157: F.ones_like(past_target),  # TODO: pass the actual observed here


src/gluonts/nursery/auto_ode/auto_ode.py (2 lines):
	- line 76: # r: growth rate shape (num_ts, ) TODO: Learn
	- line 77: # k: carrying capacity shape (num_ts, ) TODO: Learn


src/gluonts/nursery/SCott/pts/dataset/stat.py (2 lines):
	- line 134: # TODO: reorganize modules to avoid circular dependency
	- line 135: # TODO: and substitute Any with Dataset


src/gluonts/nursery/sagemaker_sdk/model.py (2 lines):
	- line 55: # TODO: implement custom data serializer and deserializer: convert between gluonts dataset and bytes
	- line 162: # TODO implement proper logic handling images when none are provided by user


src/gluonts/torch/model/deepar/module.py (1 line):
	- line 75: input_size=1,  # TODO fix


src/gluonts/model/forecast.py (1 line):
	- line 626: # FIXME: validate list elements


src/gluonts/mx/kernels/_periodic_kernel.py (1 line):
	- line 138: # TODO: Define scaling for the frequency


src/gluonts/nursery/SCott/pts/model/forecast.py (1 line):
	- line 37: # FIXME: validate list elements


src/gluonts/mx/distribution/binned.py (1 line):
	- line 155: # TODO: when mxnet has searchsorted replace this


src/gluonts/dataset/artificial/ar_p.py (1 line):
	- line 26: # TODO: support parameters


src/gluonts/mx/batchify.py (1 line):
	- line 75: # TODO: think about using shared context NDArrays


src/gluonts/mx/distribution/lowrank_gp.py (1 line):
	- line 84: # TODO 2 concatenate inputs features to x, better names would be great


src/gluonts/model/naive_2/_predictor.py (1 line):
	- line 83: # TODO: think about maybe only using past_ts_data[- max(5*season_length, 2*prediction_length):] for speedup


src/gluonts/nursery/spliced_binned_pareto/training_functions.py (1 line):
	- line 183: # TODO: handle error


src/gluonts/core/serde/__init__.py (1 line):
	- line 77: # TODO: remove


src/gluonts/mx/distribution/lds.py (1 line):
	- line 229: # TODO: Based on form of the prior decide to do either filtering


src/gluonts/model/tpp/forecast.py (1 line):
	- line 61: # TODO: not used


src/gluonts/model/predictor.py (1 line):
	- line 285: # TODO: Consider using shared memory for the data transfer.


src/gluonts/dataset/artificial/generate_synthetic.py (1 line):
	- line 99: # TODO: Fix for missing values


src/gluonts/model/deepstate/issm.py (1 line):
	- line 310: elif offset.name == "B":  # TODO: check this case


src/gluonts/model/deepar/_network.py (1 line):
	- line 94: # TODO: is the following restriction needed?


src/gluonts/model/canonical/_estimator.py (1 line):
	- line 71: # TODO: error checking


src/gluonts/model/deep_factor/_estimator.py (1 line):
	- line 159: # TODO: Allow the local model to be defined as an arbitrary local model, e.g. DF-GP and DF-LDS


src/gluonts/mx/distribution/bijection.py (1 line):
	- line 198: # TODO: eventually change for


src/gluonts/dataset/artificial/_base.py (1 line):
	- line 369: TODO: This could be converted to a RecipeDataset to avoid code duplication.


src/gluonts/model/seq2seq/_mq_dnn_estimator.py (1 line):
	- line 163: # TODO: add support for kernel size=1


src/gluonts/model/gpvar/_network.py (1 line):
	- line 187: # TODO 1 pass inputs in proj args


src/gluonts/model/seq2seq/_seq2seq_estimator.py (1 line):
	- line 261: # TODO: fix mutable arguments


src/gluonts/gluonts_tqdm.py (1 line):
	- line 21: # TODO: when we have upgraded this will give notebook progress bars


src/gluonts/dataset/artificial/recipe.py (1 line):
	- line 588: # TODO: holidays is type List[datetime.date]


src/gluonts/mx/distribution/mixture.py (1 line):
	- line 61: # TODO: handle case with all components of the same type more efficiently when sampling


src/gluonts/dataset/rolling_dataset.py (1 line):
	- line 116: # TODO Add parameter allowing for rolling of other arrays


src/gluonts/nursery/SCott/pts/dataset/recipe.py (1 line):
	- line 237: # TODO: holidays is type List[datetime.date]


src/gluonts/mx/model/predictor.py (1 line):
	- line 203: # FIXME: also needs to serialize the output_transform


src/gluonts/mx/distribution/lowrank_multivariate_gaussian.py (1 line):
	- line 334: # TODO: Implement it for the general case: `rank` > 0


src/gluonts/model/rotbaum/_predictor.py (1 line):
	- line 156: != "ignore"  # TODO: Figure out how to include 'auto' with no feat_static_cat in this check


src/gluonts/nursery/SCott/pts/model/simple_feedforward/simple_feedforward_network.py (1 line):
	- line 92: ),  # TODO: pass the actual observed here


src/gluonts/mx/block/encoder.py (1 line):
	- line 111: # TODO: fix handling of static features


src/gluonts/model/renewal/_network.py (1 line):
	- line 213: # TODO: on windows, operators below may produce NaN values


src/gluonts/shell/sagemaker/params.py (1 line):
	- line 34: # TODO: is this the right way to do things?


src/gluonts/_version.py (1 line):
	- line 174: # TODO: Do we really need this check?


src/gluonts/torch/model/predictor.py (1 line):
	- line 117: # FIXME: also needs to serialize the output_transform