AttributeError: 'Series' object has no attribute 'freq' (DeepAR algorithm in Time series forecasting) #1845
Description
Describe the bug
I'm running dbg-deepar.ipynb, provided module deepar_util.py by following the tutorial
Stock Price Prediction, using SageMaker DeepAR.
The problem may be that I cannot update Pandas on SageMaker Studio Notebook. My Pandas version '1.0.1'
class DeepARPredictor in deepar_util.py
class DeepARPredictor(sagemaker.predictor.RealTimePredictor):
def __init__(self, *args, **kwargs):
super().__init__(*args, content_type=sagemaker.content_types.CONTENT_TYPE_JSON, **kwargs)
def predict(self, ts, cat=None, dynamic_feat=None,
num_samples=100, return_samples=False, quantiles=["0.1", "0.5", "0.9"]):
"""Requests the prediction of for the time series listed in `ts`, each with the (optional)
corresponding category listed in `cat`.
ts -- `pandas.Series` object, the time series to predict
cat -- integer, the group associated to the time series (default: None)
num_samples -- integer, number of samples to compute at prediction time (default: 100)
return_samples -- boolean indicating whether to include samples in the response (default: False)
quantiles -- list of strings specifying the quantiles to compute (default: ["0.1", "0.5", "0.9"])
Return value: list of `pandas.DataFrame` objects, each containing the predictions
"""
prediction_time = ts.index[-1] + pd.Timedelta(1, unit='D')
quantiles = [str(q) for q in quantiles]
req = self.__encode_request(ts, cat, dynamic_feat, num_samples, return_samples, quantiles)
res = super(DeepARPredictor, self).predict(req)
return self.__decode_response(res, ts.index.freq, prediction_time, return_samples)
def __encode_request(self, ts, cat, dynamic_feat, num_samples, return_samples, quantiles):
instance = series_to_dict(ts, cat if cat is not None else None, dynamic_feat if dynamic_feat else None)
configuration = {
"num_samples": num_samples,
"output_types": ["quantiles", "samples"] if return_samples else ["quantiles"],
"quantiles": quantiles
}
http_request_data = {
"instances": [instance],
"configuration": configuration
}
return json.dumps(http_request_data).encode('utf-8')
def __decode_response(self, response, freq, prediction_time, return_samples):
# we only sent one time series so we only receive one in return
# however, if possible one will pass multiple time series as predictions will then be faster
predictions = json.loads(response.decode('utf-8'))['predictions'][0]
prediction_length = len(next(iter(predictions['quantiles'].values())))
prediction_index = pd.DatetimeIndex(start=prediction_time, freq=freq, periods=prediction_length)
if return_samples:
dict_of_samples = {'sample_' + str(i): s for i, s in enumerate(predictions['samples'])}
else:
dict_of_samples = {}
return pd.DataFrame(data={**predictions['quantiles'], **dict_of_samples}, index=prediction_index)
def set_frequency(self, freq):
self.freq = freq
Function in dbg-deepar.ipynb
predictor = DeepARPredictor(estimator_job)
ts, dynamic_feat, observed = util.query_for_stock('BMW', target_column, covariate_columns, stock_data_series, prediction_length)
prediction = predictor.predict(ts=ts, dynamic_feat = dynamic_feat, quantiles=[0.10, 0.5, 0.90], return_samples=False)
** Error logs**
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-118-6bae3056850a> in <module>
----> 1 prediction = predictor.predict(ts=ts, dynamic_feat = dynamic_feat, quantiles=[0.10, 0.5, 0.90], return_samples=False)
2 prediction.head()
~/deepar_util.py in predict(self, ts, cat, dynamic_feat, num_samples, return_samples, quantiles)
201
202 Return value: list of `pandas.DataFrame` objects, each containing the predictions
--> 203 """
204 prediction_time = ts.index[-1] + pd.Timedelta(1, unit='D')
205 quantiles = [str(q) for q in quantiles]
/opt/conda/lib/python3.7/site-packages/pandas/core/generic.py in __getattr__(self, name)
5272 if self._info_axis._can_hold_identifiers_and_holds_name(name):
5273 return self[name]
-> 5274 return object.__getattribute__(self, name)
5275
5276 def __setattr__(self, name: str, value) -> None:
AttributeError: 'Series' object has no attribute 'freq'
System information
- SageMaker Python SDK version:
- Framework name (eg. PyTorch) or algorithm (eg. KMeans):
- Framework version:
- Python version: 3.7.7
- CPU or GPU: CPU
- Custom Docker image (Y/N): N
- **Pandas version 1.0.1