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updated tempflow

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This commit is contained in:
Dr. Kashif Rasul
2021-01-02 10:59:50 +01:00
parent e79166f444
commit eeeb96335a
10 changed files with 54 additions and 28 deletions
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pts/model/deepar/deepar_estimator.py
+1
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@@ -27,6 +27,7 @@ from gluonts.torch.support.util import copy_parameters
from gluonts.torch.model.predictor import PyTorchPredictor
from gluonts.torch.modules.distribution_output import DistributionOutput
from gluonts.model.predictor import Predictor
from pts.model.utils import get_module_forward_input_names
from pts import Trainer
from pts.model import PyTorchEstimator
pts/model/deepvar/deepvar_estimator.py
+2
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@@ -27,6 +27,7 @@ from gluonts.transform import (
AddAgeFeature,
cdf_to_gaussian_forward_transform,
)
from pts import Trainer
from pts.model.utils import get_module_forward_input_names
from pts.feature import (
@@ -35,6 +36,7 @@ from pts.feature import (
)
from pts.model import PyTorchEstimator
from pts.modules import LowRankMultivariateNormalOutput
from .deepvar_network import DeepVARTrainingNetwork, DeepVARPredictionNetwork
pts/model/lstnet/lstnet_estimator.py
+2 -1
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@@ -6,7 +6,6 @@ import torch.nn as nn
from gluonts.dataset.field_names import FieldName
from gluonts.torch.support.util import copy_parameters
from pts.model.utils import get_module_forward_input_names
from gluonts.torch.model.predictor import PyTorchPredictor
from gluonts.model.predictor import Predictor
from gluonts.transform import (
@@ -17,8 +16,10 @@ from gluonts.transform import (
AddObservedValuesIndicator,
AsNumpyArray,
)
from pts.model import PyTorchEstimator
from pts import Trainer
from pts.model.utils import get_module_forward_input_names
from .lstnet_network import LSTNetTrain, LSTNetPredict
pts/model/n_beats/n_beats_estimator.py
+2
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@@ -14,9 +14,11 @@ from gluonts.transform import (
RemoveFields,
ExpectedNumInstanceSampler,
)
from pts import Trainer
from pts.model import PyTorchEstimator
from pts.model.utils import get_module_forward_input_names
from .n_beats_network import (
NBEATSPredictionNetwork,
NBEATSTrainingNetwork,
pts/model/simple_feedforward/simple_feedforward_estimator.py
+1
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@@ -19,6 +19,7 @@ from gluonts.transform import (
InstanceSplitter,
ExpectedNumInstanceSampler,
)
from pts.model.utils import get_module_forward_input_names
from pts import Trainer
from pts.model import PyTorchEstimator
pts/model/tempflow/tempflow_estimator.py
+21 -13
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@@ -2,15 +2,13 @@ from typing import List, Optional
import torch
from pts import Trainer
from pts.dataset import FieldName
from pts.feature import (
TimeFeature,
fourier_time_features_from_frequency_str,
get_fourier_lags_for_frequency,
)
from pts.model import PyTorchEstimator, PyTorchPredictor, copy_parameters
from pts.transform import (
from gluonts.dataset.field_names import FieldName
from gluonts.time_feature import TimeFeature
from gluonts.torch.model.predictor import PyTorchPredictor
from gluonts.torch.support.util import copy_parameters
from gluonts.model.predictor import Predictor
from gluonts.torch.model.predictor import PyTorchPredictor
from gluonts.transform import (
Transformation,
Chain,
InstanceSplitter,
@@ -24,6 +22,15 @@ from pts.transform import (
SetFieldIfNotPresent,
TargetDimIndicator,
)
from pts import Trainer
from pts.feature import (
fourier_time_features_from_frequency,
lags_for_fourier_time_features_from_frequency
)
from pts.model.utils import get_module_forward_input_names
from pts.model import PyTorchEstimator
from .tempflow_network import TempFlowTrainingNetwork, TempFlowPredictionNetwork
@@ -83,13 +90,13 @@ class TempFlowEstimator(PyTorchEstimator):
self.lags_seq = (
lags_seq
if lags_seq is not None
else get_fourier_lags_for_frequency(freq_str=freq)
else lags_for_fourier_time_features_from_frequency(freq_str=freq)
)
self.time_features = (
time_features
if time_features is not None
else fourier_time_features_from_frequency_str(self.freq)
else fourier_time_features_from_frequency(self.freq)
)
self.history_length = self.context_length + max(self.lags_seq)
@@ -181,7 +188,7 @@ class TempFlowEstimator(PyTorchEstimator):
transformation: Transformation,
trained_network: TempFlowTrainingNetwork,
device: torch.device,
) -> PyTorchPredictor:
) -> Predictor:
prediction_network = TempFlowPredictionNetwork(
input_size=self.input_size,
target_dim=self.target_dim,
@@ -206,13 +213,14 @@ class TempFlowEstimator(PyTorchEstimator):
).to(device)
copy_parameters(trained_network, prediction_network)
input_names = get_module_forward_input_names(prediction_network)
return PyTorchPredictor(
input_transform=transformation,
input_names=input_names,
prediction_net=prediction_network,
batch_size=self.trainer.batch_size,
freq=self.freq,
prediction_length=self.prediction_length,
device=device,
output_transform=None,
)
pts/model/tempflow/tempflow_network.py
+1
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@@ -4,6 +4,7 @@ import torch
import torch.nn as nn
from gluonts.core.component import validated
from pts.model import weighted_average
from pts.modules import RealNVP, MAF, FlowOutput, MeanScaler, NOPScaler
pts/model/transformer/transformer_estimator.py
+2
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@@ -23,6 +23,7 @@ from gluonts.transform import (
VstackFeatures,
SetField,
)
from pts import Trainer
from pts.model.utils import get_module_forward_input_names
from pts.feature import (
@@ -31,6 +32,7 @@ from pts.feature import (
)
from pts.model import PyTorchEstimator
from pts.modules import StudentTOutput
from .transformer_network import (
TransformerTrainingNetwork,
TransformerPredictionNetwork,
pts/model/transformer_tempflow/transformer_tempflow_estimator.py
+20 -13
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@@ -2,15 +2,12 @@ from typing import List, Optional
import torch
from pts import Trainer
from pts.dataset import FieldName
from pts.feature import (
TimeFeature,
fourier_time_features_from_frequency_str,
get_fourier_lags_for_frequency,
)
from pts.model import PyTorchEstimator, PyTorchPredictor, copy_parameters
from pts.transform import (
from gluonts.dataset.field_names import FieldName
from gluonts.time_feature import TimeFeature
from gluonts.torch.support.util import copy_parameters
from gluonts.torch.model.predictor import PyTorchPredictor
from gluonts.model.predictor import Predictor
from gluonts.transform import (
Transformation,
Chain,
InstanceSplitter,
@@ -24,6 +21,15 @@ from pts.transform import (
SetFieldIfNotPresent,
TargetDimIndicator,
)
from pts import Trainer
from pts.model import PyTorchEstimator
from pts.model.utils import get_module_forward_input_names
from pts.feature import (
fourier_time_features_from_frequency,
lags_for_fourier_time_features_from_frequency,
)
from .transformer_tempflow_network import (
TransformerTempFlowTrainingNetwork,
TransformerTempFlowPredictionNetwork,
@@ -94,13 +100,13 @@ class TransformerTempFlowEstimator(PyTorchEstimator):
self.lags_seq = (
lags_seq
if lags_seq is not None
else get_fourier_lags_for_frequency(freq_str=freq)
else lags_for_fourier_time_features_from_frequency(freq_str=freq)
)
self.time_features = (
time_features
if time_features is not None
else fourier_time_features_from_frequency_str(self.freq)
else fourier_time_features_from_frequency(self.freq)
)
self.history_length = self.context_length + max(self.lags_seq)
@@ -197,7 +203,7 @@ class TransformerTempFlowEstimator(PyTorchEstimator):
transformation: Transformation,
trained_network: TransformerTempFlowTrainingNetwork,
device: torch.device,
) -> PyTorchPredictor:
) -> Predictor:
prediction_network = TransformerTempFlowPredictionNetwork(
input_size=self.input_size,
target_dim=self.target_dim,
@@ -225,13 +231,14 @@ class TransformerTempFlowEstimator(PyTorchEstimator):
).to(device)
copy_parameters(trained_network, prediction_network)
input_names = get_module_forward_input_names(prediction_network)
return PyTorchPredictor(
input_transform=transformation,
input_names=input_names,
prediction_net=prediction_network,
batch_size=self.trainer.batch_size,
freq=self.freq,
prediction_length=self.prediction_length,
device=device,
output_transform=None,
)
pts/model/transformer_tempflow/transformer_tempflow_network.py
+2 -1
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@@ -3,7 +3,8 @@ from typing import List, Optional, Tuple
import torch
import torch.nn as nn
from gluonts.core.component import validated
from gluonts.core.component import
from pts.modules import RealNVP, MAF, FlowOutput, MeanScaler, NOPScaler