rename

pytorch_lightning/metrics/metric.py → pytorch_lightning/metrics/metricbase.py

@@ -7,10 +7,10 @@
 from pytorch_lightning.metrics.converters import tensor_metric, numpy_metric
 from pytorch_lightning.utilities.apply_func import apply_to_collection
 
-__all__ = ['Metric', 'TensorMetric', 'NumpyMetric']
+__all__ = ['MetricBase', 'TensorMetricBase', 'NumpyMetricBase']
 
 
-class Metric(torch.nn.Module, ABC):
+class MetricBase(torch.nn.Module, ABC):
     """
     Abstract Base Class for metric implementation.
 
@@ -95,7 +95,7 @@ def to(self, *args, **kwargs) -> torch.nn.Module:
             Module: self
 
         Example::
-            >>> class ExampleMetric(Metric):
+            >>> class ExampleMetric(MetricBase):
             ...     def __init__(self, weight: torch.Tensor):
             ...         super().__init__('example')
             ...         self.register_buffer('weight', weight)
@@ -199,7 +199,7 @@ def half(self) -> torch.nn.Module:
         return super().half()
 
 
-class TensorMetric(Metric):
+class TensorMetricBase(MetricBase):
     """
     Base class for metric implementation operating directly on tensors.
     All inputs and outputs will be casted to tensors if necessary.
@@ -229,7 +229,7 @@ def _to_device_dtype(x: torch.Tensor) -> torch.Tensor:
                                    _to_device_dtype)
 
 
-class NumpyMetric(Metric):
+class NumpyMetricBase(MetricBase):
     """
     Base class for metric implementation operating on numpy arrays.
     All inputs will be casted to numpy if necessary and all outputs will

tests/metrics/test_metrics.py

@@ -1,10 +1,10 @@
 import numpy as np
 import torch
 
-from pytorch_lightning.metrics.metric import Metric, TensorMetric, NumpyMetric
+from pytorch_lightning.metrics.metric import MetricBase, TensorMetricBase, NumpyMetricBase
 
 
-class DummyTensorMetric(TensorMetric):
+class DummyTensorMetric(TensorMetricBase):
     def __init__(self):
         super().__init__('dummy')
 
@@ -14,7 +14,7 @@ def forward(self, input1, input2):
         return 1.
 
 
-class DummyNumpyMetric(NumpyMetric):
+class DummyNumpyMetric(NumpyMetricBase):
     def __init__(self):
         super().__init__('dummy')
 
@@ -24,7 +24,7 @@ def forward(self, input1, input2):
         return 1.
 
 
-def _test_metric(metric: Metric):
+def _test_metric(metric: MetricBase):
     input1, input2 = torch.tensor([1.]), torch.tensor([2.])
 
     def change_and_check_device_dtype(device, dtype):