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71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
# Copyright 2022 The Plenoptix Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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The field module baseclass.
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"""
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from abc import abstractmethod
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from torch import nn
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from torchtyping import TensorType
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class FieldModule(nn.Module):
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"""Field modules that can be combined to store and compute the fields.
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Args:
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in_dim (int, optional): Input dimension to module.
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out_dim (int, optional): Ouput dimension to module.
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"""
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def __init__(self, in_dim: int = None, out_dim: int = None) -> None:
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super().__init__()
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self.in_dim = in_dim
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self.out_dim = out_dim
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def build_nn_modules(self) -> None:
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"""Function instantiates any torch.nn members within the module.
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If none exist, do nothing."""
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def set_in_dim(self, in_dim: int) -> None:
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"""Sets input dimension of encoding
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Args:
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in_dim (int): input dimension
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"""
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if in_dim <= 0:
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raise ValueError("Input dimension should be greater than zero")
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self.in_dim = in_dim
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def get_out_dim(self) -> int:
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"""Calculates output dimension of encoding.
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Returns:
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int: output dimension
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"""
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if self.out_dim is None:
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raise ValueError("Output dimension has not been set")
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return self.out_dim
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@abstractmethod
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def forward(self, in_tensor: TensorType[..., "input_dim"]) -> TensorType[..., "output_dim"]:
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"""
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Args:
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in_tensor (TensorType[..., "input_dim"]): Input tensor to process
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Returns:
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TensorType[..., "output_dim"]: Processed tensor
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"""
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raise NotImplementedError
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