mirror of
https://github.com/wassname/pytorch-lightning.git
synced 2026-09-01 12:32:04 +08:00
Alok Singh
b0a0a47a0b
- data_batch → batch - batch_i → batch_idx - dataloader_i → dataloader_idx - tng → training - training_dataloader → train_dataloader - add_log_row_interval → row_log_interval - gradient_clip → gradient_clip_val - prog → progress - tqdm_dic → tqdm_dict
28 lines
874 B
Python
28 lines
874 B
Python
import os
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from collections import OrderedDict
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import torch
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import torch.nn as nn
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import torch.nn.functional as F
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from torch import optim
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from torch.utils.data import DataLoader
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from torch.utils.data.distributed import DistributedSampler
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from torchvision.datasets import MNIST
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from torchvision import transforms
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from test_tube import HyperOptArgumentParser
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from pytorch_lightning.root_module.root_module import LightningModule
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from pytorch_lightning import data_loader
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from .lm_test_module_base import LightningTestModelBase
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from .lm_test_module_mixins import LightningValidationMixin, LightningTestMixin
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class LightningTestModel(LightningValidationMixin, LightningTestMixin, LightningTestModelBase):
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"""
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Most common test case. Validation and test dataloaders
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"""
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def on_training_metrics(self, logs):
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logs['some_tensor_to_test'] = torch.rand(1)
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