default logger is now tensorboard (#609)
* refactor * refactor * refactor * made tensorboard the default not test-tube
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@ -2,7 +2,7 @@ import os
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from abc import ABC
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from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping
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from pytorch_lightning.logging import TestTubeLogger
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from pytorch_lightning.logging import TensorboardLogger
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class TrainerCallbackConfigMixin(ABC):
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@ -69,7 +69,7 @@ class TrainerCallbackConfigMixin(ABC):
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# configure logger
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if logger is True:
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# default logger
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self.logger = TestTubeLogger(
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self.logger = TensorboardLogger(
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save_dir=self.default_save_path,
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version=self.slurm_job_id,
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name='lightning_logs'
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@ -139,41 +139,53 @@ class Trainer(TrainerIOMixin,
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"""
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# Transfer params
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if nb_gpu_nodes is not None: # Backward compatibility
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# Backward compatibility
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if nb_gpu_nodes is not None:
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warnings.warn("`nb_gpu_nodes` has renamed to `num_nodes` since v0.5.0"
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" and will be removed in v0.8.0", DeprecationWarning)
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if not num_nodes: # in case you did not set the proper value
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num_nodes = nb_gpu_nodes
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self.num_gpu_nodes = num_nodes
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self.log_gpu_memory = log_gpu_memory
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if gradient_clip is not None: # Backward compatibility
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# Backward compatibility
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if gradient_clip is not None:
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warnings.warn("`gradient_clip` has renamed to `gradient_clip_val` since v0.5.0"
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" and will be removed in v0.8.0", DeprecationWarning)
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if not gradient_clip_val: # in case you did not set the proper value
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gradient_clip_val = gradient_clip
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self.gradient_clip_val = gradient_clip_val
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self.check_val_every_n_epoch = check_val_every_n_epoch
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self.track_grad_norm = track_grad_norm
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self.on_gpu = True if (gpus and torch.cuda.is_available()) else False
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self.process_position = process_position
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self.weights_summary = weights_summary
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if max_nb_epochs is not None: # Backward compatibility
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# Backward compatibility
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if max_nb_epochs is not None:
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warnings.warn("`max_nb_epochs` has renamed to `max_epochs` since v0.5.0"
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" and will be removed in v0.8.0", DeprecationWarning)
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if not max_epochs: # in case you did not set the proper value
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max_epochs = max_nb_epochs
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self.max_epochs = max_epochs
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if min_nb_epochs is not None: # Backward compatibility
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# Backward compatibility
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if min_nb_epochs is not None:
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warnings.warn("`min_nb_epochs` has renamed to `min_epochs` since v0.5.0"
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" and will be removed in v0.8.0", DeprecationWarning)
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if not min_epochs: # in case you did not set the proper value
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min_epochs = min_nb_epochs
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self.min_epochs = min_epochs
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if nb_sanity_val_steps is not None: # Backward compatibility
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# Backward compatibility
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if nb_sanity_val_steps is not None:
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warnings.warn("`nb_sanity_val_steps` has renamed to `num_sanity_val_steps` since v0.5.0"
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" and will be removed in v0.8.0", DeprecationWarning)
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if not num_sanity_val_steps: # in case you did not set the proper value
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num_sanity_val_steps = nb_sanity_val_steps
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self.num_sanity_val_steps = num_sanity_val_steps
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self.print_nan_grads = print_nan_grads
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self.truncated_bptt_steps = truncated_bptt_steps
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@ -262,8 +274,9 @@ class Trainer(TrainerIOMixin,
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# logging
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self.log_save_interval = log_save_interval
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self.val_check_interval = val_check_interval
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# backward compatibility
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if add_row_log_interval is not None:
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# backward compatibility
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warnings.warn("`add_row_log_interval` has renamed to `row_log_interval` since v0.5.0"
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" and will be removed in v0.8.0", DeprecationWarning)
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if not row_log_interval: # in case you did not set the proper value
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@ -5,4 +5,4 @@ torch>=1.1
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torchvision>=0.4.0
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pandas>=0.24 # lower version do not support py3.7
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test-tube>=0.7.5
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future>=0.17.1 # required for builtins in setup.py
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future>=0.17.1 # required for builtins in setup.py
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