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2,301
on_epoch_end
def on_epoch_end(self, epoch, logs={}): if self.log_weights: wandb.log(self._log_weights(), commit=False) if self.log_gradients: wandb.log(self._log_gradients(), commit=False) if self.input_type in ( "image", "images", "segmentation_m...
python
wandb/integration/keras/keras.py
581
632
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,302
on_batch_begin
def on_batch_begin(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
635
636
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,303
on_batch_end
def on_batch_end(self, batch, logs=None): if self.save_graph and not self._graph_rendered: # Couldn't do this in train_begin because keras may still not be built wandb.run.summary["graph"] = wandb.Graph.from_keras(self.model) self._graph_rendered = True if self.log_b...
python
wandb/integration/keras/keras.py
639
646
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,304
on_train_batch_begin
def on_train_batch_begin(self, batch, logs=None): self._model_trained_since_last_eval = True
python
wandb/integration/keras/keras.py
648
649
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,305
on_train_batch_end
def on_train_batch_end(self, batch, logs=None): if self.save_graph and not self._graph_rendered: # Couldn't do this in train_begin because keras may still not be built wandb.run.summary["graph"] = wandb.Graph.from_keras(self.model) self._graph_rendered = True if self...
python
wandb/integration/keras/keras.py
651
658
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,306
on_test_begin
def on_test_begin(self, logs=None): pass
python
wandb/integration/keras/keras.py
660
661
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,307
on_test_end
def on_test_end(self, logs=None): pass
python
wandb/integration/keras/keras.py
663
664
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,308
on_test_batch_begin
def on_test_batch_begin(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
666
667
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,309
on_test_batch_end
def on_test_batch_end(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
669
670
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,310
on_train_begin
def on_train_begin(self, logs=None): if self.log_evaluation: try: validation_data = None if self.validation_data: validation_data = self.validation_data elif self.generator: if not self.validation_steps: ...
python
wandb/integration/keras/keras.py
672
723
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,311
on_train_end
def on_train_end(self, logs=None): if self._model_trained_since_last_eval: self._attempt_evaluation_log()
python
wandb/integration/keras/keras.py
725
727
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,312
on_test_begin
def on_test_begin(self, logs=None): pass
python
wandb/integration/keras/keras.py
729
730
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,313
on_test_end
def on_test_end(self, logs=None): pass
python
wandb/integration/keras/keras.py
732
733
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,314
on_test_batch_begin
def on_test_batch_begin(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
735
736
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,315
on_test_batch_end
def on_test_batch_end(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
738
739
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,316
on_predict_begin
def on_predict_begin(self, logs=None): pass
python
wandb/integration/keras/keras.py
741
742
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,317
on_predict_end
def on_predict_end(self, logs=None): pass
python
wandb/integration/keras/keras.py
744
745
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,318
on_predict_batch_begin
def on_predict_batch_begin(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
747
748
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,319
on_predict_batch_end
def on_predict_batch_end(self, batch, logs=None): pass
python
wandb/integration/keras/keras.py
750
751
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,320
_logits_to_captions
def _logits_to_captions(self, logits): if logits[0].shape[-1] == 1: # Scalar output from the model # TODO: handle validation_y if len(self.labels) == 2: # User has named true and false captions = [ self.labels[1] if logits[0...
python
wandb/integration/keras/keras.py
753
785
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,321
_masks_to_pixels
def _masks_to_pixels(self, masks): # if its a binary mask, just return it as grayscale instead of picking the argmax if len(masks[0].shape) == 2 or masks[0].shape[-1] == 1: return masks class_colors = ( self.class_colors if self.class_colors is not None ...
python
wandb/integration/keras/keras.py
787
797
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,322
_log_images
def _log_images(self, num_images=36): validation_X = self.validation_data[0] validation_y = self.validation_data[1] validation_length = len(validation_X) if validation_length > num_images: # pick some data at random indices = np.random.choice(validation_length, ...
python
wandb/integration/keras/keras.py
799
914
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,323
_log_weights
def _log_weights(self): metrics = {} for layer in self.model.layers: weights = layer.get_weights() if len(weights) == 1: _update_if_numeric( metrics, "parameters/" + layer.name + ".weights", weights[0] ) elif len(wei...
python
wandb/integration/keras/keras.py
916
931
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,324
_log_gradients
def _log_gradients(self): # Suppress callback warnings grad accumulator og_level = tf_logger.level tf_logger.setLevel("ERROR") self._grad_accumulator_model.fit( self._training_data_x, self._training_data_y, verbose=0, callbacks=[self._grad...
python
wandb/integration/keras/keras.py
933
952
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,325
_log_dataframe
def _log_dataframe(self): x, y_true, y_pred = None, None, None if self.validation_data: x, y_true = self.validation_data[0], self.validation_data[1] y_pred = self.model.predict(x) elif self.generator: if not self.validation_steps: wandb.termwa...
python
wandb/integration/keras/keras.py
954
1,000
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,326
_save_model
def _save_model(self, epoch): if wandb.run.disabled: return if self.verbose > 0: print( "Epoch %05d: %s improved from %0.5f to %0.5f," " saving model to %s" % (epoch, self.monitor, self.best, self.current, self.filepath) ...
python
wandb/integration/keras/keras.py
1,002
1,023
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,327
_save_model_as_artifact
def _save_model_as_artifact(self, epoch): if wandb.run.disabled: return # Save the model in the SavedModel format. # TODO: Replace this manual artifact creation with the `log_model` method # after `log_model` is released from beta. self.model.save(self.filepath[:-3],...
python
wandb/integration/keras/keras.py
1,025
1,041
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,328
get_flops
def get_flops(self) -> float: """ Calculate FLOPS [GFLOPs] for a tf.keras.Model or tf.keras.Sequential model in inference mode. It uses tf.compat.v1.profiler under the hood. """ if not hasattr(self, "model"): raise wandb.Error("self.model must be set before using this...
python
wandb/integration/keras/keras.py
1,043
1,089
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,329
__init__
def __init__( self, data_table_columns: List[str], pred_table_columns: List[str], *args: Any, **kwargs: Any, ) -> None: super().__init__(*args, **kwargs) if wandb.run is None: raise wandb.Error( "You must call `wandb.init()` first ...
python
wandb/integration/keras/callbacks/tables_builder.py
91
109
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,330
on_train_begin
def on_train_begin(self, logs: Optional[Dict[str, float]] = None) -> None: # Initialize the data_table self.init_data_table(column_names=self.data_table_columns) # Log the ground truth data self.add_ground_truth(logs) # Log the data_table as W&B Artifacts self.log_data_ta...
python
wandb/integration/keras/callbacks/tables_builder.py
111
117
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,331
on_epoch_end
def on_epoch_end(self, epoch: int, logs: Optional[Dict[str, float]] = None) -> None: # Initialize the pred_table self.init_pred_table(column_names=self.pred_table_columns) # Log the model prediction self.add_model_predictions(epoch, logs) # Log the pred_table as W&B Artifacts ...
python
wandb/integration/keras/callbacks/tables_builder.py
119
125
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,332
add_ground_truth
def add_ground_truth(self, logs: Optional[Dict[str, float]] = None) -> None: """Add ground truth data to `data_table`. Use this method to write the logic for adding validation/training data to `data_table` initialized using `init_data_table` method. Example: ``` ...
python
wandb/integration/keras/callbacks/tables_builder.py
128
144
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,333
add_model_predictions
def add_model_predictions( self, epoch: int, logs: Optional[Dict[str, float]] = None ) -> None: """Add a prediction from a model to `pred_table`. Use this method to write the logic for adding model prediction for validation/ training data to `pred_table` initialized using `init_pred...
python
wandb/integration/keras/callbacks/tables_builder.py
147
168
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,334
init_data_table
def init_data_table(self, column_names: List[str]) -> None: """Initialize the W&B Tables for validation data. Call this method `on_train_begin` or equivalent hook. This is followed by adding data to the table row or column wise. Args: column_names (list): Column names for W...
python
wandb/integration/keras/callbacks/tables_builder.py
170
179
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,335
init_pred_table
def init_pred_table(self, column_names: List[str]) -> None: """Initialize the W&B Tables for model evaluation. Call this method `on_epoch_end` or equivalent hook. This is followed by adding data to the table row or column wise. Args: column_names (list): Column names for W&...
python
wandb/integration/keras/callbacks/tables_builder.py
181
190
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,336
log_data_table
def log_data_table( self, name: str = "val", type: str = "dataset", table_name: str = "val_data" ) -> None: """Log the `data_table` as W&B artifact and call `use_artifact` on it. This lets the evaluation table use the reference of already uploaded data (images, text, scalar, etc.) w...
python
wandb/integration/keras/callbacks/tables_builder.py
192
218
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,337
log_pred_table
def log_pred_table( self, type: str = "evaluation", table_name: str = "eval_data", aliases: Optional[List[str]] = None, ) -> None: """Log the W&B Tables for model evaluation. The table will be logged multiple times creating new version. Use this to compare mo...
python
wandb/integration/keras/callbacks/tables_builder.py
220
241
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,338
__init__
def __init__( self, filepath: Union[str, os.PathLike], monitor: str = "val_loss", verbose: int = 0, save_best_only: bool = False, save_weights_only: bool = False, mode: Mode = "auto", save_freq: Union[SaveStrategy, int] = "epoch", options: Optional...
python
wandb/integration/keras/callbacks/model_checkpoint.py
73
111
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,339
on_train_batch_end
def on_train_batch_end( self, batch: int, logs: Optional[Dict[str, float]] = None ) -> None: if self._should_save_on_batch(batch): if self.is_old_tf_keras_version: # Save the model and get filepath self._save_model(epoch=self._current_epoch, logs=logs) ...
python
wandb/integration/keras/callbacks/model_checkpoint.py
113
129
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,340
on_epoch_end
def on_epoch_end(self, epoch: int, logs: Optional[Dict[str, float]] = None) -> None: super().on_epoch_end(epoch, logs) # Check if model checkpoint is created at the end of epoch. if self.save_freq == "epoch": # Get filepath where the model checkpoint is saved. if self.is_...
python
wandb/integration/keras/callbacks/model_checkpoint.py
131
142
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,341
_log_ckpt_as_artifact
def _log_ckpt_as_artifact( self, filepath: str, aliases: Optional[List[str]] = None ) -> None: """Log model checkpoint as W&B Artifact.""" try: assert wandb.run is not None model_artifact = wandb.Artifact(f"run_{wandb.run.id}_model", type="model") if self...
python
wandb/integration/keras/callbacks/model_checkpoint.py
144
171
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,342
_check_filepath
def _check_filepath(self) -> None: placeholders = [] for tup in string.Formatter().parse(self.filepath): if tup[1] is not None: placeholders.append(tup[1]) if len(placeholders) == 0: wandb.termwarn( "When using `save_best_only`, ensure that...
python
wandb/integration/keras/callbacks/model_checkpoint.py
173
184
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,343
is_old_tf_keras_version
def is_old_tf_keras_version(self) -> Optional[bool]: if self._is_old_tf_keras_version is None: from pkg_resources import parse_version if parse_version(tf.keras.__version__) < parse_version("2.6.0"): self._is_old_tf_keras_version = True else: ...
python
wandb/integration/keras/callbacks/model_checkpoint.py
187
196
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,344
__init__
def __init__( self, log_freq: Union[LogStrategy, int] = "epoch", initial_global_step: int = 0, *args: Any, **kwargs: Any, ) -> None: super().__init__(*args, **kwargs) if wandb.run is None: raise wandb.Error( "You must call `wandb.i...
python
wandb/integration/keras/callbacks/metrics_logger.py
52
86
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,345
_get_lr
def _get_lr(self) -> Union[float, None]: if isinstance(self.model.optimizer.learning_rate, tf.Variable): return float(self.model.optimizer.learning_rate.numpy().item()) try: return float( self.model.optimizer.learning_rate(step=self.global_step).numpy().item() ...
python
wandb/integration/keras/callbacks/metrics_logger.py
88
97
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,346
on_epoch_end
def on_epoch_end(self, epoch: int, logs: Optional[Dict[str, Any]] = None) -> None: """Called at the end of an epoch.""" logs = dict() if logs is None else {f"epoch/{k}": v for k, v in logs.items()} logs["epoch/epoch"] = epoch lr = self._get_lr() if lr is not None: l...
python
wandb/integration/keras/callbacks/metrics_logger.py
99
109
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,347
on_batch_end
def on_batch_end(self, batch: int, logs: Optional[Dict[str, Any]] = None) -> None: self.global_step += 1 """An alias for `on_train_batch_end` for backwards compatibility.""" if self.logging_batch_wise and batch % self.log_freq == 0: logs = {f"batch/{k}": v for k, v in logs.items()} i...
python
wandb/integration/keras/callbacks/metrics_logger.py
111
124
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,348
on_train_batch_end
def on_train_batch_end( self, batch: int, logs: Optional[Dict[str, Any]] = None ) -> None: """Called at the end of a training batch in `fit` methods.""" self.on_batch_end(batch, logs if logs else {})
python
wandb/integration/keras/callbacks/metrics_logger.py
126
130
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,349
__init__
def __init__( self, verbose: int = 0, model_save_path: Optional[str] = None, model_save_freq: int = 0, gradient_save_freq: int = 0, log: Optional[Literal["gradients", "parameters", "all"]] = "all", ) -> None: super().__init__(verbose) if wandb.run is N...
python
wandb/integration/sb3/sb3.py
87
117
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,350
_init_callback
def _init_callback(self) -> None: d = {} if "algo" not in d: d["algo"] = type(self.model).__name__ for key in self.model.__dict__: if key in wandb.config: continue if type(self.model.__dict__[key]) in [float, int, str]: d[key] =...
python
wandb/integration/sb3/sb3.py
119
136
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,351
_on_step
def _on_step(self) -> bool: if self.model_save_freq > 0: if self.model_save_path is not None: if self.n_calls % self.model_save_freq == 0: self.save_model() return True
python
wandb/integration/sb3/sb3.py
138
143
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,352
_on_training_end
def _on_training_end(self) -> None: if self.model_save_path is not None: self.save_model()
python
wandb/integration/sb3/sb3.py
145
147
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,353
save_model
def save_model(self) -> None: self.model.save(self.path) wandb.save(self.path, base_path=self.model_save_path) if self.verbose > 1: logger.info(f"Saving model checkpoint to {self.path}")
python
wandb/integration/sb3/sb3.py
149
153
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,354
wandb_callback
def wandb_callback() -> "Callable": """Old style callback that will be deprecated in favor of WandbCallback. Please try the new logger for more features.""" warnings.warn( "wandb_callback will be deprecated in favor of WandbCallback. Please use WandbCallback for more features.", UserWarning, ...
python
wandb/integration/xgboost/xgboost.py
36
52
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,355
callback
def callback(env: "CallbackEnv") -> None: for k, v in env.evaluation_result_list: wandb.log({k: v}, commit=False) wandb.log({})
python
wandb/integration/xgboost/xgboost.py
47
50
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,356
__init__
def __init__( self, log_model: bool = False, log_feature_importance: bool = True, importance_type: str = "gain", define_metric: bool = True, ): self.log_model: bool = log_model self.log_feature_importance: bool = log_feature_importance self.importance...
python
wandb/integration/xgboost/xgboost.py
95
112
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,357
before_training
def before_training(self, model: Booster) -> Booster: """Run before training is finished.""" # Update W&B config config = model.save_config() wandb.config.update(json.loads(config)) return model
python
wandb/integration/xgboost/xgboost.py
114
120
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,358
after_training
def after_training(self, model: Booster) -> Booster: """Run after training is finished.""" # Log the booster model as artifacts if self.log_model: self._log_model_as_artifact(model) # Plot feature importance if self.log_feature_importance: self._log_featu...
python
wandb/integration/xgboost/xgboost.py
122
141
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,359
after_iteration
def after_iteration(self, model: Booster, epoch: int, evals_log: dict) -> bool: """Run after each iteration. Return True when training should stop.""" # Log metrics for data, metric in evals_log.items(): for metric_name, log in metric.items(): if self.define_metric: ...
python
wandb/integration/xgboost/xgboost.py
143
158
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,360
_log_model_as_artifact
def _log_model_as_artifact(self, model: Booster) -> None: model_name = f"{wandb.run.id}_model.json" # type: ignore model_path = Path(wandb.run.dir) / model_name # type: ignore model.save_model(str(model_path)) model_artifact = wandb.Artifact(name=model_name, type="model") mode...
python
wandb/integration/xgboost/xgboost.py
160
167
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,361
_log_feature_importance
def _log_feature_importance(self, model: Booster) -> None: fi = model.get_score(importance_type=self.importance_type) fi_data = [[k, fi[k]] for k in fi] table = wandb.Table(data=fi_data, columns=["Feature", "Importance"]) wandb.log( { "Feature Importance": wan...
python
wandb/integration/xgboost/xgboost.py
169
179
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,362
_define_metric
def _define_metric(self, data: str, metric_name: str) -> None: if "loss" in str.lower(metric_name): wandb.define_metric(f"{data}-{metric_name}", summary="min") elif str.lower(metric_name) in MINIMIZE_METRICS: wandb.define_metric(f"{data}-{metric_name}", summary="min") eli...
python
wandb/integration/xgboost/xgboost.py
181
189
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,363
__init__
def __init__(self, **kwargs): self.run = wandb.init(**kwargs) self.resources = {}
python
wandb/integration/sacred/__init__.py
58
60
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,364
started_event
def started_event( self, ex_info, command, host_info, start_time, config, meta_info, _id ): # TODO: add the source code file # TODO: add dependencies and metadata. self.__update_config(config)
python
wandb/integration/sacred/__init__.py
62
67
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,365
completed_event
def completed_event(self, stop_time, result): if result: if not isinstance(result, tuple): result = ( result, ) # transform single result to tuple so that both single & multiple results use same code for i, r in enumerate(result): ...
python
wandb/integration/sacred/__init__.py
69
93
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,366
artifact_event
def artifact_event(self, name, filename, metadata=None, content_type=None): if content_type is None: content_type = "file" artifact = wandb.Artifact(name, type=content_type) artifact.add_file(filename) self.run.log_artifact(artifact)
python
wandb/integration/sacred/__init__.py
95
100
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,367
resource_event
def resource_event(self, filename): """TODO: Maintain resources list.""" if filename not in self.resources: md5 = get_digest(filename) self.resources[filename] = md5
python
wandb/integration/sacred/__init__.py
102
106
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,368
log_metrics
def log_metrics(self, metrics_by_name, info): for metric_name, metric_ptr in metrics_by_name.items(): for _step, value in zip(metric_ptr["steps"], metric_ptr["values"]): if isinstance(value, numpy.ndarray): wandb.log({metric_name: wandb.Image(value)}) ...
python
wandb/integration/sacred/__init__.py
108
114
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,369
__update_config
def __update_config(self, config): for k, v in config.items(): self.run.config[k] = v self.run.config["resources"] = []
python
wandb/integration/sacred/__init__.py
116
119
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,370
wandb_log
def wandb_log( # noqa: C901 func=None, # /, # py38 only log_component_file=True, ): """Wrap a standard python function and log to W&B.""" import json import os from functools import wraps from inspect import Parameter, signature from kfp import components from kfp.components i...
python
wandb/integration/kfp/wandb_logging.py
1
182
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,371
isinstance_namedtuple
def isinstance_namedtuple(x): t = type(x) b = t.__bases__ if len(b) != 1 or b[0] != tuple: return False f = getattr(t, "_fields", None) if not isinstance(f, tuple): return False return all(type(n) == str for n in f)
python
wandb/integration/kfp/wandb_logging.py
30
38
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,372
get_iframe_html
def get_iframe_html(run): return f'<iframe src="{run.url}?kfp=true" style="border:none;width:100%;height:100%;min-width:900px;min-height:600px;"></iframe>'
python
wandb/integration/kfp/wandb_logging.py
40
41
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,373
get_link_back_to_kubeflow
def get_link_back_to_kubeflow(): wandb_kubeflow_url = os.getenv("WANDB_KUBEFLOW_URL") return f"{wandb_kubeflow_url}/#/runs/details/{{workflow.uid}}"
python
wandb/integration/kfp/wandb_logging.py
43
45
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,374
log_input_scalar
def log_input_scalar(name, data, run=None): run.config[name] = data wandb.termlog(f"Setting config: {name} to {data}")
python
wandb/integration/kfp/wandb_logging.py
47
49
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,375
log_input_artifact
def log_input_artifact(name, data, type, run=None): artifact = wandb.Artifact(name, type=type) artifact.add_file(data) run.use_artifact(artifact) wandb.termlog(f"Using artifact: {name}")
python
wandb/integration/kfp/wandb_logging.py
51
55
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,376
log_output_scalar
def log_output_scalar(name, data, run=None): if isinstance_namedtuple(data): for k, v in zip(data._fields, data): run.log({f"{func.__name__}.{k}": v}) else: run.log({name: data})
python
wandb/integration/kfp/wandb_logging.py
57
62
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,377
log_output_artifact
def log_output_artifact(name, data, type, run=None): artifact = wandb.Artifact(name, type=type) artifact.add_file(data) run.log_artifact(artifact) wandb.termlog(f"Logging artifact: {name}")
python
wandb/integration/kfp/wandb_logging.py
64
68
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,378
_log_component_file
def _log_component_file(func, run=None): name = func.__name__ output_component_file = f"{name}.yml" components._python_op.func_to_component_file(func, output_component_file) artifact = wandb.Artifact(name, type="kubeflow_component_file") artifact.add_file(output_component_file) ...
python
wandb/integration/kfp/wandb_logging.py
70
77
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,379
decorator
def decorator(func): input_scalars = {} input_artifacts = {} output_scalars = {} output_artifacts = {} for name, ann in func.__annotations__.items(): if name == "return": output_scalars[name] = ann elif isinstance(ann, output_types): ...
python
wandb/integration/kfp/wandb_logging.py
106
177
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,380
wrapper
def wrapper(*args, **kwargs): bound = new_sig.bind(*args, **kwargs) bound.apply_defaults() mlpipeline_ui_metadata_path = bound.arguments["mlpipeline_ui_metadata_path"] del bound.arguments["mlpipeline_ui_metadata_path"] with wandb.init( job_ty...
python
wandb/integration/kfp/wandb_logging.py
123
173
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,381
full_path_exists
def full_path_exists(full_func): def get_parent_child_pairs(full_func): components = full_func.split(".") parents, children = [], [] for i, _ in enumerate(components[:-1], 1): parent = ".".join(components[:i]) child = components[i] parents.append(parent) ...
python
wandb/integration/kfp/kfp_patch.py
46
61
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,382
get_parent_child_pairs
def get_parent_child_pairs(full_func): components = full_func.split(".") parents, children = [], [] for i, _ in enumerate(components[:-1], 1): parent = ".".join(components[:i]) child = components[i] parents.append(parent) children.append(child) ...
python
wandb/integration/kfp/kfp_patch.py
47
55
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,383
patch
def patch(module_name, func): module = wandb.util.get_module(module_name) success = False full_func = f"{module_name}.{func.__name__}" if not full_path_exists(full_func): wandb.termerror( f"Failed to patch {module_name}.{func.__name__}! Please check if this package/module is instal...
python
wandb/integration/kfp/kfp_patch.py
64
82
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,384
unpatch
def unpatch(module_name): if module_name in wandb.patched: for module, func in wandb.patched[module_name]: setattr(module, func, getattr(module, f"orig_{func}")) wandb.patched[module_name] = []
python
wandb/integration/kfp/kfp_patch.py
85
89
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,385
unpatch_kfp
def unpatch_kfp(): unpatch("kfp.components") unpatch("kfp.components._python_op") unpatch("wandb.integration.kfp")
python
wandb/integration/kfp/kfp_patch.py
92
95
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,386
patch_kfp
def patch_kfp(): to_patch = [ ( "kfp.components", create_component_from_func, ), ( "kfp.components._python_op", create_component_from_func, ), ( "kfp.components._python_op", _get_function_source_definitio...
python
wandb/integration/kfp/kfp_patch.py
98
123
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,387
wandb_log
def wandb_log( func=None, # /, # py38 only log_component_file=True, ): """Wrap a standard python function and log to W&B. NOTE: Because patching failed, this decorator is a no-op. """ from functools import wraps def decorator(func): @wraps(func) def wrapper(*args, **kw...
python
wandb/integration/kfp/kfp_patch.py
126
147
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,388
decorator
def decorator(func): @wraps(func) def wrapper(*args, **kwargs): return func(*args, **kwargs) return wrapper
python
wandb/integration/kfp/kfp_patch.py
137
142
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,389
wrapper
def wrapper(*args, **kwargs): return func(*args, **kwargs)
python
wandb/integration/kfp/kfp_patch.py
139
140
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,390
_get_function_source_definition
def _get_function_source_definition(func: Callable) -> str: """Get the source code of a function. This function is modified from KFP. The original source is below: https://github.com/kubeflow/pipelines/blob/b6406b02f45cdb195c7b99e2f6d22bf85b12268b/sdk/python/kfp/components/_python_op.py#L300-L319. """...
python
wandb/integration/kfp/kfp_patch.py
150
176
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,391
create_component_from_func
def create_component_from_func( func: Callable, output_component_file: Optional[str] = None, base_image: Optional[str] = None, packages_to_install: Optional[List[str]] = None, annotations: Optional[Mapping[str, str]] = None, ): '''Convert a Python function to a component and returns a task facto...
python
wandb/integration/kfp/kfp_patch.py
179
303
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,392
strip_type_hints
def strip_type_hints(source_code: str) -> str: """Strip type hints from source code. This function is modified from KFP. The original source is below: https://github.com/kubeflow/pipelines/blob/b6406b02f45cdb195c7b99e2f6d22bf85b12268b/sdk/python/kfp/components/_python_op.py#L237-L248. """ # For wa...
python
wandb/integration/kfp/kfp_patch.py
306
324
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,393
add_wandb_visualization
def add_wandb_visualization(run, mlpipeline_ui_metadata_path): """NOTE: To use this, you must modify your component to have an output called `mlpipeline_ui_metadata_path` AND call `wandb.init` yourself inside that component. Example usage: def my_component(..., mlpipeline_ui_metadata_path: OutputPath()): ...
python
wandb/integration/kfp/helpers.py
4
28
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,394
get_iframe_html
def get_iframe_html(run): return f'<iframe src="{run.url}?kfp=true" style="border:none;width:100%;height:100%;min-width:900px;min-height:600px;"></iframe>'
python
wandb/integration/kfp/helpers.py
19
20
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,395
__init__
def __init__( self, learn: "fastai.basic_train.Learner", log: Optional[Literal["gradients", "parameters", "all"]] = "gradients", save_model: bool = True, monitor: Optional[str] = None, mode: Literal["auto", "min", "max"] = "auto", input_type: Optional[Literal["ima...
python
wandb/integration/fastai/__init__.py
83
118
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,396
on_train_begin
def on_train_begin(self, **kwargs: Any) -> None: """Call watch method to log model topology, gradients & weights.""" # Set self.best, method inherited from "TrackerCallback" by "SaveModelCallback" super().on_train_begin() # Ensure we don't call "watch" multiple times if not Wand...
python
wandb/integration/fastai/__init__.py
120
130
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,397
on_epoch_end
def on_epoch_end( self, epoch: int, smooth_loss: float, last_metrics: list, **kwargs: Any ) -> None: """Log training loss, validation loss and custom metrics & log prediction samples & save model.""" if self.save_model: # Adapted from fast.ai "SaveModelCallback" curre...
python
wandb/integration/fastai/__init__.py
132
170
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,398
on_train_end
def on_train_end(self, **kwargs: Any) -> None: """Load the best model.""" if self.save_model: # Adapted from fast.ai "SaveModelCallback" if self.model_path.is_file(): with self.model_path.open("rb") as model_file: self.learn.load(model_file, pu...
python
wandb/integration/fastai/__init__.py
172
179
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,399
_wandb_log_predictions
def _wandb_log_predictions(self) -> None: """Log prediction samples.""" pred_log = [] if self.validation_data is None: return for x, y in self.validation_data: try: pred = self.learn.predict(x) except Exception: raise ...
python
wandb/integration/fastai/__init__.py
181
244
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }
2,400
__init__
def __init__(self, summary_op=None, steps_per_log=1000, history=None): self._summary_op = summary_op self._steps_per_log = steps_per_log self._history = history with telemetry.context() as tel: tel.feature.estimator_hook = True
python
wandb/integration/tensorflow/estimator_hook.py
27
33
{ "name": "Git-abouvier/wandb", "url": "https://github.com/Git-abouvier/wandb.git", "license": "MIT", "stars": 0, "forks": 0 }