New console logger with expanded progress tracking

spacy/errors.py

@@ -962,6 +962,7 @@ class Errors(metaclass=ErrorsWithCodes):
  E1046 = ("{cls_name} is an abstract class and cannot be instantiated. If you are looking for spaCy's default "
  "knowledge base, use `InMemoryLookupKB`.")
  E1047 = ("`find_threshold()` only supports components with a `scorer` attribute.")
+ E1048 = ("Got '{unexpected}' as console progress bar type, but expected one of the following: {expected}")
 
 
 # Deprecated model shortcuts, only used in errors and warnings

spacy/training/loggers.py

@@ -26,14 +26,36 @@ def setup_table(
  return final_cols, final_widths, ["r" for _ in final_widths]
 
 
+# We cannot rename this method as it's directly imported
+# and used by external packages such as spacy-loggers.
 @registry.loggers("spacy.ConsoleLogger.v2")
 def console_logger(
  progress_bar: bool = False,
  console_output: bool = True,
  output_file: Optional[Union[str, Path]] = None,
 ):
  """The ConsoleLogger.v2 prints out training logs in the console and/or saves them to a jsonl file.
- progress_bar (bool): Whether the logger should print the progress bar.
+ progress_bar (bool): Whether the logger should print a progress bar tracking the steps till the next evaluation pass.
+ console_output (bool): Whether the logger should print the logs on the console.
+ output_file (Optional[Union[str, Path]]): The file to save the training logs to.
+ """
+ return console_logger_v3(
+ progress_bar=None if progress_bar is False else "eval",
+ console_output=console_output,
+ output_file=output_file,
+ )
+
+
+@registry.loggers("spacy.ConsoleLogger.v3")
+def console_logger_v3(
+ progress_bar: Optional[str] = None,
+ console_output: bool = True,
+ output_file: Optional[Union[str, Path]] = None,
+):
+ """The ConsoleLogger.v3 prints out training logs in the console and/or saves them to a jsonl file.
+ progress_bar (Optional[str]): Type of progress bar to show in the console. Allowed values:
+ train - Tracks the number of steps from the beginning of training until the full training run is complete (training.max_steps is reached).
+ eval - Tracks the number of steps between the previous and next evaluation (training.eval_frequency is reached).
  console_output (bool): Whether the logger should print the logs on the console.
  output_file (Optional[Union[str, Path]]): The file to save the training logs to.
  """
@@ -70,6 +92,7 @@ def setup_printer(
  for name, proc in nlp.pipeline
  if hasattr(proc, "is_trainable") and proc.is_trainable
  ]
+ max_steps = nlp.config["training"]["max_steps"]
  eval_frequency = nlp.config["training"]["eval_frequency"]
  score_weights = nlp.config["training"]["score_weights"]
  score_cols = [col for col, value in score_weights.items() if value is not None]
@@ -84,6 +107,13 @@ def setup_printer(
  write(msg.row(table_header, widths=table_widths, spacing=spacing))
  write(msg.row(["-" * width for width in table_widths], spacing=spacing))
  progress = None
+ expected_progress_types = ("train", "eval")
+ if progress_bar is not None and progress_bar not in expected_progress_types:
+ raise ValueError(
+ Errors.E1048.format(
+ unexpected=progress_bar, expected=expected_progress_types
+ )
+ )
 
  def log_step(info: Optional[Dict[str, Any]]) -> None:
  nonlocal progress
@@ -141,11 +171,23 @@ def log_step(info: Optional[Dict[str, Any]]) -> None:
  )
  )
  if progress_bar:
+ if progress_bar == "train":
+ total = max_steps
+ desc = f"Last Eval Epoch: {info['epoch']}"
+ initial = info["step"]
+ else:
+ total = eval_frequency
+ desc = f"Epoch {info['epoch']+1}"
+ initial = 0
  # Set disable=None, so that it disables on non-TTY
  progress = tqdm.tqdm(
- total=eval_frequency, disable=None, leave=False, file=stderr
+ total=total,
+ disable=None,
+ leave=False,
+ file=stderr,
+ initial=initial,
  )
- progress.set_description(f"Epoch {info['epoch']+1}")
+ progress.set_description(desc)
 
  def finalize() -> None:
  if output_stream:

website/docs/api/top-level.md

@@ -513,7 +513,7 @@ a [Weights & Biases](https://www.wandb.com/) dashboard.
 Instead of using one of the built-in loggers, you can
 [implement your own](/usage/training#custom-logging).
 
-#### spacy.ConsoleLogger.v2 {#ConsoleLogger tag="registered function"}
+#### spacy.ConsoleLogger.v2 {tag="registered function"}
 
 > #### Example config
 >
@@ -564,11 +564,33 @@ start decreasing across epochs.
 
  </Accordion>
 
-| Name | Description |
-| ---------------- | --------------------------------------------------------------------- |
-| `progress_bar` | Whether the logger should print the progress bar ~~bool~~ |
-| `console_output` | Whether the logger should print the logs on the console. ~~bool~~ |
-| `output_file` | The file to save the training logs to. ~~Optional[Union[str, Path]]~~ |
+| Name | Description |
+| ---------------- | ---------------------------------------------------------------------------------------------------------------------------- |
+| `progress_bar` | Whether the logger should print a progress bar tracking the steps till the next evaluation pass (default: `False`). ~~bool~~ |
+| `console_output` | Whether the logger should print the logs in the console (default: `True`). ~~bool~~ |
+| `output_file` | The file to save the training logs to (default: `None`). ~~Optional[Union[str, Path]]~~ |
+
+#### spacy.ConsoleLogger.v3 {#ConsoleLogger tag="registered function"}
+
+> #### Example config
+>
+> ```ini
+> [training.logger]
+> @loggers = "spacy.ConsoleLogger.v3"
+> progress_bar = "all_steps"
+> console_output = true
+> output_file = "training_log.jsonl"
+> ```
+
+Writes the results of a training step to the console in a tabular format and
+optionally saves them to a `jsonl` file.
+
+| Name | Description |
+| ---------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `progress_bar` | Type of progress bar to show in the console: `"train"`, `"eval"` or `None`. |
+| | The bar tracks the number of steps until `training.max_steps` and `training.eval_frequency` are reached respectively (default: `None`). ~~Optional[str]~~ |
+| `console_output` | Whether the logger should print the logs in the console (default: `True`). ~~bool~~ |
+| `output_file` | The file to save the training logs to (default: `None`). ~~Optional[Union[str, Path]]~~ |
 
 ## Readers {#readers}