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	pipe_name instead of section in debug_model
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				|  | @ -16,7 +16,7 @@ def debug_model_cli( | |||
|     # fmt: off | ||||
|     ctx: typer.Context,  # This is only used to read additional arguments | ||||
|     config_path: Path = Arg(..., help="Path to config file", exists=True), | ||||
|     section: str = Arg(..., help="Section that defines the model to be analysed"), | ||||
|     pipe_name: str = Arg(..., help="Name of the pipe of which the model should be analysed"), | ||||
|     layers: str = Opt("", "--layers", "-l", help="Comma-separated names of layer IDs to print"), | ||||
|     dimensions: bool = Opt(False, "--dimensions", "-DIM", help="Show dimensions"), | ||||
|     parameters: bool = Opt(False, "--parameters", "-PAR", help="Show parameters"), | ||||
|  | @ -53,20 +53,20 @@ def debug_model_cli( | |||
|     cfg = Config().from_disk(config_path) | ||||
|     with show_validation_error(): | ||||
|         try: | ||||
|             _, config = util.load_model_from_config(cfg, overrides=config_overrides) | ||||
|             nlp, config = util.load_model_from_config(cfg, overrides=config_overrides) | ||||
|         except ValueError as e: | ||||
|             msg.fail(str(e), exits=1) | ||||
|     seed = config["pretraining"]["seed"] | ||||
|     seed = config.get("training", {}).get("seed", None) | ||||
|     if seed is not None: | ||||
|         msg.info(f"Fixing random seed: {seed}") | ||||
|         fix_random_seed(seed) | ||||
| 
 | ||||
|     component = dot_to_object(config, section) | ||||
|     component = nlp.get_pipe(pipe_name) | ||||
|     if hasattr(component, "model"): | ||||
|         model = component.model | ||||
|     else: | ||||
|         msg.fail( | ||||
|             f"The section '{section}' does not specify an object that holds a Model.", | ||||
|             f"The component '{pipe_name}' does not specify an object that holds a Model.", | ||||
|             exits=1, | ||||
|         ) | ||||
|     debug_model(model, print_settings=print_settings) | ||||
|  |  | |||
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