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@@ -38,22 +38,22 @@ during training and validation.
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Integrate ClearML with the following steps:
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1. Create a `ClearMLLogger` object:
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```python
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from ignite.contrib.handlers.clearml_logger import *
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```python
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from ignite.contrib.handlers.clearml_logger import *
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clearml_logger = ClearMLLogger(task_name="ignite", project_name="examples")
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```
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This creates a [ClearML Task](../fundamentals/task.md) called `ignite` in the `examples` project, which captures your
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script's information, including Git details, uncommitted code, python environment.
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clearml_logger = ClearMLLogger(task_name="ignite", project_name="examples")
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```
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This creates a [ClearML Task](../fundamentals/task.md) called `ignite` in the `examples` project, which captures your
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script's information, including Git details, uncommitted code, python environment.
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You can also pass the following parameters to the `ClearMLLogger` object:
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* `task_type` – The type of experiment (see [task types](../fundamentals/task.md#task-types)).
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* `report_freq` – The histogram processing frequency (handles histogram values every X calls to the handler). Affects
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`GradsHistHandler` and `WeightsHistHandler` (default: 100).
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* `histogram_update_freq_multiplier` – The histogram report frequency (report first X histograms and once every X
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reports afterwards) (default: 10).
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* `histogram_granularity` - Histogram sampling granularity (default: 50).
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You can also pass the following parameters to the `ClearMLLogger` object:
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* `task_type` – The type of experiment (see [task types](../fundamentals/task.md#task-types)).
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* `report_freq` – The histogram processing frequency (handles histogram values every X calls to the handler). Affects
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`GradsHistHandler` and `WeightsHistHandler` (default: 100).
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* `histogram_update_freq_multiplier` – The histogram report frequency (report first X histograms and once every X
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reports afterwards) (default: 10).
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* `histogram_granularity` - Histogram sampling granularity (default: 50).
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1. Attach the `ClearMLLogger` to output handlers to log metrics:
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