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Update docs (#520)
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@ -101,7 +101,8 @@ input_model = InputModel.import_model(
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task.connect(input_model)
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task.connect(input_model)
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```
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```
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## Querying Models
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## Accessing Models
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### Querying Models
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Retrieve a list of model objects by querying the system by model names, projects, tags, and more, using the
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Retrieve a list of model objects by querying the system by model names, projects, tags, and more, using the
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[`Model.query_models`](../references/sdk/model_model.md#modelquery_models) and / or
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[`Model.query_models`](../references/sdk/model_model.md#modelquery_models) and / or
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the [`InputModel.query_models`](../references/sdk/model_inputmodel.md#inputmodelquery_models) class methods. These
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the [`InputModel.query_models`](../references/sdk/model_inputmodel.md#inputmodelquery_models) class methods. These
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@ -127,7 +128,7 @@ model_list = Model.query_models(
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)
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)
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```
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```
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### Tag Filters
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#### Tag Filters
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The `tags` field supports advanced queries through combining tag names and operators into a list.
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The `tags` field supports advanced queries through combining tag names and operators into a list.
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The supported operators are:
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The supported operators are:
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@ -177,6 +178,31 @@ The default operator for a query is `or`, unless `and` is placed at the beginnin
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)
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)
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```
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```
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### Retrieving Models
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Retrieve a local copy of a ClearML model through a `Model`/`InputModel` object's [`get_local_copy()`](../references/sdk/model_outputmodel.md#get_local_copy).
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The method returns a path to a cached local copy of the model. In the case that the model is already cached, you can set
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`force_download` to `True` in order to download a fresh version.
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## Logging Metrics and Plots
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Use the following methods to explicitly log additional information to your models.
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These methods can be used on `Model`, `InputModel`, and/or `OutputModel` objects:
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* Scalars
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* Scalar series plots - [`report_scalar`](../references/sdk/model_outputmodel.md#report_scalar)
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* Single metric values - [`report_single_value`](../references/sdk/model_outputmodel.md#report_single_value)
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* Plots
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* 2d plots
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* Histogram - [`report_histogram`](../references/sdk/model_outputmodel.md#report_historgram)
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* Vector as histogram plot - [`report_vector`](../references/sdk/model_outputmodel.md#report_vector)
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* Table - [`report_table`](../references/sdk/model_outputmodel.md#report_table)
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* Line plot - [`report_line_plot`](../references/sdk/model_outputmodel.md#report_line_plot)
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* Scatter plot - [`report_scatter2d`](../references/sdk/model_outputmodel.md#report_scatter2d)
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* Confusion matrix (heat map) - [`report_confusion_matrix`](../references/sdk/model_outputmodel.md#report_confusion_matrix) & [`report_matrix`](../references/sdk/model_outputmodel.md#report_matrix)
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* 3d plots
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* Scatter plot - [`report_scatter3d`](../references/sdk/model_outputmodel.md#report_scatter3d)
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* Surface plot - [`report_surface`](../references/sdk/model_outputmodel.md#report_surface)
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## SDK Reference
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## SDK Reference
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For information about all model methods, see the following SDK reference pages:
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For information about all model methods, see the following SDK reference pages:
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@ -409,6 +409,11 @@ folder, which can later be uploaded to the [ClearML Server](../deploying_clearml
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Before initializing a Task, use the [Task.set_offline](../references/sdk/task.md#taskset_offline) class method and set
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Before initializing a Task, use the [Task.set_offline](../references/sdk/task.md#taskset_offline) class method and set
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the `offline_mode` argument to `True`. The method returns the Task ID and a path to the session folder.
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the `offline_mode` argument to `True`. The method returns the Task ID and a path to the session folder.
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:::caution
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Notice that the `Task.set_offline` method only works with tasks created using `Task.init` and not with those created
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using the `Task.create` method.
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:::
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```python
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```python
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from clearml import Task
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from clearml import Task
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# Use the set_offline class method before initializing a Task
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# Use the set_offline class method before initializing a Task
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@ -436,6 +441,17 @@ Upload the execution data that the Task captured offline to the ClearML Server u
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In the `session_folder_zip` argument, insert the path to the zip folder containing the session.
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In the `session_folder_zip` argument, insert the path to the zip folder containing the session.
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To upload the session from the same script that created it, first close the task then disable offline mode:
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```python
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Task.set_offline(offline_mode=True)
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task = Task.init(project_name="examples", task_name="my_task")
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# task code
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task.close()
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Task.set_offline(False)
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Task.import_offline_session(task.get_offline_mode_folder())
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```
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You can also use the offline task to update the execution of an existing previously executed task by providing the
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You can also use the offline task to update the execution of an existing previously executed task by providing the
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previously executed task’s ID. To avoid overwriting metrics, you can specify the initial iteration offset with
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previously executed task’s ID. To avoid overwriting metrics, you can specify the initial iteration offset with
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`iteration_offset`.
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`iteration_offset`.
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@ -11,6 +11,12 @@ local folder, which can be later uploaded to the [ClearML Server](../deploying_c
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Before initializing a Task, use the [Task.set_offline](../references/sdk/task.md#taskset_offline) class method and set the
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Before initializing a Task, use the [Task.set_offline](../references/sdk/task.md#taskset_offline) class method and set the
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`offline_mode` argument to `True`.
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`offline_mode` argument to `True`.
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:::caution
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Notice that the `Task.set_offline` method only works with tasks created using `Task.init` and not with those created
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using the `Task.create` method.
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:::
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```python
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```python
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from clearml import Task
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from clearml import Task
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# Use the set_offline class method before initializing a Task
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# Use the set_offline class method before initializing a Task
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@ -58,6 +64,17 @@ Upload the session's execution data that the Task captured offline to the ClearM
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In the `session_folder_zip` argument, insert the path to the zip folder containing the session.
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In the `session_folder_zip` argument, insert the path to the zip folder containing the session.
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To upload the session from the same script that created it, first close the task then disable offline mode:
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```python
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Task.set_offline(offline_mode=True)
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task = Task.init(project_name="examples", task_name="my_task")
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# task code
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task.close()
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Task.set_offline(False)
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Task.import_offline_session(task.get_offline_mode_folder())
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```
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You can also use the offline task to update the execution of an existing previously executed task by providing the
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You can also use the offline task to update the execution of an existing previously executed task by providing the
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previously executed task’s ID. To avoid overwriting metrics, you can specify the initial iteration offset with
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previously executed task’s ID. To avoid overwriting metrics, you can specify the initial iteration offset with
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`iteration_offset`.
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`iteration_offset`.
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