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# ClearML Explicit Logging
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Using the **ClearML** [Logger ](https://github.com/allegroai/clearml/blob/master/clearml/logger.py ) module and other **ClearML** features, you can explicitly log any of the following:
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* Report graphs and images
* [Scalar metrics ](#scalar-metrics )
* [Histograms ](#histograms )
* [Line plots ](#line-plots )
* [2D scatter diagrams ](#2d-scatter-diagrams )
* [3D scatter diagrams ](#3d-scatter-diagrams )
* [Confusion matrices ](#confusion-matrices )
* [Surface diagrams ](#surface-diagrams )
* [Images ](#images )
* Track hyper-parameters and OS environment variables
* Logging experiment parameter [dictionaries ](#logging-experiment-parameter-dictionaries )
* Specifying [environment variables ](#specifying-environment-variables-to-track ) to track
* Message logging
* [Reporting text without formatting ](#reporting-text-without-formatting )
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Additionally, the **ClearML** Logger module provides methods that allow you to do the following:
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* Get the [current logger]()
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* Overrride the ClearML configuration file with a [default upload destination]() for images and files
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## Graphs and Images
### Scalar Metrics
Use to report scalar metrics by iteration as a line plot.
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/scalar_reporting.py )) with the following method.
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**Method**:
```python
def report_scalar(self, title, series, value, iteration)
```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The data series label.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > value
< / td >
< td > float
< / td >
< td > The scalar metric data value (y-axis).
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### Histograms
Use to report any data by iteration as a histogram.
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/scatter_hist_confusion_mat_reporting.py )) with the following method.
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**Method**:
```python
def report_histogram(self, title, series, values, iteration, labels=None, xlabels=None)
```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The data series label.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > values
< / td >
< td > Either:
< ul >
< li > list of float
< / li >
< li > numpy array
< / li >
< / ul >
< / td >
< td > The histogram data values (y-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > labels
< / td >
< td > list of strings
< / td >
< td > Labels for each bar group in the histogram. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > xlabels
< / td >
< td > list of strings
< / td >
< td > Labels for each bucket in the histogram. Each label in the < code > xlabels< / code > list corresponds to a value in the < code > values< / code > list (or numpy array). The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### Line Plots
Use to report any data by iteration as a single or multiple line plot.
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/scatter_hist_confusion_mat_reporting.py )) with the following method.
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**Method**:
```python
def report_line_plot(self, title, series, iteration, xaxis, yaxis, mode='lines', reverse_xaxis=False, comment=None)
```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > LineSeriesInfo
< / td >
< td > One (single line plot) or more (multiple line plot) series of data.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > comment
< / td >
< td > string
< / td >
< td > Any text (e.g., subtitle or other comment) which displays under the plot title. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > mode
< / td >
< td > string
< / td >
< td > Type of line plot. The values are:
< ul >
< li > < code > lines< / code > - lines connecting data points (default)
< / li >
< li > < code > markers< / code > - markers for each data point
< / li >
< li > < code > lines+markers< / code > - lines and markers
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > reverse_xaxis
< / td >
< td > boolean
< / td >
< td > Indicates whether to display the x-axis values in ascending or descending order. The values are:
< ul >
< li > < code > True< / code > - descending order
< / li >
< li > < code > False< / code > - ascending order (default)
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > xaxis
< / td >
< td > string
< / td >
< td > x-axis title.
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > yaxis
< / td >
< td > string
< / td >
< td > y-axis title.
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### 2D Scatter Diagrams
Use to report any vector data as a 2D scatter diagram.
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/scatter_hist_confusion_mat_reporting.py )) with the following method.
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**Method**:
```python
def report_scatter2d(self, title, series, scatter, iteration, xaxis=None, yaxis=None, labels=None, mode='lines', comment=None)
```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > scatter
< / td >
< td > Either:
< ul >
< li > list of (pairs of x, y)
< / li >
< li > ndarray
< / li >
< / ul >
< / td >
< td > The scatter data. For example, a list of pairs in the form: < code > [(x1,y1),(x2,y2),(x3,y3),...]< / code > .
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The data series label.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > comment
< / td >
< td > string
< / td >
< td > Any text (e.g., subtitle or other comment) which displays under the plot title. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > labels
< / td >
< td > list of strings
< / td >
< td > Label text per data point in the scatter diagram. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > mode
< / td >
< td > string
< / td >
< td > Type of 2D scatter diagram. The values are:
< ul >
< li > < code > lines< / code > - lines connecting data points (default)
< / li >
< li > < code > markers< / code > - markers for each data point
< / li >
< li > < code > lines+markers< / code > - lines and markers
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > xaxis
< / td >
< td > string
< / td >
< td > x-axis title. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > yaxis
< / td >
< td > string
< / td >
< td > y-axis title. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### 3D Scatter Diagrams
Use to report any array data as a 3D scatter diagram.
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/3d_plots_reporting.py )) with the following method.
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**Method**:
```python
def report_scatter3d(self, title, series, scatter, iteration, labels=None, mode='markers', fill=False, comment=None)
```
**Argument**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > scatter
< / td >
< td > Either:
< ul >
< li > list of (pairs of x, y, z)
< / li >
< li > ndarray
< / li >
< li > list of series [[(x1,y1,z1)...]]
< / li >
< / ul >
< / td >
< td > The scatter data. For example, a list of series in the form:
< code > [[(x1,y1,z1),(x2,y2,z2),...],[(x3,y3,z3),(x4,y4,z4),...],[(x5,y5,z5),(x6,y6,z6),...]]< / code >
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The data series label.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > comment
< / td >
< td > string
< / td >
< td > Any text (e.g., subtitle or other comment) which displays under the plot title. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > fill
< / td >
< td > boolean
< / td >
< td > Indicates whether to fill the area under the scatter diagram. The values are:
< ul >
< li > < code > True< / code > - fill
< / li >
< li > < code > False< / code > - do not fill (default)
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > labels
< / td >
< td > list of strings
< / td >
< td > Label text per data point in the scatter. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > mode
< / td >
< td > string
< / td >
< td > Type of 3D scatter diagram. The values are:
< ul >
< li > < code > lines< / code >
< / li >
< li > < code > markers< / code >
< / li >
< li > < code > lines+markers< / code >
< / li >
< / ul >
The default values is < code > lines< / code > .
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### Confusion Matrices
Use to report a heat-map matrix as a confusion matrix. You can also plot a heat-map as a [surface diagram ](#surface-diagrams ).
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/scatter_hist_confusion_mat_reporting.py )) with the following method.
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**Method**:
```python
def report_confusion_matrix(self, title, series, matrix, iteration, xlabels=None, ylabels=None, comment=None)
```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > matrix
< / td >
< td > ndarray
< / td >
< td > A heat-map matrix.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The data series label.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > xlabels
< / td >
< td > list of strings
< / td >
< td > Label per column of the matrix. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > ylabels
< / td >
< td > list of strings
< / td >
< td > Label per row of the matrix. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### Surface Diagrams
Use to plot a heat-map matrix as a surface diagram. You can also plot a heat-map as a [confusion matrix ](#confusion-matrices ).
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/3d_plots_reporting.py )) with the following method.
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**Method**:
```python
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def report_surface(self, title, series, matrix, iteration, xlabels=None, ylabels=None, xaxis=None, yaxis=None, camera=None, comment=None)
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```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number (x-axis).
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > matrix
< / td >
< td > ndarray
< / td >
< td > A heat-map matrix.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The data series label.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The plot title.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > camera
< / td >
< td > tuple
< / td >
< td > The position of the camera as (x, y, x), if applicable.
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > comment
< / td >
< td > string
< / td >
< td > Any text (e.g., subtitle or other comment) which displays under the plot title. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > xlabels
< / td >
< td > list of strings
< / td >
< td > Label per column of the matrix. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
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< td > xaxis
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< / td >
< td > string
< / td >
< td > x-axis title.
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > ylabels
< / td >
< td > list of strings
< / td >
< td > Label per row of the matrix. The default value is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
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< td > yaxis
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< / td >
< td > string
< / td >
< td > y-axis title.
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### Images
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Use to report an image and upload its contents to the bucket specified in the **ClearML** configuration file,
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or a [a default upload destination ](#set-default-upload-destination ), if you set a default.
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/manual_reporting.py )) with the following method.
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**Method**:
```python
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def report_image(self, title, series, iteration, local_path=None, matrix=None, max_image_history=None, delete_after_upload=False)
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```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > iteration
< / td >
< td > integer
< / td >
< td > The iteration number.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > series
< / td >
< td > string
< / td >
< td > The label of the series.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > title
< / td >
< td > string
< / td >
< td > The title of the image.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > delete_after_upload
< / td >
< td > boolean
< / td >
< td > Indicates whether to delete the local copy of the file after uploading it. The values are:
< ul >
< li > < code > True< / code > - delete
< / li >
< li > < code > False< / code > - do not delete (default)
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > matrix
< / td >
< td > ndarray
< / td >
< td > A 3D numpy.ndarray object containing image data (RGB). If < code > path< / code > is not specified, then < code > matrix< / code > is required. The default values is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > max_image_history
< / td >
< td > integer
< / td >
< td > The maximum number of images to store per metric / variant combination. For an unlimited number of images to store, specify a negative number.
The default value which is set in the global configuration is < code > 5< / code > .
< / td >
< td > No
< / td >
< / tr >
< tr >
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< td > local_path
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< / td >
< td > string
< / td >
< td > The path of the image file. If < code > matrix< / code > is not specified, then < code > path< / code > is required. The default values is < code > None< / code > .
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
## Hyper-parameters and Environment Variables
### Logging Experiment Parameter Dictionaries
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In order for **ClearML** to log a dictionary of parameters, use the `Task.connect` method.
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For example, to log the hyper-parameters < code > learning_rate< / code > , < code > batch_size< / code > , < code > display_step< / code > , < code > model_path< / code > , < code > n_hidden_1< / code > , and < code > n_hidden_2< / code > :
```python
# Create a dictionary of parameters
parameters_dict = { 'learning_rate': 0.001, 'batch_size': 100, 'display_step': 1,
'model_path': "/tmp/model.ckpt", 'n_hidden_1': 256, 'n_hidden_2': 256 }
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# Connect the dictionary to your ClearML Task
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parameters_dict = Task.current_task().connect(parameters_dict)
```
### Specifying Environment Variables to Track
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By setting the `CLEARML_LOG_ENVIRONMENT` environment variable, make **ClearML** log either:
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* All environment variables
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export CLEARML_LOG_ENVIRONMENT="*"
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* Specific environment variables
For example, log `PWD` and `PYTHONPATH`
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export CLEARML_LOG_ENVIRONMENT="PWD,PYTHONPATH"
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* No environment variables
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export CLEARML_LOG_ENVIRONMENT=
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## Logging Messages
Use the methods in this section to log various types of messages. The method name describes the type of message.
### Debugging Messages
**Method**:
```python
def debug(self, msg, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### Informational Messages
**Method**:
```python
def info(self, msg, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### Warnings
**Method**:
```python
def warn(self, msg, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:< a name = "log_arguments" > < / a >
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### General Errors
**Method**:
```python
def error(self, msg, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### Critical Errors
**Method**:
```python
def critical(self, msg, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### Fatal Errors
**Method**:
```python
def fatal(self, msg, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
### Console and Logger Messages
**Method**:
```python
def console(self, msg, level=logging.INFO, omit_console=False, *args, * *kwargs)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > level
< / td >
< td > string
< / td >
< td > The log level. The values are:
< ul >
< li > < code > logging.DEBUG< / code >
< / li >
< li > < code > logging.INFO< / code >
< / li >
< li > < code > logging.WARNING< / code >
< / li >
< li > < code > logging.ERROR< / code >
< / li >
< li > < code > logging.FATAL< / code >
< / li >
< li > < code > logging.CRITICAL< / code >
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > omit_console
< / td >
< td > boolean
< / td >
< td > Indicates whether to send the message to the log only. The values are:
< ul >
< li > < code > True< / code > - send the message to the log only
< / li >
< li > < code > False< / code > - send the message to the console and the log
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
### Reporting Text Without Formatting
**Method**:
```python
def report_text(self, msg, level=logging.INFO, print_console=False, *args, * *_)
```
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First [get the current logger ](#get-the-current-logger ) and then use it (see an [example script ](https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py )) with the following method.
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**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > msg
< / td >
< td > string
< / td >
< td > The text to log.
< / td >
< td > Yes
< / td >
< / tr >
< tr >
< td > level
< / td >
< td > string
< / td >
< td > The log level. The values are:
< ul >
< li > < code > logging.DEBUG< / code >
< / li >
< li > < code > logging.INFO< / code >
< / li >
< li > < code > logging.WARNING< / code >
< / li >
< li > < code > logging.ERROR< / code >
< / li >
< li > < code > logging.FATAL< / code >
< / li >
< li > < code > logging.CRITICAL< / code >
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< tr >
< td > print_console
< / td >
< td > boolean
< / td >
< td > Indicates whether to log to the console, in addition to the log. The values are:
< ul >
< li > < code > True< / code > - print to the console and log
< / li >
< li > < code > False< / code > - print to the log, only (default)
< / li >
< / ul >
< / td >
< td > No
< / td >
< / tr >
< / tbody >
< / table >
## Logger Object and Storage Methods
### Get the Current Logger
Use to return a reference to the current logger object.
**Method**:
```python
def current_logger(cls)
```
**Arguments**:
None.
### Set Default Upload Destination
Use to specify the default destination storage location used for uploading images.
Images are uploaded and a link to the image is reported.
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Credentials for the storage location are in the global configuration file (for example, on Linux, < code > ~/clearml.conf< / code > ).
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**Method**:
```python
def set_default_upload_destination(self, uri)
```
**Arguments**:
< table width = "100%" >
< thead >
< tr >
< th width = "15%" > Parameter
< / th >
< th width = "25%" > Type
< / th >
< th width = "55%" > Description
< / th >
< th width = "5%" > Mandatory
< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > uri
< / td >
< td > string
< / td >
< td > The destination storage location, for example < code > s3://bucket/directory/< / code > or < code > file:///tmp/debug/< / code > .
< / td >
< td > Yes
< / td >
< / tr >
< / tbody >
< / table >
