Metadata-Version: 2.1
Name: dam4ml
Version: 1.0.0
Summary: Dam4ML client library
Home-page: https://github.com/numericube/dam4ml-client
Author: NumeriCube
Author-email: support@numericube.com
License: GPLv3
Description: =====================
        DAM4ML CLIENT LIBRARY
        =====================
        
        This is the dam4ml client library.
        
        Installation
        ------------
        
        pip install dam4ml
        
        (Ugh, pretty is, uh?)
        
        Basic usage
        -----------
        
        .. code-block:: python
        
            from dam4ml import client
            from dam4ml import transforms
        
            # Login to DAM4ML
            dataset = client.connect("mnist", api_key="")
        
            # (optional) Pre-load the whole dataset for offline performance.
            # This will take a while but will improve further performance.
            dataset.load()
        
            # (optional) You can pre-filter your dataset. See DAM4ML website
            # for more information about how to build your filter
            filter = {
                "tag_slug": "test",
            }
        
            # Iterate through all dataset items
            for item in dataset.as_dict(**filter):
                # ...process each dataset item here.
                pass
        
            # Convert dataset to a pynum array
            dataset.as_pynum(**filter)
        
            # Even better, simulate what Keras' load_dataset() method would do:
            pn_dataset = dataset.as_pynum()
            (x_train, y_train) = pn_dataset[]
            (x_val, y_val) = pn_dataset[]
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Description-Content-Type: text/x-rst
