deepy/core/tensor_conversion.py
def convert_to_neural_var(obj):
    """
    Convert object and a test object into neural var.
    :param obj: tensor or list or dict or tuple
    :param test_obj: NeuralVar or list or dict or tuple
    :return:
    """
    from theano.tensor.var import TensorVariable
    from deepy.core.neural_var import NeuralVariable
    if type(obj) == list:
        return [convert_to_neural_var(item) for item in obj]
    elif type(obj) == tuple:
        return tuple(convert_to_neural_var(list(obj)))
    elif type(obj) == dict:
        merged_map = {}
        for key in obj:
            merged_map[key] = convert_to_neural_var(obj[key])
        return merged_map
    elif type(obj) == MapDict:
        merged_map = {}
        for key in obj:
            merged_map[key] = convert_to_neural_var(obj[key])
        return MapDict(merged_map)
    elif type(obj) == TensorVariable:
        deepy_var = NeuralVariable(obj)
        if hasattr(obj, 'tag') and hasattr(obj.tag, 'last_dim'):
            deepy_var.output_dim = obj.tag.last_dim
        return deepy_var
    else:
        return obj
def convert_to_neural_var(obj):
    """
    Convert object and a test object into neural var.
    :param obj: tensor or list or dict or tuple
    :param test_obj: NeuralVar or list or dict or tuple
    :return:
    """
    from theano.tensor.var import TensorVariable
    from deepy.core.neural_var import NeuralVariable
    if type(obj) == list:
        return [convert_to_neural_var(item) for item in obj]
    elif type(obj) == tuple:
        return tuple(convert_to_neural_var(list(obj)))
    elif type(obj) == dict:
        merged_map = {}
        for key in obj:
            merged_map[key] = convert_to_neural_var(obj[key])
        return merged_map
    elif type(obj) == MapDict:
        merged_map = {}
        for key in obj:
            merged_map[key] = convert_to_neural_var(obj[key])
        return MapDict(merged_map)
    elif type(obj) == TensorVariable:
        deepy_var = NeuralVariable(obj)
        if hasattr(obj, 'tag') and hasattr(obj.tag, 'last_dim'):
            deepy_var.output_dim = obj.tag.last_dim
        return deepy_var
    else:
        return obj
def convert_to_neural_var ( obj ) : from theano . tensor . var import TensorVariable from deepy . core . neural_var import NeuralVariable if type ( obj ) == list : return [ convert_to_neural_var ( item ) for item in obj ] elif type ( obj ) == tuple : return tuple ( convert_to_neural_var ( list ( obj ) ) ) elif type ( obj ) == dict : merged_map = { } for key in obj : merged_map [ key ] = convert_to_neural_var ( obj [ key ] ) return merged_map elif type ( obj ) == MapDict : merged_map = { } for key in obj : merged_map [ key ] = convert_to_neural_var ( obj [ key ] ) return MapDict ( merged_map ) elif type ( obj ) == TensorVariable : deepy_var = NeuralVariable ( obj ) if hasattr ( obj , 'tag' ) and hasattr ( obj . tag , 'last_dim' ) : deepy_var . output_dim = obj . tag . last_dim return deepy_var else : return obj
Convert object and a test object into neural var.
    :param obj: tensor or list or dict or tuple
    :param test_obj: NeuralVar or list or dict or tuple
    :return:
Convert object and a test object into neural var . : param obj : tensor or list or dict or tuple : param test_obj : NeuralVar or list or dict or tuple : return :