def convert_constant(params, w_name, scope_name, inputs, layers, weights, names):
    """
    Convert constant layer.

    Args:
        params: dictionary with layer parameters
        w_name: name prefix in state_dict
        scope_name: pytorch scope name
        inputs: pytorch node inputs
        layers: dictionary with keras tensors
        weights: pytorch state_dict
        names: use short names for keras layers
    """
    print('Converting constant ...')

    params_list = params['value'].numpy()

    def target_layer(x, value=params_list):
        return tf.constant(value.tolist(), shape=value.shape)

    lambda_layer = keras.layers.Lambda(target_layer)
    layers[scope_name + '_np'] = params_list  # ad-hoc
    layers[scope_name] = lambda_layer(layers[list(layers.keys())[0]])
def convert_constant(params, w_name, scope_name, inputs, layers, weights, names):
    """
    Convert constant layer.

    Args:
        params: dictionary with layer parameters
        w_name: name prefix in state_dict
        scope_name: pytorch scope name
        inputs: pytorch node inputs
        layers: dictionary with keras tensors
        weights: pytorch state_dict
        names: use short names for keras layers
    """
    print('Converting constant ...')

    params_list = params['value'].numpy()

    def target_layer(x, value=params_list):
        return tf.constant(value.tolist(), shape=value.shape)

    lambda_layer = keras.layers.Lambda(target_layer)
    layers[scope_name + '_np'] = params_list  # ad-hoc
    layers[scope_name] = lambda_layer(layers[list(layers.keys())[0]])
def convert_constant ( params , w_name , scope_name , inputs , layers , weights , names ) : print ( 'Converting constant ...' ) params_list = params [ 'value' ] . numpy ( ) def target_layer ( x , value = params_list ) : return tf . constant ( value . tolist ( ) , shape = value . shape ) lambda_layer = keras . layers . Lambda ( target_layer ) layers [ scope_name + '_np' ] = params_list # ad-hoc layers [ scope_name ] = lambda_layer ( layers [ list ( layers . keys ( ) ) [ 0 ] ] )
Convert constant layer.

    Args:
        params: dictionary with layer parameters
        w_name: name prefix in state_dict
        scope_name: pytorch scope name
        inputs: pytorch node inputs
        layers: dictionary with keras tensors
        weights: pytorch state_dict
        names: use short names for keras layers
Convert constant layer .